Singidunum Journal - Vol 11 No 1 by Singidunum University

Vol. 11 No. 1

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Vol. 11 No. 1 P��: Singidunum University

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Professor Milovan Stanišić, Singidunum University mstanisic@singidunum.ac.rs Emeritus Slobodan Unković, Singidunum University sunkovic@singidunum.ac.rs Professor Francesco Frangialli, UNWTO frangialli@gmail.com Professor Gunther Friedl, Technische Universität München gunther.friedl@wi.tu-muenchen.de Professor Karl Ennsfellner, IMC University of Applied Sciences, Krems karl.ennsfellner@�h-krems.ac.at Professor Gyorgy Komaromi, International Business School, Budapest gyorgy@komaromi.net Professor Vasile Dinu, University of Economic Studies, Bucharest dinu_cbz@yahoo.com Professor Ada Mirela Tomescu, University of Oradea, Oradea ada.mirela.tomescu@gmail.com Professor Radojko Lukić, University of Belgrade rlukic@ekof.bg.ac.rs Professor Alexandar Angelus, Lincoln University angelus@lincolnuca.edu Professor Krunoslav Čačić, Singidunum University kcacic@singidunum.ac.rs Professor Verka Jovanović, Singidunum University vjovanovic@singidunum.ac.rs Professor Milan Milosavljević, Singidunum University mmilosavljevic@singidunum.ac.rs Professor Olivera Nikolić, Singidunum University onikolic@singidunum.ac.rs Professor Budimir Stakić, Singidunum University bstakic@singidunum.ac.rs Professor Mladen Veinović, Singidunum University mveinovic@singidunum.a.crs Professor Jovan Popesku, Singidunum University jpopesku@singidunum.ac.rs Professor Zoran Jeremić, Singidunum University zjeremic@singidunum.ac.rs Associate Professor Christine Juen, Austrian Agency for International christine.juen@oead.at Mobility and Cooperation in Education, Science and Research, Wien Associate Professor Anders Steene, Södertörn University, Stockholm/Hudinge anders.steene@sh.se Associate Professor Ing. Miriam Jankalová, University of Žilina miriam.jankalova@fpedas.uniza.sk Associate Professor Bálint Molnár, Corvinus University of Budapest molnarba@inf.elte.hu Associate Professor Vesna Spasić, Singidunum University vspasic@singiduunm.ac.rs Associate Professor Goranka Knežević, Singidunum University gknezevic@singidunum.ac.rs Associate Professor Michael Bukohwo Esiefarienrhe, University of Agriculture, esiefabukohwo@gmail.com Dept. of Maths/Statistics, Markurdi Associate Professor Nemanja Stanišić, Singidunum University nstanisic@singidunum.ac.rs Assistant Professor Patrick Ulrich, University of Bamberg patrick.ulrich@uni-bamberg.de Assistant Professor Konstadinos Kutsikos, University of the Aegean, Chios kutsikos@aegean.gr Assistant Professor Theodoros Stavrinoudis, University of the Aegean, Chios tsta@aegean.gr Assistant Professor Marcin Staniewski, University of Finance and Management, Warsaw staniewski@vizja.pl Assistant Professor Gresi Sanje, İstanbul Bilgi Üniversitesi, Istanbul gresi.sanje@bilgi.edu.tr Dr. Aleksandar Lebl, Research and Development Institute for Telecommunications and Electronics, Belgrade lebl@iritel.com E�� O��

Editor-in-Chief: Deputy Editor: Managing Editor: Production Editor: Prepress: Novak Njeguš

Professor Milovan Stanišić, Singidunum University Professor Verka Jovanović, Singidunum University Assistant Professor Svetlana Stanišić Stojić, Singidunum University Assistant Professor Gordana Dobrijević, Singidunum University Design: Aleksandar Mihajlović

ISSN: 2217-8090 Singidunum Journal of Applied Sciences is published biannually. Contact us: Singidunum Journal of Applied Sciences 32 Danijelova Street, 11010 Belgrade, Serbia Phone No. +381 11 3093236, +381 11 3093219, Fax. +381 11 3093294 E-mail: journal@singidunum.ac.rs Web: www.journal.singidunum.ac.rs Printed by: Mladost Grup, Loznica

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CONTENTS

1-4

Guest editor's introduction The challenges students are facing in the 21st century Dejan Popović

5 - 15

Property prices and regional labor markets in Poland Krzysztof Drachal

16 - 24

Monetary and foreign currency policy of the European Central Bank Vladimir Mladenović, Мiroljub Hadžić

25 - 33

Job satisfaction of men and women employed in manufacturing sector and education in Serbia Jelena Vukonjanski, Edit Terek, Bojana Gligorović

34 - 42

The importance of marketing innovation in new economy Dejan Ilić, Slavica Ostojić, Nemanja Damnjanović

III

43 - 52

The effect of gender on negotiation behaviour Gordana Dobrijević

53 - 66

Duration and convexity of bonds Slobodan Čerović, Marina Pepić, Stanislav Čerović, Nevena Čerović

67 - 73

Standardization and classi�ication of events in tourism based on a systems approach Aleksandra Golob, Tadeja Jere Jakulin

74 - 83

Options, Greeks, and risk management Jelena Paunović

84 - 89

Instructions for authors

SJAS 2014, 11 (1): 1-4 ISSN 2217-8090 DOI: 10.5937/sjas11-5973

GUEST EDITOR'S INTRODUCTION

THE CHALLENGES STUDENTS ARE FACING IN THE 21ST CENTURY Dejan Popović1 University of Belgrade, Faculty of Law Blvd. Kralja Aleksandara 67, Belgrade, Serbia

Professor Dejan Popović, PhD addressing the students and professors of Singidunum University on the occasion of 4 April, Belgrade University Students Day

Dear colleagues and students of Singidunum University, I have been working at Belgrade University for forty years. I was an assistant professor when Professor Slobodan Unkovic held the vice dean post, and an associate professor when he became remarkably successful rector of the oldest Serbian university. My university career developed side by side with the career of your rector Professor Milovan Stanišić, who used to be the professor of the Faculty of Economics at that time. Professor Stanišić, along with Professor Unković and a number of other colleagues, undertook a great challenge of establishing a new university - Singidunum University. Responding to the will of professors and students, I was elected Rector of Belgrade University in 2004. At that time we prepared the Law on Higher Education, which introduced Serbia into the Bologna study system and enabled us to become part of the European academic society. We have joined our efforts to create new institutions – one of them was “Conference of the Universities of Serbia“ (KONUS) within which the representatives of Belgrade and Singidunum University have always teamed in order to successfully defend academic values. The career path I pursued took me to the United Kingdom where I held the ambassador post for five years, but right after the expiration of my mandate I returned to the Faculty of Law. Today, I am quite honoured and pleased to be invited by my friends and very renowned colleagues, to visit Singidunum University again – and I am specially honoured for being provided with such an opportunity to address you, my dear colleagues. My aim is to briefly represent my viewpoint of student’s role in today’s world and the challenges, both the students and the universities are facing. 1

SJAS 2014  11 (1)  1-4

Popović D.  The challenges students are facing in the 21st century

The students have always played an important role in Serbian society. In the 19th century, “Licej” (lyceum, the first institution of higher education in Serbia) and the Belgrade Higher School generated numerous state officials, industrials, diplomats and scientists who gave huge contribution to modernizing Serbia and by the beginning of the 20th century succeeded in making Serbia a proud, democratic country – a member of the thus existent Union of the European Nations. Belgrade University was a hub of anti-fascism fighters between the two world wars; thousands of its students died fighting for the liberation of Yugoslavia. In the post-war period, the students formed the heart of the urban population, making SFRY a respectable state worldwide. They represented the barrier that prevented or at least tried to stop the authoritative tendencies towards which the ruling powers in Yugoslavia, and after its disintegration, in Serbia as well, strived – back in 1968, 1992, 1996/97 and most recently in 2000. Having spent almost entire working life with the students, I think I am right when I am pointing out the importance of the role of the young and educated – even when depolitization is taking place and when the majority shares the belief that the things are finally settling into their place. The experience is telling us that tough periods are reoccurring but also that the voice of changes always wins. According to the census from 2012, the number of university degree holders in the population older than 15 years was 10.6% which represents a slight but insufficient growth if we compare this figure with the percentage from the 1990s, when university degree holders constituted only 6.5% of the total population. If we put it into precise numbers, only 652,234 citizens acquired higher education. In Finland, for example, there is 39.3% of university degree holders, in the UK 39.4%, in the USA 42.5%, in Israel and Japan 46.4% , in Canada 51.3%, and in Russia 53.5%. You will notice that some of the highly developed countries, such as Germany, are not at the top of the list, but their prosperity is also provided by numerous vocational high schools, which we unfortunately do not have. Although unemployment rates in Serbia are huge (up to 50% in the young population), the chances to get a job are a little bit higher for those who hold a university degree than for those who only have secondary education. The data that 34.4% of Serbian population above the age of 15 has only primary education is very painful. According to 2012 census, there were 2,121,400 of citizens who had only primary school. This is the best, or more precisely I would say the worst, indicator of the negligence of our society. Under such circumstances, it is quite understandable that the number of students enrolling in the first year of bachelor studies is 50,000 on the annual basis, despite the financial difficulties the parents and secondary school graduates are facing. In 2013/14 school year, out of 53,564 first-year students, 83.9% enrolled in the state universities and higher schools, whereas 16.1% opted for the private ones. The data for the previous five years are similar, which indicates relative stability of this structure. However, most of us, professors at both state and private universities, are aware of how rapidly the world around us is changing. Comparative researches show that many state-run institutions of higher education had to reorganize at the beginning of the 20th century, so as to adjust to the requirements of the new industrial era. It was at the beginning of the 20th century, back in 1905, when the Belgrade Higher School had been raised to the level of University. Industrial revolution set its own quality requirements expected from the ones to be employed: efficiency, uniformity, standardization – all compliant with Taylor’s view of the industrial division of labour, which demanded specialisation and routine. Business operation of the industrial era was led by hierarchy, and the task of universities was to instil the students with knowledge about hierarchy and vertical system of governance that depended on specialisation, expertize and correct metrics which was dictated by the industrial division of labour. All these, when collected, should have ensured success. 2

SJAS 2014  11 (1)  1-4

Popović D.  The challenges students are facing in the 21st century

Today, at the beginning of the 21st century, we need a new revolution, that would modernize universities and prepare the graduates for a different work environment. The research conducted among the employers indicates that even in the most developed countries, the universities no longer equip the students to respond to the new, changed requirements the contemporary jobs are placing. In developed countries, it is estimated that a student who acquires a university degree nowadays will change his career 4 to 6 times. So what the universities are doing is the following – they are preparing the students for the career path that is going to be linear, final, specialized and predictable. It turns out that students are prepared to be the experts in the fields that are going to become obsolete. As I previously said, I spent five years in the United Kingdom, the country which represents the educational super force. Among 10 best-ranked world universities, apart from eight American, there are two British universities – Cambridge and Oxford. There are several UK universities in the list of 30 highest-ranked: UCL is 21st on the list and Imperial College is 24th. The remaining universities from the list are all American; there is only one from Switzerland, two from Japan and one from Canada. However, the investigations conducted in Britain claim that their students have excellent marks on the exams, but lack certain knowledge and skills necessary for the 21st century jobs: understanding human diversity in global context, skills in communication, cooperation, analytical judging, networking, ability to synthesize information based on a wide spectrum of facts. I would add one more thing here – in Britain, but to the greater extent in underdeveloped countries such as Serbia, many graduates do not know how to prepare their curriculum vitae or how to present their personal traits or talents at job interviews. The Internet significantly changed the job structure in the 21st century, just in the same way as it was done by the conveyor belt in the factories at the beginning of the 20th century. Today, global life does not have vertical hierarchy, but turns into a horizontal plane. Certainly, that does not mean that everybody is equal, but it does mean that the standardization brought by the industrial revolution is slowly disappearing under the flows of information brought by the internet and the network. No manager can achieve control over how and when information flows. That also refers to the media, publishers, professors - information runs freely over the network. Such circumstances have an enormous influence on how we work and communicate, what kind of attitude we assume as citizens (please remember the twitter ban in Turkey or internet censorship in North Korea), the way how we are organized or disorganized. The old division of labour faces constant challenges. The universities of the 21st century should equip the students with the new skills mandatory for the information era – interpersonal, synthetizing, organization and communication skills. That is exactly the reason why study programs are becoming multidisciplinary, linking socio-humanistic and natural sciences, qualitative with quantitative studying, whereas post-graduation level combines research and professional master studies. Creation of good, modern syllabi requires deep theoretical knowledge and historic deliberation, joined with practical experience, managerial skills and new forms of collaborative online writing and presentation. Earning this modern degree does not automatically mean that all the problems will be solved, they won’t – but the graduates will be qualified to face the job crisis and flexibly respond to the emerging problems; they will be ready to switch to the new, today maybe non-existent jobs. Serbia is entering a decisive phase of its positioning as a state in the 21st century. Having commenced accession talks with the EU and its member states in 2014, Serbia has a chance

SJAS 2014  11 (1)  1-4

Popović D.  The challenges students are facing in the 21st century

to finalize these talks by the end of this decade and possibly, or even probably, become a full member of the European Union in the 2030s. The mere accession talks will change the conditions we live in: the candidate country is expected to implement acquis communitaire into its legal system and to adjust the functioning of society and make it compliant with the EU. Serbia is facing a serious task – not only to dramatically increase the portion of the higher educated – as with one third of the population having completed only primary school it is doomed to experience failure in any field – but to adjust the knowledge and skills gained on tertiary education with the radically changed world into which we are embarking. Your professors are fully aware of this fact; and that is why your study plans and programs – as contemporary world would say, or curricula and syllabi as the Romans would put it – are changing and constantly adjusting to the new challenges. In the world of scientific revolution, many jobs for which you will apply upon graduation do not exist at this moment. That is why you have to accept the concept of life-long learning. Just imagine all the possibilities that will open for you by the free movement of labour force in the huge EU market. However that freedom bears its risk: a highly qualified person from some other member state may wish to get a job exactly in Serbia. Competition brings challenges, but doubtlessly raises quality and offers quite a distinct perspective from the one, I would say pretty sombre, we are surrounded by now.

SJAS 2014, 11 (1): 5-15 ISSN 2217-8090 UDK: 339.13:332.2(438); 347.215(438) DOI: 10.5937/sjas11-4650 Original paper/Originalni naučni rad

PROPERTY PRICES AND REGIONAL LABOR MARKETS IN POLAND Krzysztof Drachal1,* Warsaw University of Technology, Faculty of Mathematics and Information Science, Koszykowa 75, 00-662 Warszawa, Poland

Abstract: The purpose of this research is the construction and analysis of a macroeconomic model of property prices in Poland covering the period between 2006 and 2013. The model is based on a supply-demand approach. Property prices have been found to be significantly affected by wages (positive correlation), unemployment rate (negative correlation), construction costs (positive correlation) and size of population (positive correlation). The panel data were collected from the biggest cities in voivodeships (Polish administrative regions). Both models with fixed and random effects were analyzed. Some similarities with a developed (UK) market have been found as well.

INTRODUCTION House prices in Poland increased significantly in the period between 2002 and 2008. They increased almost 3 times in some districts. Average transaction value increased approximately 2.43 times. Only in one year period, 2005 – 2006, the prices increased by 72%-82% in the fastest developing cities (Florczak, 2008; Wąsewicz, 2010). Since then, a slow fall in the property prices has been observed. In some cities it was quite strong (ca. 24%), but in the whole country, on average, it has been more stable, i.e. approximately 8% between 2008 and 2013 (NBP, 2013). However, the Polish property market is young and still emerging. It is not as developed as Western property markets are. Not only does it lack some sophisticated instruments (for example, reverse mortgage which is still under legal discussion), but it also lacks credit boom. For example, in 2010, the value of a mortgage of an average household was only 5.5 of an average monthly salary. It is one of the lowest ratios in Europe (Drachal, 2011b; HYPO, 2010). * E-mail: k.drachal@mini.pw.edu.pl

Key words: property market, house prices, regional labor market, unemployment.

Moreover, official statistics (provided by the central bank) on house prices have been published recently (NBP, 2013). A lot of research has been done relying on the researchers’ own data sources or on the data collected directly from developers (who do not publish their data in an easily accessible way). Therefore, the research has relied on different data sources. Moreover, there is a serious lack of econometric models for the Polish property market. Many articles are available only in Polish and they usually conclude that house prices have risen due to some social (or speculative) factors. For example, Zelazowski (2011) constructed linear regression models for voivodeships and found that significant house price determinants are GDP per capita and population size whereas unemployment and construction costs are not that influential. Unemployment was also found not to be significant for linear regression models constructed by Drachal (2011a). Unfortunately, there has not been much research on econometric models including both property and labor markets in Poland. 5

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Drachal K.  Property prices and regional labor markets in Poland

In Poland, the ratio of the people holding a university degree amongst the total labor force has a continuously rising trend. At the beginning of 2006, there were 14.6% of university degree holders whereas currently they constitute 22.1% of the total labour force. Those holding only a high school diploma (so-called “matura” exam) maintain a stable level of ca. 11%. A slight decline in the ratio of those who hold a vocational school diploma is observed. They made up 28.5% of the total labor force in 2006 and 26.3% at the beginning of 2013 (GUS, 2013). Such changes are related with the recently increased number of university degree holders in Poland who then expect to get a higher salary. Furthermore, there are plenty governmental actions focused on increasing the level of education in the Polish society. This concerns the projects which focus on the creation of innovative economy. Therefore, it may be expected that such an increase in educated labor force will drive house prices. On the other hand, having a diploma is no longer a guarantee for having a well paid and stable job. In addition, a lot of young people have decided to immigrate since EU accession. This fact has no correspondence in official statistics, because most of them are still registered in Poland although they work and live abroad and visit their relatives in Poland just a few times a year. The other important fact is that Polish regions (voivodeships) are highly differentiated on the basis of e.g. unemployment rate (the range in the beginning of 2013 was 11.6%), average wages, property prices, etc. Despite the actions connected with sustainable development and attempt to compensate for these differences, the richer regions become richer and poor regions become poorer, because people move and seek jobs in richer regions or (as mentioned above) abroad. (Please note the voivodeships correspond to NUTS-2 classification.) In view of the presented facts it seems interesting to take a closer look at the relations between the property prices and local labor markets in Poland. This paper is based on the recently published data in connection with the property market by the central bank of Poland (NBP, 2013). METHODS When a consumer makes a decision about buying a property it may be expected that not only the current wages, but also the perspective of future earnings are considered. Buying a property is usu6

ally financed by a long term bank credit. A consumer would prefer not only to have high wages at the moment of buying, but also to keep future wages at the level allowing him to regularly repay the debt. As a result, high unemployment may be perceived as an indicator of unstable future earnings or even as a risk of losing income which allows one to afford a property. Moreover, the increasing trend of unemployment may result in stricter credit policies, which would reduce the demand for housing space (Gathergood, 2011; Johnes and Hyclak, 1999). In this particular case (the study focused on big cities) unemployment rate is one of the direct indicators of place attractiveness. A residence in an area where one may find a good job is worth more, because, for example, transportation costs are lower and one does not have to spend so much time on traveling to work every day. One of the possible approaches towards modeling the property market is to consider supply and demand functions and to assume that the current property price is that of the partial equilibrium (Meen, 2001; Qingyu, 2010; Ashworth and Parker, 1997). One may also narrow to log-log models, i.e. the demand function is given by the equation: (1) ln(hD)=a1. ln(p)+ln(f(x1,...,xn)). On the other hand, the supply function is given by the equation: (2) ln(hS)=a2. ln(p)+ln(g(y1,...,ym)) . In the above equations a1, a2 are some coefficients, f and g are some functions, x1,...,xn are demand variables, y1,...,ym are supply variables, h is available housing space and p is property price. Assuming the equilibrium state (i.e. hD=hS) and assuming particular properties for functions f and g, a combination of (1) and (2) produces the following equation: (3) ln(pt) = b0+b1. ln(x1,t)+...+bn. ln(xn,t)+bn+1. . ln(y1,t)+...+bn+m. ln(ym,t). In the above equation b0, b1, ..., bn+m are some coefficients and t indicates time period. The wages and their first lags (first differences), new available housing space, population size, unemployment rate, ratio of high skilled workers in total labor force, size of the total labor force, construction costs and mortgage rate were chosen as potentially significant factors determining demand and supply. Such a choice is consistent with the research mentioned previously and with the stated hypotheses about Polish property market.

SJAS 2014  11 (1)  5-15

Property prices, wages, new housing space and ratio of skilled workers have log-normal distribution assuming 5% significance level. Nevertheless, log-log models are useful if distribution is long right tailed (as - roughly speaking - it is in the considered case). They also work well when operations are rather multiplicative than additive. At least log-log models are often used in estimating demand functions, when constant elasticity is desired (Hill et al., 2011). For example, a similar model was used by Qingyu (2010) in case of the UK property market. Therefore, it would be also useful to compare the results between the UK and Poland obtained from similar models in the further part of this paper. Quarterly data covering the period starting in the third quarter of 2006 and ending in the first quarter of 2013 were taken. The data for 16 biggest cities were collected, one city from each Polish voivodeship. The obtained panel is balanced. The official statistics from the National Statistics Bureau and central bank were used (GUS, 2013; NBP, 2013). Unfortunately, there is no reliable data source containing the property prices in Poland which would cover the period before 2006. All data, except construction costs (in PLN) and mortgage rates (in %), were collected only for particular cities (not for the whole regions these cities represent). It is reasonable to assume that they are the same for all voivodeships. Wages (in PLN) were measured as an average monthly wage. It has to be mentioned that wages in Poland are highly differentiated. This may influence the usability of an average wage as a ratio. However, it is the best indicator of consumer wealth, if one does not want to divide consumers into more specific groups. New available housing space was measured in square meters, this concerns the housing buildings finished in the considered quarter. Population size (of the cities) was measured by the number of people who are permanently registered to live there. This number may not correspond to reality, because big cities in voivodeships usually provide jobs for people who are officially registered in other voivodeships. However, if one buys a house or flat, he or she must be registered to live in such a house or flat. On the other hand, if someone buys a few flats and rents them to people who are officially registered somewhere else then in such a case there is no correspondence in the official statistics. This fact may be potentially an important bias in case of e.g. Warsaw (the capital city). Unfortunately, more thorough data about the mentioned case would require another specific

Drachal K.  Property prices and regional labor markets in Poland

research. Adding a variable corresponding to the number of workers to the model is one of the possible remedies. Unemployment rate is measured in percentages. Ratio of skilled workers is measured as a percentage of those people who hold a university diploma amongst the total labor force. Mortgage rates and housing prices were taken from the central bank statistics (NBP, 2013). All other data were taken from the National Statistics Bureau (GUS, 2013). Historically, the most important problem in any analysis of the Polish property market has been a complete lack of the official house price index. Research was based on different data sources originating from different providers. Sometimes even construction costs were misleadingly used. (It occurred in some non-Polish research, probably due to translational problems.) Fortunately, the central bank has published some data from its own sources recently. It can be perceived as a highly reliable source and detailed enough in order to proceed with the analysis. The analysis is based on transactional prices. Calculations are done with the help of GRETL package. CALCULATION AND RESULTS One possible model when working with panel data is that of fixed effects. In such a model it is assumed that the relationships between predictors and the outcome variable are characteristics of each voivodeship. Variables vary with time and these characteristics are assumed to be unique for particular voivodeships and constant with time. A random effects model is proper if one assumes that differences across voivodeships have some influence on explanatory variables. It seems reasonable that such a thing happens for the analyzed data. Moreover, results of a random effects model may be generalized for the whole population (in the considered case: big cities in Poland). On the other hand, the sample taken into the analysis (the biggest city from each voivodeship) is complete if the population is considered to be the biggest voivodeship cities. The sample is relatively small, if the population is understood as just these big Polish cities (without much precision what “big” means). Therefore, random model effect may be extrapolated on big Polish cities in general. But a question emerges - can the other big cities be classified in the same cluster as capitals of voivodeships? 7

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Drachal K.  Property prices and regional labor markets in Poland

model

const

ln(hspacet)

ln(unempt)

ln(costst)

ln(wagest-1)

6.661**

-0.01756**

-0.2506**

0.1044**

0.1903**

(0.2978)

(0.008474)

(0.01810)

(0.04226)

(0.06245)

4.081**

-0.2417**

0.09668**

0.2003**

0.1850**

(0.8025)

(0.01751)

(0.04189)

(0.06171)

(0.06020)

ln(psizet)

Adj. R2 0.9179

Table 1: Panel regressions estimations. Dependent variable: ln(pt) Standard errors in parentheses ** indicates signiﬁcance at the 5 percent level

Therefore, both models were evaluated. Table 1 presents the outcomes from panel regressions. It appears that only housing space (hspace), unemployment rate (unemp), construction costs (costs) and wages (wages) are significant for the fixed effects model. For a random effects model housing space is not significant, but population size (psize) is significant (contrary to fixed effects model). All signs of coefficients in both models are consistent with economics theory prediction. Moreover, coefficients for common significant variables in both models are almost the same numerically. (For detailed outcomes see Appendix 2.) Due to Hausman test the random effects model is preferred. Similar conclusion is taken from BreuschPagan test. But the problem may be that for a random effects model it is assumed that unobserved variables are uncorrelated with all observed variables. From econometric point of view more detailed tests would be more useful then. However, the presented analysis is a pioneering one for the current Polish market, so only the first outcomes are communicated here. The next problem is to estimate regressions for each voivodeship. This is to find out whether the house prices are more sensitive to unemployment rate in richer regions (i.e. characterized by higher average wages throughout the whole analyzed period). The outcomes of (robust, HAC) regression are presented in Table 2. (see Appendix 1. for the abbreviated names of voivodeships). The increase in unemployment rate results in the decrease in house prices in all regions. However, the differences in elasticity are high between voivodeships. For example, in the most developed region (MA), characterized by the highest average wages, house prices are sensitive to unemployment at the moderate level in comparison with other regions. It can be seen from Picture 1 that there are a 8

few groups of regions. The first one (including only MA) is characterized by high wages and moderate sensitivity to unemployment. The second group (including MP and DS) consists of regions with small sensitivity to unemployment and moderate average wages. These regions are the developed ones. For example, DS is attractive for large business. MP is not only business friendly, but also attractive for tourists. The third group (including only WM) consists of the region with small unemployment sensitivity and low average wages. This is the region with high unemployment rate, but very attractive for tourists. However, it lacks good road connections. The fourth group (including OP, WP and ZP) consists of regions with lower wages and it is moderately sensitive to unemployment. The fifth group (including PM and SL) consists of regions with higher average wages and there is a moderate unemployment sensitivity. These regions are the centers of large businesses. For example, SL is heavily urbanized (mostly because of heavy industry, mines, etc.). The sixth group (including PK, LB, PD, LD and KP) consists of regions characterized by lower wages and higher sensitivity to unemployment. The last group (including LU and SW) consists of regions with low wages and very high sensitivity to unemployment. These regions are not developed and there are more developed or more tourist attractive regions in their neighborhood. Summarizing, it cannot be stated that the house prices in poorer regions are the ones less sensitive to unemployment rate changes. The sensitivity to unemployment is rather connected with opportunities of each region and its potential to continue the existing development processes in the future. If a region has some characteristics which increase its long term opportunities for a potential investor (e.g. tourist attractiveness, concentration of heavy industry, headquarters of large companies, etc.) then, even if wages are high, house prices are not sensitive to unemployment

SJAS 2014  11 (1)  5-15

Drachal K.  Property prices and regional labor markets in Poland

voivodeship

const

ln(unempt)

ln(costst)

ln(wagest-1)

ln(psizet)

205.5**

-0.3810**

0.2599**

0.3288**

-15.96**

0.6466

(1.253e-05)

(2.284e-09)

(6.235e-09)

(2.852e-09)

(9.930e-07)

-7.547**

-0.4384**

0.3772**

0.1500**

0.9622**

(5.368e-09)

(8.952e-012)

(6.510e-013)

(3.085e-012)

(4.193e-010)

3.152**

-0.2393**

0.1852**

0.01607**

0.3211**

(1.605e-08)

(1.122e-011)

(9.184e-012)

(2.010e-011)

(1.251e-09)

-15.38**

-0.2934**

0.1634**

0.4076**

1.521**

(7.550e-09)

(3.910e-012)

(7.696e-012)

(3.615e-011)

(5.791e-010)

3.386**

-0.8966**

0.3296**

0.1559**

0.2491**

(5.963e-09)

(8.293e-012)

(3.534e-013)

(3.768e-011)

(4.618e-010)

-146.1**

-0.07894**

-0.1281**

-0.1843**

11.63**

(5.816e-06)

(1.603e-09)

(2.210e-09)

(6.291e-09)

(4.322e-07)

195.7**

-0.6237**

0.2390**

0.06433**

-14.76**

(7.608e-07)

(7.076e-011)

(1.788e-010)

(1.926e-09)

(5.826e-08)

-2.897**

-0.4307**

0.05962**

0.4718**

0.5793**

(1.593e-08)

(2.067e-011)

(1.506e-011)

(1.191e-010)

(1.096e-09)

1.558**

-0.2086**

0.1155**

0.09816**

0.4548**

(5.338e-08)

(3.295e-011)

(6.882e-011)

(4.960e-011)

(4.429e-09)

45.43**

-0.2681**

-0.09801**

0.02086**

-3.076**

(6.209e-09)

(1.507e-011)

(2.126e-012)

(6.952e-011)

(4.779e-010)

-172.1**

-0.2344**

-0.07544**

1.108**

13.05**

(1.433e-06)

(7.486e-011)

(1.510e-010)

(6.571e-09)

(1.042e-07)

-26.72**

-0.4258**

-0.2500**

0.04400**

3.116**

(4.157e-09)

(1.736e-011)

(1.447e-011)

(9.192e-011)

(4.176e-010)

-45.98**

-0.2753**

0.2022**

-0.06378**

4.161**

(2.978e-09)

(2.648e-012)

(8.647e-012)

(1.609e-011)

(2.264e-010)

159.4**

-0.2330**

-0.01948**

-0.1004**

-10.39**

(5.864e-07)

(1.737e-010)

(8.104e-010)

(1.502e-09)

(4.126e-08)

289.9**

-0.1147**

0.03252**

-0.5534**

-20.73**

(2.833e-05)

(2.128e-09)

(1.621e-08)

(1.375e-08)

(2.103e-06)

-49.99**

-0.3864**

-0.1812**

0.3265**

4.938**

(1.469e-08)

(2.466e-011)

(7.483e-012)

(3.851e-011)

(1.293e-09)

0.5722

0.5354

0.6040

0.7451

0.4931

0.8292

0.4260

0.4961

0.5371

0.5560

0.6100

0.7529

0.7120

0.3043

0.3922

Table 2: Regression estimates. Dependent variable: ln(pt) Standard errors in parentheses ** indicates signiﬁcance at the 5 percent level

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Drachal K.  Property prices and regional labor markets in Poland

Picture 1: Coeﬃcient of ln(unempt) vs. average wage.

changes more than the whole country on average. However, if there are fast developing, more attractive regions around or if a region is generally perceived as underdeveloped, then such a region is highly sensitive to unemployment rate changes. The average is taken from the whole period between the third quarter of 2006 and the first quarter of 2013. It has been found that unemployment rate and ratio of people holding a university diploma are not significantly correlated. However it may be easily observed that there is a significant positive correlation between property prices and level of average wages. Although it has been stated that sensitivity of prices to unemployment is not observed to be higher

in richer regions, it can be seen that unemployment rate is negatively correlated with prices. It is another argument in favor of hypothesis that one of the important determinants driving the property prices in big Polish cities is a low unemployment rate. Finally, notice that generally there is a negative “relationship” between mortgage rate and unemployment rate. However, Philips curve analogy is too simple. (Remember e.g. that unemployment varies through regions, but mortgage rate is the same for the whole country). On the other hand, the wage curve behaves normally. In other words, regions of high unemployment are characterized by low average wages and vice versa.

Picture 2: Property prices and average wages for each voivodeship between 2006 and 2013. 10

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Drachal K.  Property prices and regional labor markets in Poland

Picture 3: Property prices and unemployment rate for each voivodeship between 2006 and 2013.

Picture 4: Average wages and unemployment rate for each voivodeship between 2006 and 2013.

DISCUSSION AND CONCLUSIONS Out of Central and Eastern European markets, the Polish real estate market is the one most correlated with the UK market (Kucharska-Stasiak, Matysiak, 2004). Furthermore, it is the fastest developing economy in the European Union and the Polish property market is the most active one out of other Central and Eastern European markets (PWC, 2013). On the other hand, the UK property market is more developed and bigger. Moreover, in Poland only 8.4% of the population lives in their own prop-

erty burdened with a mortgage or loan, whereas in the UK it is 41.9%. In Poland 73.7% of the population lives in their own property with no outstanding mortgage or housing loan, whereas in the UK it is only 26% (EUROSTAT, 2013). But transparency of Polish real estate market is comparable with Western developed markets. Some investors perceive the Polish market even as the “core” one. The UK market transparency gained 1.33 composite score and is therefore the second most transparent market in the world (and therefore the first one amongst European countries, too). Poland gained 2.11 composite 11

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Drachal K.  Property prices and regional labor markets in Poland

scores and is on the 19th place in the world, according to Jones Lang LaSalle report (2012). Therefore, it is interesting to compare the results of the current research for Poland with the similar surveys for the UK. For example, it is interesting that for a similar logarithmic model almost the same value of R-squared coefficient has been found on the UK market when the fixed effects model was analyzed (Qingyu, 2010). However, in case of Poland only the first lag of wages is significant, whereas for the UK current wages have also been found significant. Moreover, on the UK market, it has been observed that interest rates have a significant influence on house prices. A very astonishing fact is that the average sensitivity of unemployment rate is almost the same in Poland and in the UK. Moreover, similar numerical values of regional sensitivity have been found in Poland and the UK for different regions (similar ranges). In both Poland and the UK very small and very high values of this sensitivity have been found. On the contrary, Qingyu (2010) has found results from the UK inconclusive to determine whether poorer regions are more sensitive to unemployment rate changes. On the other hand, Meen (2001) concluded that such correlation exists indeed. Also Clapp and Giacotto (1994) found such relationship important in the US and Vermeulen (2008) in some Western European cities. In the final random effects model, a mortgage rate has not been included. However, regression models for each voivodeship allow inserting a mortgage rate into models for most cities (except for just a few ones). However, after that R-squared of models has not been much greater than the original ones (presented in Table 2). In addition, coefficients for other variables do not change significantly after including a mortgage rate, therefore, omitting this variable does not generate much bias. In fact, it may occur that the real impact of interest rate is “included” in wages. Consumers may perceive interest costs not by direct evaluation but by perception of their wealth just through wages. In Poland it has been found that house prices are significantly more sensitive to unemployment than on average only in two highly underdeveloped and poor regions (out of sixteen analyzed regions). It is worth mentioning that there are also a few relatively rich regions, where changes in unemployment have only a slight influence on house prices. It seems that in Poland there are regional characteristics that influence house prices, not simply the current unemployment rate level. 12

Regression models for each voivodeships have much smaller R-squared than similar ones for the UK. It is consistent with the previous research (unfortunately available only in Polish) concluding that it is hard to model house prices solely on the basis of macroeconomic indicators. However, the obtained R-squared seems satisfactory for many regions, confirming that the model proposed in this paper is usable. At first, it was expected that an increasing rate of the people who hold university diplomas would play significant role in house price increase. Such expectations were justified as they relied on the research from other countries, e.g. Glaeser and Saiz (2003) or Andrews and Sanchez (2011). However, this has not been confirmed by the conducted analysis. Maybe some other models will say more about the relationship between the house prices and education in Poland. It has thus far remained an open question. If one assumes that differences between voivodeships change with time, then it is reasonable to stick to a random effects model. It may be stated further (but still as a hypothesis open for future research) that the house price dynamics in the biggest cities is a consequence of continuous adaptation of labor force. In other words, current social-economical processes lead to a situation in which more and more people work (and therefore live) in big cities. Small cities are becoming less attractive, because they offer fewer opportunities in comparison with large city agglomerations. Regional labor markets polarization has been observed in Europe e.g. by Puga and Overman (2002). What drives the house prices in big cities may not only be the current macroeconomic situation, but also the possibility to gain profits in the future. Profits from having closer distance to good schools for children, well equipped medical centers, possibility to rent rooms for students or workers, etc. If the number of workers who hold a university diploma increases, then employers will consequently increase their recruitment requirements, especially in big cities. Therefore (in further research) it would be interesting to consider some other models including, for example, the time needed to find a job, the time spent on traveling to work, access to medical centers, training centers, schools and universities, number of theaters, cinemas, community centers, and other factors connected with the standard of living and its changes in the selected cities.

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REFERENCES Andrews, D., & Sanchez, A.C. (2011). Drivers of homeownership rates in selected OECD countries. doi: 10.1787/5kgg9mcwc7jf-en. Ashworth, J., & Parker, S.C. (1997). Modelling regional house prices in the UK. Scottish Journal of Political Economy, 44(3), 225-246. doi: 10.1111/14679485.00055. Clapp, J.M., & Giacotto, C. (1994). The influence of economic variables on house price dynamics. Journal of Urban Economics, 36(2), 161-183. doi: 10.1006/ juec.1994.1031. Drachal, K. (2011a). Analiza determinant cen nieruchomości w Polsce. Świat Nieruchomości, 75, 30-33. (in Polish). Drachal, K. (2011b). Perspektywa polskiego rynku nieruchomości. Świat Nieruchomości, 78, 10-15. (in Polish). EUROSTAT. (2013). Housing statistics. Retrieved August 1, 2013, from http://epp.eurostat.ec.europa.eu/ statistics_explained/index.php/Housing_statistics. Florczak, K. (2008). Ceny na polskim rynku nieruchomości mieszkaniowych. Studia i Materiały Towarzystwa Naukowego Nieruchomości, 16(2), 33-44. (in Polish). Gathergood, J. (2011). Unemployment risk, house price risk and the transition into homeownership in the United Kingdom. Journal of Housing Economics, 20(3), 200-209. doi: 10.1016/j.jhe.2011.03.001. Glaeser, E.L., & Saiz, A. (2003). The rise of the skilled city. Retrieved August 20, 2013, from http://www.philadelphiafed.org/research-and-data/publications/working-papers/2004/wp04-2.pdf. GUS. (2013). Statistical yearbook of the Republic of Poland 2013. Retrieved August 21, 2013, from http:// www.stat.gov.pl/cps/rde/xbcr/gus/RS_rocznik_statystyczny_rp_2013.pdf. Hill, R.C., Griffiths, W.E., & Lim, G.C. (2011). Principles of econometrics. New York: Wiley. HYPO. (2010). Hypostat 2010: A review of Europe’s mortgage and housing markets. Retrieved September 2, 2013, from http://www.hypo.org/Content/default.asp?pageId=578.

Drachal K.  Property prices and regional labor markets in Poland

Johnes, G., & Hyclak, T. (1999). House prices and regional labor markets. The Annals of Regional Sciences, 33(1), 33-49. doi: 10.1007/s001680050091. Jones Lang LaSalle. (2012). Real estate transparency index. Retrieved November 4, 2013, from www.lasalle. com/Research/ResearchPublications/TransparencyIndex_2012.pdf. Kucharska-Stasiak, E., & Matysiak, G. (2004). The transition of the Polish real estate market within a Central and Eastern European context. Retrieved September 12, 2013, from http://www.reading.ac.uk/LM/LM/ fulltxt/1604.pdf. Meen, G. (2001). The time-series behavior of house prices: A transatlantic divide? Journal of Housing Economics, 11(1), 1-23. doi: 10.1006/jhec.2001.0307. NBP. (2013). Ceny ofertowe. Retrieved September 12, 2013, from http://www.nbp.pl/publikacje/rynek_nieruchomosci/ceny_mieszkan.xls. (in Polish). Puga, D., & Overman, H.G. (2002). Unemployment clusters across Europe’s regions and countries. Economic Policy, 17(34), 115-147. doi: 10.1111/1468-0327.00085. PWC. (2013). Emerging trends in real estate. Survey of PwC and Urban Land Institute. Retrieved November 4, 2013, from http://www.uli.org/wp-content/uploads/ ULI-Documents/Emerging-Trends-Europe-2013.pdf. Qingyu, Z. (2010). Regional unemployment and house price determination. MPRA Paper No. 41785. Retrieved September 2, 2013, from http://mpra.ub.uni-muenchen.de/41785/. Vermeulen, W. (2008). Essays on housing supply, land use regulation and regional labour markets. [Amsterdam]: Thela Thesis. Wąsewicz, M. (2010). Rynek nieruchomości mieszkaniowych i jego finansowanie. Annales Universitatis Mariae Curie-Sklodowska, 44, 553-566. (in Polish). Żelazowski, K. (2011). Regionalne zróżnicowanie cen i ich determinant na rynku mieszkaniowym w Polsce. Studia i Materiały Towarzystwa Naukowego Nieruchomości, 19(3), 98-106. (in Polish).

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Drachal K.  Property prices and regional labor markets in Poland

APPENDIX 1

Abbreviations of voivodeships: DS - Lower Silesian, KP - Kuyavian-Pomeranian, LB - Lubusz, LD - Lodz, LU - Lublin, MA - Masovian, MP - Lesser Poland, OP - Opole, PD - Podlaskie, PK - Subcarpathian, PM - Pomeranian, SL - Sielsian, SW - Swietokrzyskie, WM - Warmian-Masurian, WP - Greater Poland, ZP - West Pomeranian. APPENDIX 2 FE:Fixed-effects, using 416 observations Included 16 cross-sectional units Time-series length = 26 Dependent variable: ln_p

const ln_hspace ln_unemp ln_costs ln_wages_1 Mean dependent var Sum squared resid R-squared F(19, 396) Log-likelihood Schwarz criterion rho

Coeﬃcient 6.66134 -0.0175582 -0.250556 0.104383 0.190334 8.409087 2.303636 0.921628 245.0973 490.5304 -860.4472 0.507505

Std. Error 0.297761 0.00847371 0.0181032 0.0422579 0.0624463

S.D. dependent var S.E. of regression Adjusted R-squared P-value(F) Akaike criterion Hannan-Quinn Durbin-Watson

Test for differing group intercepts Null hypothesis: The groups have a common intercept Test statistic: F(15, 396) = 85.7876 with p-value = P(F(15, 396) > 85.7876) = 3.50401e-114 14

t-ratio 22.3714 -2.0721 -13.8404 2.4701 3.0480

p-value <0.00001 0.03890 <0.00001 0.01393 0.00246

*** ** *** ** ***

0.266136 0.076271 0.917868 1.9e-205 -941.0609 -909.1864 0.667184

SJAS 2014  11 (1)  5-15

RE:Random-effects (GLS), using 416 observations Included 16 cross-sectional units Time-series length = 26 Dependent variable: ln_p

const l_households l_unemp l_costs l_wages_1 Mean dependent var Sum squared resid Log-likelihood Schwarz criterion

Coeﬃcient 4.08112 0.185023 -0.241658 0.0966763 0.200324

Drachal K.  Property prices and regional labor markets in Poland

Std. Error 0.802456 0.0601992 0.0175068 0.0418942 0.0617083

8.409087 11.75969 151.4511 -272.7488

t-ratio 5.0858 3.0735 -13.8036 2.3076 3.2463

S.D. dependent var S.E. of regression Akaike criterion Hannan-Quinn

p-value <0.00001 0.00226 <0.00001 0.02152 0.00126

*** *** *** ** ***

0.266136 0.168947 -292.9023 -284.9337

‘Within’ variance = 0.00587845 ‘Between’ variance = 0.0291888 theta used for quasi-demeaning = 0.911989 Breusch-Pagan test Null hypothesis: Variance of the unit-specific error = 0 Asymptotic test statistic: Chi-square(1) = 3202.49 with p-value = 0 Hausman test Null hypothesis: GLS estimates are consistent Asymptotic test statistic: Chi-square(4) = 0.487165 with p-value = 0.974738

CENE NEKRETNINA I REGIONALNA TRŽIŠTA RADA U POLJSKOJ Rezime: Cilj ovog istraživanja je izrada i analiza makroekonomskog modela cena nekretnina u Poljskoj u periodu između 2006. i 2013. godine. Model je zasnovan na pristupu ponuda - potražnja. Konstatovano je da na cene nekretnina značajno utiču plate (pozitivna korelacija), stopa nezaposlenosti (negativna korelacija), troškovi izgradnje (pozitivna korelacija) i broj stanovništva (pozitivna korelacija). Podaci su prikupljeni iz najvećih gradova u vojvodinama (administrativnim regioni na koje je podeljena Poljska). Analizirana su oba modela sa fiksnim i slučajnim efektima. Konstatovane su takođe i neke sličnosti sa razvijenim tržištima (UK).

Ključne reči: tržište nekretnina, cene stambenih jedinica, regionalno tržište rada, nezaposlenost Received: October 10th, 2013. Correction: October 31st, 2013. Accepted: November 12th, 2013.

SJAS 2014, 11 (1): 16-24 ISSN 2217-8090 UDK: 338.23:336.74(4-672EU) DOI: 10.5937/sjas11-4902 Original paper/Originalni naučni rad

MONETARY AND FOREIGN CURRENCY POLICY OF THE EUROPEAN CENTRAL BANK Vladimir Mladenović1,*, Мiroljub Hadžić2 Business School of Applied Studies Blace, 70 Kralja Petra I, Blace, Serbia 2 Singidunum University, Department of Business 32 Danijelova Street, Belgrade, Serbia 1

Abstract: The paper analyzes how successful the ECB has been in pursuing its monetary and foreign exchange policy, which is, at the same time, a complex issue and crucial for the justification of its existence. Firstly, the ECB is trying hard to keep up with the global crisis and to maintain the stability of the euro. The main task of the ECB is to keep inflation below 2% p.a. This paper demonstrates that the ECB has managed to retain inflation within the required limits for a significant period of time, except for few relatively short-lived exceptions. By managing an adequate monetary policy the ECB has successfully accomplished its goals in the period of reference, as demonstrated by inflation trend results, monetary aggregate M3, and the level of interest rates.

EUROPEAN CENTRAL BANK AND ITS INDEPENDENCE The European Central Bank was established on June 1, 1998. Along with national central banks of 17 members of the European Monetary Union (Eurozone) and central banks of other EU members, it constituted the ESCB (European System of Central Banks). The main task of the ECB was to manage operations related to the introduction of a common currency – the euro, and to supervise the whole process. According to the Maastricht Agreement, the ESCB is the cornerstone of monetary power of EU, which defines monetary aggregates, monetary policy and implements monetary instruments. Some authors argued (Bernholz, 1999, p. 777) that the decision to leave national central banks within the ESCB could be linked to some aspects of the monetary policy management and the decentralization issue on one hand and, on the other hand, the reten16

* E-mail: v.mladenovic@vpsk.edu.rs

Key words: monetary policy, European Central Bank, inflation, interest rates, euro.

tion of present positions within the ESCB and the efficiency of such a monetary policy management. In the past, central banks were seen as institutions capable and responsible to fulfill several goals at the same time: providing the high rate of economic growth and employment, financing state budget and coping with balance of payment problems. In line with this, economic theory did not comment on the independence of central banks and credibility of their monetary policies. Today, the independence of central banks is higher than before and their primary goal is price stability (Cukierman, 2007, p. 368). The Independence of a central bank is understood as the existence of high level of freedom in the creation and realization of monetary policy. However, the independence of central bank is a rather wider concept: personal independence, financial independence and independence in monetary policy (independence in formulation of the goal and independence in monetary instruments introduction) (Barjaktarović, 2010, p. 167).

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Mladenović V., Hadžić M.  Monetary and foreign currency policy of the ECB

According to the Maastricht Convention, the ECB is in charge of maintaining stable prices, as well as preserving the stability of output and employment rates. In order to achieve these goals, the ECB built up a wall to protect itself from the interference of politics (Grauwe, 2005, p. 176). The independence of the ECB is closely related to its main goal – price stability. The concept of independence of the ECB consists of: institutional independence, legal independence, functional and operational independence, financial and organizational independence (Scheller, 2006, p. 124). The ECB only recognizes the aim of the monetary policy. This is laid down by the Maastricht Convention which, at the same time, empowers the ECB to pursue other goals, provided that they do not undermine price stability (Grauwe, 2005, p. 207). Price stability can be understood as the situation with neither inflation nor deflation in the long run (Gerdesmeier, 2011, p. 24). Price stability was firstly defined in 1998 by Supervisory board of the ECB as annual HICP (Harmonized Index of Consumer Prices) bellow 2%, in medium period. It was slightly changed in 2003 into: annual inflation rate under, but near to 2%, in medium term (European Central Bank, 2011, p. 65). MONETARY POLICY

The monetary policy and policy of public finances are the most important components of macroeconomic policy. Monetary policy’s function is to regulate the amount of money in circulation, maintain the balance between commodity stocks and monetary funds, enable smooth performance of commodity circulation, and ensure a stable economic course. Monetary-credit policy relies on certain categories – monetary indicators, which are used in the definition of the quality and the function of money in economy, as well as in management of the monetary policy and the solvency policy in economy and other sectors. These indicators actually constitute the basis for an efficient monetary policy, since they are used as the means for controlling its effects, in the first place its basic orientation and its adjustment to current economic trends. They are called monetary aggregates (Barać et al., 2007, p. 59). Monetary policy involves the mastering and conscious directing (i.e. control) of all forms and flows of money in reproduction (solvent, insolvent, foreign currency, and other funds). Credit policy in-

volves an active participation of the banking system in the regulation of credit volume and its structure in economy. Active influence on one of the main channels of the creation and withdrawal of money in circulation, as well as on credit volume involves detailed and carefully crafted actions through which a predominant portion of money in economy is determined. Therefore, the two concepts merge into one, namely the monetary-credit policy, since operations are not exclusively “monetary“ or “credit“, although there is a commonly held view that the current money is basically credit(deposit) money (Barać et al., 2007, p. 58). Central banks usually use three main monetary instruments: ◆ Open market operations – supply or withdrawal of state securities; ◆ Rate of refinancing – interest rate by which central banks are ready to finance commercial banks, within national economy, in the short run; ◆ Compulsory reserves – part of deposits collected within commercial banks, which has to be unused for credit lending (Mankiw and Taylor, 2011, p. 600). Strategy of ECB monetary policy is based on: ◆ Quantitative definition of the price stability (inflation rate below, but near to 2% annually, in the medium run) and ◆ Two anchor approach for the examination of price stability risk: ◆ Firstly, economic analysis of factors which determine prices in short and medium run and ◆ Secondly, monetary analysis of the relation between money supply and prices in long run (Gerdesmeier, 2011, p. 63). FOREIGN CURRENCY POLICY The system of economic relations with foreign markets, as an important part of the economic system, should provide conditions for a rational integration of the national economy into the international division of labor. This primarily means that systemic instruments will provide an objective assessment of cost-effective engagement of production factors in individual economic activities and, consequently, the identification of sectors in which a national economy makes the most of available resources (Jovanović Gavrilović, 2008, pp. 23-24). 17

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Mladenović V., Hadžić M.  Monetary and foreign currency policy of the ECB

The price at which one national currency is exchanged for another is called foreign currency rate. Foreign currency rate should be distinguished from foreign currency parity which represents an officially established value of the national money, expressed through a more widely accepted denominator, such as: gold, special drawing rights (SDR), a more stable and important national currency, etc. Under normal circumstances foreign currency rate is close to foreign currency parity as it constitutes its basis (Jovanović Gavrilović, 2008, pp. 23-24). EUROPEAN CENTRAL BANK AND THE GLOBAL ECONOMIC CRISIS

The global economic crisis, and the crisis of international financial markets, that occurred in the second half of 2007, raised numerous questions about the financial stability of the Eurozone. Despite the crisis, the financial system of the Eurozone remained relatively robust and resistant in 2007. Prior to the market crisis the financial system of the Eurozone had been in a good financial position, owing to strong profitability of the banking sector that lasted for a few years. Thus, the banking system was quite secure from risks. Enhanced profitability of large banks of the euro area in 2007 was largely driven by a strong increase in non-interest income. Besides, the degree of profitability was also related to a (low) degree of collection of bad debts. In the course of 2008, tensions and problems in the financial system of the Eurozone occurred, and gradually only deteriorated. As months went by, commercial banks of the euro were experiencing a decline in market capitalization, due to a fall in share price, a decrease in the loans volume, and an increase in credit expenses. As the uncertainty, caused by global economic developments, was mounting, aversion to risks, felt by the participants in the financial market, was growing. Credit market solvency deteriorated and the availability of funds fell during the year, while the activity of insurance markets slowed down. In such an environment, investors and creditors started to lose confidence into the ability of some financial companies to meet their obligations. Consequently, a lot of major financial companies encountered challenges, trying to access funds and capital markets. Some of the largest financial institutions experienced a decline in the price of their shares at the stock market. Due 18

to such a development, some international institutions were forced to ask for an additional support from the governments. However, bankruptcy was inevitable for some international financial institutions. Initially, commercial banks in the Eurozone faced the financial crisis from a generally stable financial position (which at the time did not cause any concern), owing to several years of positive (profitable) operations. Although some large banks were affected by depreciation that continued persistently for a year, they seemed to be resistant to unfavorable developments until the dramatic downturn in September 2008. In 2009, the ECB Council adopted supplementary non-standard measures, as it was facing dysfunctional money markets, despite relatively low ECB’s key interest rates and low interest rates on loans. It was also expected that support for the recovery would be given through the lowering of interest rates for households and businesses. These actions surpassed the outcome which could have been achieved through the reduction of the ECB key interest rates. This approach took into account the fact that, in the Eurozone, banks play the major role in providing financial resources for the real economy. As a result, the terms of financing improved substantially, and this reduced tensions on the money market. All the non-standard actions, adopted by the Council, were temporary and designed to maintain price stability for the time being, in a direct and an indirect way, while inflation expectations remained firmly anchored, owing to price stability. Monetary policy, implemented in 2010, led to the start of recovery of the euro area while, on the other hand, tensions on financial markets lingered. The Recovery of the real economy in 2010 appeared to be stronger than expected. Still, heightened financial tensions recurred in May. These events could be treated as a result of growing concern over the monetary sphere, given the (un)sustainability of the public finance policy (especially in Greece), since it produces adverse effects on other countries and economies, particularly on the government bonds market. In 2011, the European Central Bank continued to be a firm and reliable support, as confirmed by the fact that the expected mid- to long-term inflation was stable and close to 2% but still below this level. In 2011, a general rise in prices directly stemmed from higher prices of energy and assets, resulting in an immediate inflation rise.

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The set of measures, announced and adopted by the ECB Council and high representatives of member states of the Eurozone, referred to several key areas, their aim having been to restore the financial stability of the euro. Key elements of the new set of measures refer to new fiscal measures and more effective tools for stabilizing the Eurozone, including the more efficient financial stability, faster implementation of the Stabilization Program mechanism, and measures for tackling problems in Greece. In Greece, Ireland, and Portugal tensions on the government bonds market diminished but in the meantime spread to Italy and Spain and, subsequently, to other countries of the euro area. Such developments were also reflected in other issues, such as financial sustainability in certain countries of the Eurozone, concerns about global economic prospects, insecurity as to the financial support extended by the EU to member states of the euro area that were most vulnerable to the debt crisis, alongside the possibility of engaging the private sector in this area. According to the analysis of general economic and monetary trends for 2012, inflation remained at an acceptable level and in pace with the long-term goal. This is confirmed by the cross-analysis of signals coming from the monetary sphere. Additional economic policy measures and the progress of European reforms can help sustain the financial sentiment on the market and enhance the opportunities for economic growth. MAIN FEATURES OF THE ECB MONETARY AND FOREIGN CURRENCY POLICY IN THE PERIOD 2004-2012 The ECB instruments and their effects and results, monetary-credit features and foreign currency

policy for the period 2004-2012 have been analysed so as to reach valid conclusions with regard to the ECB economic policy measures. Monetary aggregate М3 The total solvency assets (М3) is a wider aggregate than М2 and it consists of: solvency assets (М2), reserve assets, assets for the payment of orders from abroad, assets for covering the letters of credit, other limited deposits, assets for the purchase of foreign currency, and joint assets.

Monetary dynamics (currency in circulation), within the European monetary union, in 2004, was under the influence of two opposed forces: on one hand, there were low interest rates and, on the other hand, the normalization of the contraction of debts and investment of citizens, stemming from their current situation, in the period from 2001 to mid-2003. A stronger monetary growth was perceived in 2005, owing to the stimulative effect of low interest rates within the Eurozone. At the same time, discouraging growth effects of М3 (as presented in Graph 1), related to stabilized investment activity of the Eurozone citizens, were losing its pace, especially in the first half of the year. In a nutshell, accelerated monetary growth in 2005 spurred further monetary growth in the euro area. In 2006, monetary growth continued, reaching, at the end of the year, the highest ever annual rate, since the beginning of EMU Phase 3. The Strong growth of М3 was largely a product of low levels of interest rates and more vigorous economic activity in the euro area, further propped up by a strong expansion of credits extended to the private sector.

Liabilities

Money in circulation

Overnight deposits

Deposits with agreed maturity of up to 2 years

Deposits redeemable at notice of up to 3 months

Repurchaseagreement

Money market funds shares/units

Debt securities issued with a maturity of up to 2 years

Table 1: Monetary aggregates deﬁnition in Eurozone Source: http://www.ecb.europa.eu/mopo/strategy/monan/html/index.en.html

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Graph 1: EU М3 trends in the period 2004-2012 Source: http://sdw.ecb.europa.eu/home.do?chart=t.1.2

The wide basis of the monetary trends analysis suggests that the growth of M3 to some extent can excessively increase the rate of monetary expansion. Strong M3 growth can be guided by the theoretical requirements of monetary values. A crucial turn of events, with regard to monetary trends, came with the global economic crisis in 2008 when it started, and especially at the beginning of 2009. Monetary expansion was moderate during 2008. The rough estimation of M3 components confirmed the existence of monetary growth, which was moderate at the time. Throughout the year, the growth of non-financial private sector loans slowed down, following the introduction of tighter borrowing requirements and a weaker economic activity. In 2009, the annual growth rate of М3 and loans to the private sector slipped into the negative zone. Economic recession, i.e. subdued production and trade, as well as uncertainty of business prospects, continued to push back companies’ demand for financial resources. To a certain extent, a lack of financial resources, extended by banks, also played an important role, as stated by analysts of bank loans in the euro zone. The growth of М3 was moderate in 2010, at an average rate of 0.6%. This serves to confirm the assessment that monetary expansion was moderate and inflation pressures around the mid-year limited. By that time, the monetary analysis used as the basis for the analysis and the assessment of money supply and credit growth, had been improved mark20

edly. This only reinforced the ECB’s mid-term monetary policy strategy. The ECB’s monetary policy took a new turn in 2011. Monetary expansion, from the years prior to the crisis, continued, the underlying objective having been to help economic activities recover and come out of the recession zone. After a relatively low growth of M3 of 1.7% in 2010, monetary expansion in the euro area gradually accelerated in the first three quarters of 2011, reaching 2.9% in September 2011 (as it can be seen in Figure 2). Still, financial market tensions and the pressure exerted on banks to adjust their annual balance sheets, particularly in the field of capital needs, undermined monetary dynamics in the autumn and slowed down the overall annual growth rate, reducing it to 1.5% in December. The profile of M3 growth in 2011 was under a strong impact of inter-banking transactions. Therefore, it can be concluded that monetary expansion throughout the year was moderate. The annual rate of M3 rose to 3.9% in October 2012, from 2.6% in September, while the growth of М1 sped up to 6.4%, from 5.0% a month earlier. These trends, partially down to a specific nature of the business, led to higher overnight deposits which belong to the non-monetary financial sector. Household and non-financial corporation deposits increased in October. To sum up, the period under consideration can be divided into three sub-periods that were characterized by different profiles of the monetary policy

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and the money supply, as measured by the monetary aggregate М3. During the period of escalation of the global economy crisis, 2008 inclusive, the monetary policy was moderately expansive. In the following period, 2010 inclusive, monetary restriction was introduced in order to suppress inflation pressures, with a subsequent revival of the monetary expansion whose aim was to lead to the overcoming of economic recession in the Eurozone. Inflation

One of the main tasks of the ECB is to keep inflation at the level of up to 2%. The ECB has striven to reach that goal by pursuing an adequate monetary policy, and thus alleviate the impact of the global economic crisis and maintain stability. The inflation rate in 2004 was, to a great extent, driven by an increase in administrative prices and indirect fees and, in the second half of the year in particular, a higher price of oil. Out of these reasons, the annual HICP (Harmonized Index of Consumer Prices) inflation in 2004 remained at the same level, compared to the level of 2.1%, of the year before (European Central Bank, 2005, p. 43). Long-term inflation expectations remained at a level similar to the one associated with price stability. Inflation in 2005 was slightly faster, mostly due to the rising trend of energy prices and, to a limited extent, the increase in administrative prices and in-

direct fees. The annual inflation was kept at an acceptable level of 2.2% in 2005. An average annual rate of price increase reached 2.2% in 2006, almost the same level as in 2005, which can be seen in Graph 2. The inflation rate was unstable throughout the year and it was mostly affected by changes in the price of oil. Annual inflation remained at 2.1% in 2007 as well. The inflation rate was quite unstable, just like the year before, due to the impact of energy prices. At the end of the year, the annual inflation went up sharply to much above 2%. The increase was largely caused by rising oil and food prices in the second half of 2007. In 2008, a relatively high inflation trend continued from the end of the previous year, due to large-scale effects of the crisis and the atmosphere of instability and strong inflationary expectations. An average annual inflation rate in 2008 rose to as much as 3.3%, considerably above the level the ECB had aspired to on a long-term basis; moreover, this was the highest level ever since the introduction of the euro. Under the influence of a restrictive ECB monetary policy, inflation pressures fell to 1.6% in December. In 2009, the annual inflation rate first dropped from 1.1% in January, to -0.7% in July, before it sped up again to 0.9% in December. Major factors, that caused oscillations to the general price increase, were the increase in production prices and in prices of energy resources.

Graph 2: EMU Inﬂation rate in the period 2004 - 2012 Source: http://sdw.ecb.europa.eu/home.do?chart=t.1.1

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Inflationary pressures lessened in the course of 2010, primarily owing to a shift in the monetary policy toward monetary restriction in 2009, which resulted in an average annual inflation rate of 1.6% only. In 2011, inflation was constantly at a higher level, on average at 2.7%, as an effect of a restored monetary expansion that was designed to help the real economy overcome recession. As for the monthly profile of annual inflation, it gradually rose from 2.3% in January, to the maximum of 3.0% in the period from September to November, dropping again to 2.7% in December. Mid-term and long-term expectations, as regards inflation, remained steadily at the targeted ECB levels. According to Eurostat data, annual inflation dropped to an acceptable level of 2.2% in November 2012. On the basis of current prices of oil futures, a further fall to below 2% is expected in 2013. By means of the policy relevant to the horizon, and under conditions of weak economic activity in the Eurozone, and well-anchored long-term inflationary expectations, price pressures will probably remain rather moderate. Interest rates The interest rate, set by the Governors Council, presents the minimal tender rate, beyond which the European Central Bank would not accept offers submitted by financial institutions (Grauwe, 2005, p. 318).

The ECB Council kept key interest rates unchanged during 2004, and that at historically low levels. The lowest offered rate of ECB major refinancing operations was kept at 2%, while the rates of deposit facilities and marginal facilities of lending remained at 1% and 3%, respectively. In 2006, the Council raised the key interest rates, in order to curb the risk of strong inflation pressures that had been detected. Monetary adjustment took place under conditions of economic growth and powerful money and credit expansion. In a series of expansion developments, the Council raised the minimal offered rate of major refinancing operations of the euro-system from 2.25% in January, to 3.50% by the end of 2006. The Council continued the adjustment of the monetary policy, by raising the key interest rates by 50 index points in March and June, and so the minimal offered rates were increased to 4.00% in June 2007. When the global economic crisis escalated, the Council started the monetary relaxation, by lowering the reference interest rates. Firstly, it reduced the rate of the major refinancing operation by 150 base points, to 1%, and that in four stages. In May, it decided to lower it to 1.75%, leaving the interest rate on deposit facilities at the same level, of 0.25. Considering the effects of monetary relaxation, the ECB Council came to a conclusion that the profile of interest rates policy should not be altered

Graph 3: EMU Interest rates on the money market in the period 2004 - 2011 (% p.a.) Source: http://sdw.ecb.europa.eu/servlet/quickviewChart?SERIES_KEY=143.FM.M.U2.EUR.RT.MM.EURIBOR1YD_.HSTA

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and, accordingly, left the key ECB interest rates at an unchanged, historically low level, reached in May 2009. The interest rate on major refinancing operations was at 1.00% during 2010, the rate on deposit facilities at 0.25%, and the rate on the marginal interest facility at 1.75%. In 2011, the interest rate policy was slightly modified. In order to secure and maintain stability, the ECB Council raised basic interest rates in April and July 2011, by 25 percentage points each time. CONCLUSION

The paper pointed out that independent position of a central bank is essentially important for a successful monetary policy. There are several important elements which ensure independency of the ECB to political influences, such as: institutional independence, legal independence, functional and operational independence, financial and organizational independence. Increasing interest in the (in)dependency of a central bank, in recent years, is the result of increasing interest in joining the Eurozone. At the same time, economic theory argued that there is a positive relationship between independent position of a central bank and price stability. The paper also found out that ECB monetary policy was successful, because the main aim of the policy and analytical tools were well defined. As it was pointed, the price stability was defined as inflation rate below, but near to 2% annually. Also, price stability risk was well assessed using both: economic analysis, in short and medium run, and monetary analysis in long run. The ECB’s task is to keep inflation under control, at the level of 2%. By managing an adequate monetary policy, the ЕCB has striven to reach its goal and thus reduce the impact of the world economic crisis and maintain stability. The proof that the task was successfully fulfilled, i.e. that inflation remained below 2%, is the fact that the ECB managed to keep inflation around 2%, for a long time. Aberrant situations, when inflation exceeded the 2% target, were relatively short (in 2008 inflation was at 3.3%, during 2009 somewhat higher). After these short-lived episodes inflation would go back to within the targeted range. Through regular monitoring of monetary aggregates, the ECB managed to track the situation, in terms of the required amount of the circulating money, and to timely decide on corrective measures of monetary regulation, for the largest part of the

analyzed period. During the period of the global economic crisis escalation (2008 inclusive), monetary policy was moderately expansive. What ensued in the next period (2010 inclusive), was monetary restriction, the main objective of which was the curbing of inflation pressures. In the period that followed, monetary expansion was revivified, for the purpose of overcoming the economic crisis in the Eurozone. An adequate policy of reference interest rates was an efficient lever of monetary regulation. The analysis of the monetary policy profile and its basic instruments, including interest rates, and the analysis of achieved results in the pursuit of the desired goal – price stability, confirm that inflation will be within the target of below 2%, if the reference interest rate is regulated at 2%. The dynamic analysis of the monetary policy, and results achieved during years of work, demonstrate that the ECB has led an adequate monetary policy, which resulted in a successful accomplishment of its objectives, for the most of the period analyzed, including the period of the economic crisis escalation. REFERENCES Barać, S., Stakić, B., Hadžić, M., & Ivaniš, M. (2007). Praktikum za bankarsko poslovanje. Beograd: Fakultet za finansijski menadžment i osiguranje. (in Serbian).

Barjaktarović, L. (2010). Monetarno - kreditni i devizni sistem. Beograd: Univerzitet Singidunum. (in Serbian). Bernholz, P. (1999). The Bundesbank and the process of European monetary integration. In: Fifty years of the Deutsche Mark: Central Bank and the currency in Germany since 1948. Oxford: Oxford University Press. Cukierman, A. (2007). Nezavisnost centralne banke i institucije monetarne politike: prošlost, sadašnjost i budućnost. Paneconomicus, 54(4), 367-395. (in Serbian). doi:10.2298/PAN0704367C. European Central Bank. (2005). Annual Report 2004. Retrieved March 10, 2013, from http://www.ecb.europa. eu/pub/pdf/annrep/ar2004en.pdf. European Central Bank. (2006). Annual Report 2005. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2005en.pdf. European Central Bank. (2007). Annual Report 2006. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2006en.pdf. European Central Bank. (2008). Annual Report 2007. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2007en.pdf. 23

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European Central Bank. (2009). Annual Report 2008. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2008en.pdf. European Central Bank. (2010). Annual Report 2009. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2009en.pdf. European Central Bank. (2011). Annual Report 2010. Retrieved March 10, 2013, from http:// www.ecb.int/pub/ pdf/annrep/ar2010en.pdf. European Central Bank. (2012). Annual Report 2011. Retrieved March 10, 2013, from http://www.ecb.int/pub/ pdf/annrep/ar2011en.pdf. European Central Bank. (2011). The monetary policy of the ECB. Frankfurt am Main: European Central Bank.

Gerdesmeier, D. (2011). Price stability: Why is it importnat to you? Retrieved March 10, 2013, from http:// www.ecb.europa.eu/pub/pdf/other/whypricestability_en.pdf. Grauwe, P. (2005). Economics of monetary union. Oxford: Oxford University Press. Jovanović Gavrilović, P. (2008). Međunarodno poslovno finansiranje. Beograd: Centar za izdavačku delatnost Ekonomskog fakulteta. (in Serbian). Mankiw, N.G., & Taylor, M.P. (2011). Economics. Andover: Cengage Learning. Scheller, H.K. (2006). The European Central Bank: History, role and functions. Frankfurt: European Central Bank.

MONETARNA I DEVIZNA POLITIKA EVROPSKE CENTRALNE BANKE Rezime: Ovaj rad se bavi analizom uspešnosti Evropske centralne banke u sprovođenju svoje monetarne i devizne politike, što je, istovremeno, jedan kompleksan zadatak, od vitalnog značaja za opravdanost njenog postojanja. ECB, najpre, ulaže velike napore da ide u korak sa svetskom krizom i da očuva stabilnost evra. Osnovni zadatak Evropske centralne banke jeste da inflaciju zadrži ispod 2%, na godišnjem nivou. Ovaj rad pokazuje da je ECB uspela da održi inflaciju u traženim okvirima, tokom značajnog vremenskog perioda, sa nekoliko kratkotrajnih izuzetaka. Uspostavljanjem adekvatne monetarne politike, ECB je uspešno ostvarila svoje ciljeve, u referentnom periodu, što je pokazano kroz rezultate trenda inflacije, monetarni agregat M3, kao i nivo kamatnih stopa.

Ključne reči: monetarna politika, Evropska centralna banka, inflacija, kamatne stope, evro. Received: November 13th, 2013. Correction: November 22nd, 2013. Accepted: January 17th, 2014.

SJAS 2014, 11 (1): 25-33 ISSN 2217-8090 UDK: 005.32:331.101.32 DOI: 10.5937/sjas11-4951 Original paper/Originalni naučni rad

JOB SATISFACTION OF MEN AND WOMEN EMPLOYED IN MANUFACTURING SECTOR AND EDUCATION IN SERBIA Jelena Vukonjanski 1, Edit Terek1,*, Bojana Gligorović1 University of Novi Sad, Technical Faculty “Mihajlo Pupin” Đure Đakovića Street, Zrenjanin, Serbia

Abstract: This paper presents the results of the research on job satisfaction of men and women employed in manufacturing sector and in education sectors in Serbia. The surveys were conducted in Serbian enterprises, as well as in Serbian primary schools. In the first survey, the data were obtained by questioning N1=256 middle managers, from 131 companies in Serbia. The sample comprised 136 men and 120 women. In the second survey, the data were obtained by questioning N2=362 teachers, from 57 primary schools in Serbia. The sample included 250 women and 112 men. T-test was used for statistical analysis. Specifically, three t-tests were used for the following groups of data: job satisfaction in industrial sector and job satisfaction in education; job satisfaction of men in manufacturing sector and job satisfaction of women in manufacturing sector; job satisfaction of men in education and job satisfaction of women in education. The main conclusions are as follows: employee job satisfaction is higher in education than in industrial sector; job satisfaction in industrial sector is higher for men than for women; job satisfaction in education is slightly higher for women than for men.

INTRODUCTION Job satisfaction is one of the most widely studied phenomena in organizational behaviour literature. Since 1972, over 3000 studies, that examine the impact and consequences of job satisfaction, have been published (Locke, 1976). In addition, there is no indication that the interest in researching job satisfaction has been reducing in the last 35 years. Spector (1997) suggests that job satisfaction is, without a doubt, the * E-mail: terekedita@gmail.com

Key words: job satisfaction, men and women, companies in Serbia, primary schools in Serbia.

most studied variable in I/O Psychology (Industrial and Organizational Psychology). He also states that job satisfaction is the central variable in many theories dealing with the phenomenon of organization, such as the nature of work, supervision and work environment. Numerous studies show the correlation between job satisfaction and variables such as organizational commitment, absenteeism, work motivation and organizational culture (Meyer et al., 2002; Sempane et al., 2002; Scott and Taylor, 1985; Martin and Miller, 1986; Locke and Latham, 1990). 25

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Individuals evaluate their jobs on the basis of factors which they regard as being important to them (Sempane et al., 2002). This evaluation is an emotional response to the work, which can vary along a continuum from positive to negative (McCormick and Ilgen, 1985). People are satisfied with their jobs when they feel good about their work. That feeling is often associated with their sense of doing a good job, becoming more skilled in their profession and having a good performance (Megginson et al., 1982). In this paper, job satisfaction is viewed as an attitude towards work as a whole (of a global satisfaction) or to certain aspects. Satisfaction with specific aspects usually refers to several aspects, including the work, supervision, pay, opportunities for advancement and associates. Due to the multidimensionality of job satisfaction / dissatisfaction, many authors choose to measure individual dimensions of job satisfaction rather than overall job satisfaction (Vukonjanski et al., 2012). Individual dimensions of job satisfaction enable the researcher to identify the relationship between individual dimensions of job satisfaction and various internal and external values. Job satisfaction is one of the predictors of many significant organizational outcomes, including job performance (Judge et al., 2001). This research revealed a number of conclusions on the relationship between satisfaction in the workplace and productivity. Also, it has been shown that factors, related to organizational culture and personal determinants, have the greatest impact. According to Bellou (2010), employees recognize fairness, opportunities for personal growth, enthusiasm for the job and a good reputation as amplifiers of job satisfaction, while aggression is seen as a cultural trait that decreases job satisfaction. Research conducted by Lee and Chang (2008), among Chinese (Taiwan) workers, confirms the strong relationship between organizational culture and job satisfaction. Similarly, Fargher et al. (2008) investigated the relationship between organizational culture and job satisfaction in Eastern and Western Europe. The study points to the strong influence of national culture on individual attitude toward job satisfaction. There are significant differences between employees in Eastern and Western Europe, which are primarily due to different meaning and influences of family and religion in these two regions. As job satisfaction is very important for the functioning of the companies, and it also has a great significance for the functioning of education26

al institutions, where the satisfaction of teachers is most widely observed. According to Shann (1998), the job satisfaction of teachers is very important, influencing factor of teachers’ commitment and performance and their retention in the profession. Therefore, the job satisfaction of teachers potentially contributes to the overall effectiveness of the school. In reference (Hoerr, 2013), it is pointed to the importance of job satisfaction of teachers for success in the classroom and the overall atmosphere in the school. Hoerr further states that the growth of teachers’ job satisfaction develops through the teaching and promotion of teachers. They become more effective, and therefore happier. According to Wolk (2008), the overall satisfaction and satisfaction of students in the school can hardly be realized without teachers who are satisfied with their work. Teachers’ job satisfaction is very modern field of research and new questionnaires for measuring the job satisfaction of teachers have been developed (Ho and Au, 2006). Finally, according to Fraser and Hodge (2000), job satisfaction has a central role in studies relating to work and occupation. The issue of job satisfaction is very sensitive in Serbia, both in manufacturing sector and in education. Employees in industrial sector often have reduced job satisfaction, due to the large volume of work, longer working hours and low salaries. Teachers are often frustrated by low incomes, relatively poor working conditions and the fact the profession of teachers is not valued enough. So, in manufacturing sector and education there are reasons why employees have reduced job satisfaction. The aim of this study is to detect the differences in job satisfaction of employees in manufacturing sector and education. It is expected that the research results will provide a better insight into and the understanding of the situation in this area. Therefore, the research highlights the elements which contribute to reduced job satisfaction in general, and especially in industrial sector and education. On the basis of these findings, it is possible to define appropriate actions, in order to increase job satisfaction. Given the importance of job satisfaction, both in manufacturing sector and in education, this will lead to improved business performance and other organizational outcomes. The results of two surveys, conducted back in 2011 and 2013 in Serbia, were used to perform the desired conclusion. The first survey was conducted in Serbian companies. Among other things,

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this survey determined the impacts of organizational culture on job satisfaction (Vukonjanski et al., 2012), satisfaction with communication on job satisfaction (Nikolić et al., 2013), as well as the relationship between leadership and leader – member exchange (LMX theory) (Nikolić et al., 2012). Another survey was carried out in primary schools in Serbia. This paper presents the results of these two surveys, which are related to job satisfaction of men and women in manufacturing sector and education in Serbia. PROBLEM

There are numerous definitions of job satisfaction. Locke (1976) defines job satisfaction as a pleasurable or positive emotional state, resulting from the appraisal of one’s job or job experiences. According to Spector (1997), job satisfaction is a person’s evaluation of his (or her) job and work context, i.e. an attitude reflecting how much people like or dislike their job. Job satisfaction is more an attitude than behavior (Robins and Coulter, 2005). However, the consequences of that attitude have an influence on behaviour: satisfied employees come to work regularly, they work better, achieve better work performance and they are loyal to their organization (Robins and Coulter, 2005). It was found that job satisfaction can contribute to the psychological stability of employees, both in and outside the workplace (Robbins et al., 2003). Job satisfaction of employees affects their physical and mental health, longevity and emotional life in general (Locke, 1976; Sempane et al., 2002). METHOD Survey instrument The Job Satisfaction Survey questionnaire (Spector, 1985) was used as an instrument for measuring job satisfaction. This questionnaire has 36 items, related to nine dimensions of job satisfaction. The answers are measured by a 6-point Likert scale. Dimensions of job satisfaction are defined and described in the following way (Spector, 1985): JS1 – Pay (Pay and remuneration), JS2 – Promotion (Promotion opportunities), JS3 – Supervision (Immediate supervisor), JS4 – Fringe Benefits (Monetary and nonmonetary fringe benefits), JS5 – Contingent Rewards (Appreciation, recognition, and rewards

for good work), JS6 – Operating Procedures (Operating policies and procedures), JS7 – Co-workers (People you work with), JS8 – Nature of Work (Job tasks themselves), JS9 – Communication (Communication within the organization). The Job Satisfaction Survey questionnaire is customarily used to measure job satisfaction in companies, therefore, in industrial sector. However, this form can be used to measure the satisfaction of employees in education, such as in reference (Astrauskaite et al., 2011). Using the same questionnaire to measure job satisfaction of employees in manufacturing sector and education, was, certainly helpful for the analysing the results in this paper. In this way, it provides a high degree of comparability of the results. Participants and data collection The survey in industrial sector included companies in Serbia. The data was obtained by questioning N1 = 256 middle managers, from 131 companies. All examined managers have higher education. In the sample of N1 = 256 respondents, there were 136 men and 120 women. This survey was carried out in 2011. The survey in education included primary schools in Serbia, from the fifth to eighth grade. The data was obtained by questioning N2 = 362 teachers, from 57 primary schools. All examined teachers have higher education. In the sample of N2 = 362 respondents, there were 250 men and 112 women. This survey was carried out in 2013. RESULTS

In the survey that was conducted in industrial sector, the values of Cronbach’s Alpha, for all dimensions of job satisfaction, range from α = 0.703 to α = 0.834. In the survey that was conducted in education, the values of Cronbach’s Alpha, for all dimensions of job satisfaction, range from α = 0.703 do α = 0.870. Table 1 shows the comparative results of the average values of all nine dimensions of job satisfaction in manufacturing sector and education. T-test (independent samples test) was used for the comparison of two sets of data (job satisfaction in industrial sector and job satisfaction in education). The main results of statistical analysis are also given in Table 1. It can be noted that, in five dimensions (JS3, JS5, JS7, JS8 and JS9), there is a statistically 27

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

Group Statistics

Std. DeviaIndustry and EduN Mean tion cation Industry 256 2.9107 1.32451 JS1 Education 362 3.0711 1.04518 JS2 JS3 JS4 JS5 JS6 JS7 JS8 JS9

Industry

Std. Error Mean .08850 .05493

256 3.3304

1.18838

.07940

Education 362 3.4710

1.31547

.06914

256 3.6641

1.29293

.08639

Education 362 4.6906

Industry

1.14312

.06008

256 2.9989

1.25291

.08371

Education 362 2.9544

1.34867

.07088

1.35047

.09023

Industry Industry

256 3.1529

Education 362 3.5753 Industry

256 3.1830

Education 362 3.2106 Industry

256 4.3571

Education 362 4.5981 Industry

256 4.4900

Education 362 5.2666

1.29203

.06791

1.04199

.06962

1.04305

.05482

1.13777

.07602

.93377

.04908

1.23553

.08255

.84890

.04462

256 3.9699

1.31775

.08805

Education 362 4.8094

.95043

.04995

Industry

Independent Samples Test Sig.

t -1.627

584

24.063

.000

-1.540

392.005

-1.304

584

.193

-.14064

6.872

.009

-1.336

508.709

.182

-.14064

6.969

.009

3.590

.059

.002 .558 7.049 36.174 44.050

.964 .455 .008 .000 .000

Sig. Mean Diﬀer(2-tailed) ence .104 -.16042

.124

-.16042

-10.042

584

.000

-1.02655

-9.756

428.911

.000

-1.02655

.398

584

.690

.04446

.405

498.963

.685

.04446

-3.779

584

.000

-.42237

-3.740

456.655

.000

-.42237

-.311

584

.756

-.02760

-.311

472.953

.756

-.02760

-2.788

584

.005

-.24092

-2.663

404.246

.008

-.24092

-9.009

584

.000

-.77662

-8.276

353.670

.000

-.77662

-8.936

584

.000

-.83953

-8.293

366.230

.000

-.83953

Table 1. Comparative result of the average values of all nine dimensions of job satisfaction in manufacturing sector and education (t-test)

Group Statistics Industry JS1 JS2 JS3 JS4 JS5 JS6 JS7 JS8 JS9

Mean

Independent Samples Test

Std. Deviation

Std. Error Mean

Men

136

3.1766

1.36458

.12157

Women

120

2.5689

1.19318

.12053

Men

136

3.4881

1.24413

.11084

Women

120

3.1276

1.08543

.10964

Men

136

3.7718

1.38925

.12376

Women

120

3.5255

1.14957

.11612

Men

136

3.1508

1.31304

.11698

Women

120

2.8036

1.14831

.11600

Men

136

3.4345

1.42695

.12712

Women

120

2.7908

1.15472

.11664

Men

136

3.2837

1.04850

.09341

Women

120

3.0536

1.02435

.10347

Men

136

4.4603

1.08001

.09621

Women

120

4.2245

1.20056

.12128

Men

136

4.6905

1.23306

.10985

Women

120

4.2321

1.19613

.12083

Men

136

4.0020

1.36033

.12119

Women

120

3.9286

1.26664

.12795

Mean Difference

Sig.

t 3.491

222

.001

.60771

3.965

.048

3.550

218.925

.000

.60771

2.274

222

.024

.36054

4.449

.036

2.313

219.040

.022

.36054

1.418

222

.158

.24632

8.824

.003

1.451

221.123

.148

.24632

2.073

222

.039

.34722

3.027

.083

2.108

218.917

.036

.34722

3.635

222

.000

.64371

7.249

.008

3.731

221.634

.000

.64371

1.646

222

.101

.23016

.136

.713

1.651

210.850

.100

.23016

1.544

222

.124

.23583

1.523

196.979

.129

.23583

2.796

222

.006

.45833

2.807

211.494

.005

.45833

.413

222

.680

.07341

.417

214.896

.677

.07341

.439 .358 .026

.508 .550 .873

Sig. (2-tailed)

Table 2. Comparative results of the average values of all nine dimensions of job satisfaction of men and women in industrial sector (t-test) 28

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

Group Statistics

Men

112

Std. Deviation 3.1092 1.07299

Women

250

3.0619

1.03995

.06096

Education JS1 JS2 JS3 JS4 JS5 JS6 JS7 JS8 JS9

Independent Samples Test

Mean

Std. Error Mean .12734

Men

112

3.3873

1.31664

.15626

Women

250

3.4914

1.31664

.07718

Men

112

4.4225

1.13593

.13481

Women

250

4.7560

1.13723

.06667

Men

112

3.0951

1.32582

.15735

Women

250

2.9201

1.35421

.07939

Men

112

3.6021

1.30629

.15503

Women

250

3.5687

1.29072

.07566

Men

112

3.3310

.98178

.11652

Women

250

3.1813

1.05700

.06196

Men

112

4.5810

.94281

.11189

Women

250

4.6022

.93315

.05470

Men

112

5.0141

.97458

.11566

Women

250

5.3282

.80523

.04720

Men

112

4.7183

1.00706

.11952

Women

250

4.8316

.93656

.05490

360

Sig. (2-tailed) .733

Mean Diﬀerence .04730

104.440

.738

.04730

-.597

360

.551

-.10408

-.597

106.791

.552

-.10408

-2.216

360

.027

-.33348

-2.217

106.879

.029

-.33348

Sig.

t .341

.337

.562

.335

.097

.756

.000

.983

.980

360

.328

.17497

.019

.889

.993

108.476

.323

.17497

.195

360

.846

.03338

.001 .778 .379 7.018 1.251

.973 .378 .539 .008 .264

.194

105.870

.847

.03338

1.085

360

.279

.14971

1.134

113.010

.259

.14971

-.172

360

.864

-.02125

-.171

105.999

.865

-.02125

-2.822

360

.005

-.31409

-2.514

94.627

.014

-.31409

-.900

360

.369

-.11331

-.861

101.569

.391

-.11331

Table 3. Comparative results of the average values of all nine dimensions of job satisfaction of men and women in education (t-test)

significant difference between the observed groups of data. The results of these five dimensions are marked in Table 1. Table 2 shows the comparative results of the average values of all nine dimensions of job satisfaction of men and women in manufacturing sector. T-test (independent samples test) was used for the comparison of two sets of data (job satisfaction of men in industrial sector and job satisfaction of women in industrial sector). The main results of statistical analysis are also given in Table 2. It can be noted that, in five dimensions (JS1, JS2, JS4, JS5 and JS9), there is a statistically significant difference between the observed groups of data. The results of these five dimensions are marked in Table 2. Table 3 shows the comparative results of the average values of all nine dimensions of job satisfaction of men and women in education. T-test (independent samples test) was used for the comparison of two sets of data (job satisfaction of men in education and job satisfaction of women in education). The main results of statistical analysis are also given in Table 3. It can be noted that, in two dimensions (JS3 and JS8), there is a statistically significant difference between the observed groups of data. The results of these two dimensions are marked in Table 3.

DISCUSSION Based on the results obtained by t- test, presented in Table 1, we can see that in five (of nine) dimensions of job satisfaction, there are significant statistical gaps between job satisfaction, among employees in manufacturing sector and education. This, overall analysis was done without taking into account the gender of respondents. Differences in job satisfaction in industrial sector and education were found in the following dimensions: JS3 – Supervision, JS5 – Contingent Rewards, JS7 – Co-workers, JS8 – Nature of Work, JS9 – Communication. In all five cases, the job satisfaction of employees is higher in education than in manufacturing sector. This can be seen from the average values of the observed dimensions of job satisfaction in manufacturing sector and education. Looking at the average marks, the results for both groups are around the average, but still higher at teachers than at those employed in enterprises. Striking of employees in the education sector (mainly because of low wages) has been common in Serbia in recent decades. Therefore, an opinion has been formed in the public that teachers are dissatisfied with their job. This view arose, because the 29

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

dissatisfaction with salary is often equated with the overall job dissatisfaction. The results, however, indicate that salary is not crucial for the perception of job satisfaction among teachers. Also, employees in education are becoming aware that their position is not really that bad, compared to the employees in industrial sector, primarily due to the shorter working hours, greater number of free days, and regular and secure incomes. Possible explanations for each dimension separately follow: ◆ JS3 – Supervision. In primary schools, like in public institutions, there is less uncertainty in the process of governance and management. In this regard, the directors of the schools are under less pressure from the leaders in manufacturing sector. Consequently, employees in industrial sector feel more pressure from the management, and this results in a decline of satisfaction with supervision. ◆ JS5 – Prizes in education are generally not of material character; they are usually given in the form of certain recognitions and accolades. For example, when a teacher has a successful mentoring and his student wins a prize in national and international competitions, it is difficult to pass without a proper acknowledgment, praise, promotion within the school and local community, and sometimes beyond. For teacher, there is a satisfaction with these and similar successes, as well as a feeling that additional efforts and successes are adequately evaluated. Teachers in such activities do not expect financial compensation. On the other hand, the employees in industrial sector expect financial compensation for any overtime, extra work and achievements. However, in the companies in Serbia, all of the above mentioned is often not accompanied by appropriate rewards. The reasons for this are poor financial strength of a large number of companies, negligence of the management and high labor force fluctuation, due to the high percentage of unemployed. Because of all this, it happens that rewards for the employees in manufacturing sector are often absent, although employees deserve them, and this leads to lower satisfaction in this area. ◆ JS7 – Co-workers. In education, the teachers are not so much directed at each other, since they each teach their courses and do not have many of common activities. If there 30

are joint activities (clubs, excursions/school trips, competitions), teachers are in a better position to choose their associates, while in industrial sector this is often not possible. The conclusion is that in education there are fewer potentially adverse situations, that may lead to dissatisfaction, than in industrial sector. ◆ JS8 – Nature of Work. The job in education may not be paid as certain jobs in manufacturing sector (although it depends on the particular company and many other factors), but carries less uncertainty and stress. Also a job in education means more free time, and summer and winter holidays. A potential problem, in the nature of work in the education sector, is the need to work with children, but people who have problem with this, usually do not start their career as teachers. (This does not mean that work in education is relatively easy, stress-free and free of responsibilities: stress and responsibility exist, but they are not concentrated on a certain amount of activity and a period of time. Errors in the economy can be immediately noticed, the consequences come much faster, and it is known who is responsible for most situations. For example, if a manufacturing process error occurs, because of a technologist’s mistake, it can endanger the health of consumers and / or employees; it can go with the withdrawal of entire series of products from the market, big losses for the company etc. On the other hand, if a teacher performs his job badly, such situation can last for years, and the effects will be visible in a few decades, when it will be difficult to identify the cause and the culprit. So in education responsibility is rather fuzzy and undefined, with no clear consequences for those who make a mistake.) ◆ JS9 – Communication. In this case, similar explanations can be accepted to those given in dimensions JS7 – Associates. Teachers, to a greater extent, can choose with whom they want to communicate. For example, if a math teacher does not want to communicate with a biology teacher, he can, actually, largely avoid the communication, and this does not, in any way, affect the work of either teacher. Based on the results obtained by t-test, presented in Table 2, we can see that in five (of nine) dimensions of job satisfaction, there are significant gaps between job satisfaction among women in indus-

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

trial sector and the job satisfaction of women in the economy. Difference exists in the following sizes: JS1 – Pay, JS2 – Promotion, JS4 – Fringe Benefits, JS5 – Contingent Rewards, JS8 – Nature of Work. In all the five cases, job satisfaction in industrial sector is higher at men than at women. This can be seen from the average values of the observed dimensions of job satisfaction between men and women in the manufacturing sector. Thus, at most dimensions of job satisfaction in industrial sector, men are more satisfied with their work. A significant number of references examine the differences in job satisfaction between men and women. The results vary in a wide range. Some pieces of research suggest that there are differences in job satisfaction between men and women (Bokemeier and Lacy, 1987; Choi, 2013). The largest number of studies, for example (D'Arcy et al., 1984; Groot and Maassen van den Brink, 2000), shows that women are more satisfied with their job than man. This is generally interpreted in the way that women have less ambitions and expectations, in the business sphere, than man. On the other hand, a small amount of research shows that men are more satisfied with their job than women (Jung et al., 2007; Chiu, 1998; Lindorff, 2011). This result is obtained in this paper. In this case, for the conditions in Serbia, this can be explained by a significant margin results for the dimension of organizational culture – gender egalitarianism, between the actual state and the state how it should be (Vukonjanski et al., 2012). Unfortunately, in manufacturing sector women are not completely equal with men, and this is reflected in the fact that men are more encouraged to professional development than women; fewer women are in authoritative positions. This situation leads to the decreased job satisfaction among women in industrial sector. In addition, for an explanation of this situation, it is necessary to consider the particular dimension which, apparently, is the key in this case, and this is the dimension JS8 – Nature of Work. The Nature of the work in manufacturing sector is such that it often requires full-time working hours, often working long hours, working on weekends, holidays. In addition, in industrial sector there are more changes that require additional work, further learning, and that brings a new loss of time and additional stress. This is especially true for women who, in such circumstances, usually sacrifice their careers and their work, to a greater extent, because of taking care of their family. The logical consequence is that men tend to have an advantage in manufacturing sec-

tor; they progress faster in their job, given that, in most cases, they have more time for business and career. As a result, men are often better able to be paid more, to get a promotion, additional privileges and be rewarded. Therefore, men are more satisfied, with the nature of the work in industrial sector, and other dimensions, as listed above. Based on the results obtained by t-test, shown in Table 3, we can see that in two (of nine) dimensions of job satisfaction, there was a statistically significant gap between job satisfaction among men in education and job satisfaction of women in education. Differences exist in the following sizes: JS3 –Supervision, JS8 – Nature of Work. In both cases, job satisfaction in education is higher at women than at men. This can be seen from the average values of the observed dimensions of job satisfaction between men and women in education. Given that, at a small number of dimensions of job satisfaction, there is a greater job satisfaction of women than men in education. These results have some similarities with the results of the research in Cyprus, where it was determined that the gender of the teacher has no effect on his/her job satisfaction (Eliophotou Menon and Athanasoula-Reppa, 2011). However, the results, obtained in this study, are also consistent with the studies that confirm that women are more satisfied with a job in education (Ladebo, 2005; Ghazi and Maringe, 2011). In education there is a balance between job satisfaction between men and women. While there are five statistically significant differences of job satisfaction in manufacturing sector, such differences in education occur only in the two dimensions of job satisfaction. As it was expected, women are more satisfied with the nature of the work in education. Women employed in the education sector feel accomplished by their professional work; they are doing a respectable job, have more time for their family and do not feel they should contribute financially more to the family. In addition, women are more satisfied with the dimension JS3 – Supervision. A possible explanation is that men in education are following the work of the school principal, because they are more interested in some of the organizational and managerial aspects of the school, and therefore, they have the opportunity to spot a situation with which they are not satisfied. At the same time, women in education, simply because they are satisfied with the nature of their work, pay less attention to the work of the principal and supervision. 31

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

CONCLUSION

Having conducted the analysis, we can conclude the following: employee job satisfaction is higher in education than in manufacturing sector; job satisfaction in industrial sector is higher at men than at women; job satisfaction in education is slightly higher at women than at men. In all the three analyses, there is only one dimension of job satisfaction, in which there are still significant differences: JS8 – Nature of Work. The impression is that this dimension plays a key role in understanding the results. Satisfaction or dissatisfaction with the nature of the work indirectly reflects on some dimensions of job satisfaction, both in industrial sector and in education. Women are more satisfied with the nature of work in education, while men are more satisfied with the nature of work in manufacturing sector. When it comes to the overall analysis, the job satisfaction is greater in education, than in manufacturing sector. This can also be explained by the nature of the work in education as, in general, this job brings more free time, with less stress, changes and uncertainty. The results may have significance for the theory and practice of management in Serbian enterprises and schools. Based on these results, managers can better understand their employees and take appropriate actions, in order to increase job satisfaction. This will have a positive impact on business performances and the effectiveness of enterprises and schools. REFERENCES Astrauskaite, M., Vaitkevicius, R., & Perminas, A. (2011). Job satisfaction survey: A confirmatory factor analysis based on secondary school teachers’ sample. International Journal of Business and Management, 6(5), 41-51. Bellou, V. (2010). Organizational culture as a predictor of job satisfaction: The role of gender and age. Career Development International, 15(1), 4-19. doi: 10.1108/13620431011020862. Bokemeier, J.L., & Lacy, W.B. (1987). Job values, rewards, and work conditions as factors in job satisfaction among men and women. The Sociological Quarterly, 28, 189-204. doi: 10.1111/j.1533-8525.1987.tb00290.x. Chiu, C. (1998). Do professional women have lower job satisfaction than professional men? Lawyers as a case study. Sex Roles, 38(7-8), 521-537. doi: 10.1023/A:1018722208646. Choi, S. (2013). Demographic diversity of managers and employee job satisfaction empirical analysis of the federal case. Review of Public Personnel Administration, 33(3), 275-298. doi: 10.1177/0734371X12453054. 32

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Vukonjanski J., Terek E., Gligorović B.  Job satisfaction of men and women

Locke, E.A. (1976). The nature and causes of job satisfaction. In M.D. Dunnette (Ed.), Handbook of industrial and organizational psychology. Chicago: Rand McNally. Locke, E.A., & Latham, G.P. (1990). Work motivation and satisfaction - light at the end of the tunnel. Psychological Science, 1(4), 240-246. doi: 10.1111/j.1467-9280.1990. tb00207.x. McCormick, E.J., & Ilgen, D.R. (1985). Industrial and organisational psychology (8th ed.). London: Allen & Unwin. Megginson, L.C., Mosley, D.C., & Pietri, P.H. (1982). Management concepts and applications (4th ed.). New York: Harper Collins. Meyer, J.P., Stanley, D.J., Herscovitch, L., & Topolnytsky, L. (2002). Affective, continuance and normative commitment to the organization: A meta-analysis of antecedents, correlates, and consequences. Journal of Vocational Behavior, 61, 20-52. Nikolić, M., Vukonjanski, J., & Terek, E. (2012). Stanje liderstva i LMX u preduzećima u Srbiji. Tehnika, 67(2), 287291. (in Serbian). Nikolić, M., Vukonjanski, J., Nedeljković, M. Hadžić, O., & Terek, E. (2013). The impact of internal communication satisfaction dimensions on job satisfaction dimensions and the moderating role of LMX. Public Relations Review, 39(2013), 563-565. doi: 10.1016/j.pubrev.2013.09.002. Robbins, M.J., Peterson, M., Tedrick, T., & Carpenter, J.R. (2003). Job satisfaction on NCAA Division III athletic directions: Impact on job design and time on task. International Sports Journal, 7(2), 46-57.

Robins, S., & Coulter, M. (2005). Menadžment. Beograd: Data Status. (in Serbian). Scott, D., & Taylor, G.S. (1985). An examination of conflicting findings between job satisfaction and absenteeism: A meta analysis. Academy of Management Journal, 28, 599-612. Sempane, M.E., Rieger, H.S., & Roodt, G. (2002). Job satisfaction in relation to organisational culture. SA Journal of Industrial Psychology, 28(2), 23-30. doi: 10.4102/ sajip.v28i2.49. Shann, M.H. (1998). Professional commitment and satisfaction among teachers in urban middle schools. The Journal of Educational Research, 92(2), 67-73. Spector, P.E. (1985). Measurement of human service staff satisfaction: Development of the job satisfaction survey. American Journal of Community Psychology, 13(6), 693-713. Spector, P.E. (1997). Job satisfaction: Application, assessment, cause, and consequences. Thousand Oaks, CA: Sage Publications. Vukonjanski, J., Nikolić, M., Hadžić, O., Terek, E., & Nedeljković, M. (2012). Relationship between GLOBE organizational culture dimensions, job satisfaction and leader-member exchange in Serbian organizations. Journal for East European Management Studies, 17(3), 333-368. Wolk, S. (2008). Joy in school. Educational Leadership, 66(1), 8-15.

ZADOVOLJSTVO POSLOM MUŠKARCA I ŽENA ZAPOSLENIH U PRIVREDI I OBRAZOVANJU U SRBIJI Rezime:

Ovaj rad predstavlja rezultate istraživanja, na temu zadovoljstva poslom muškaraca i žena zaposlenih u privredi i obrazovanju u Srbiji. Istraživanja su sprovedena u srpskim preduzećima i osnovnim školama. U prvom istraživanju, podaci su dobijeni ispitivanjem N1 = 256 menadžera na srednjem nivou, iz 131 kompanije u Srbiji. Uzorak je sačinjen od 136 muškaraca i 120 žena. U drugom istraživanju, podaci su dobijeni ispitivanjem N2 = 362 nastavna radnika, iz 57 osnovnih škola u Srbiji. Ovaj uzorak sastojao se od 250 žena i 112 muškaraca. T-test je upotrebljen za statističku analizu. Tačnije, tri t-testa su upotrebljena za sledeće grupe podataka: zadovoljstvo poslom u privredi i zadovoljstvo poslom u obrazovanju; zadovoljstvo poslom muškaraca u privredi i zadovoljstvo poslom žena u privredi; zadovoljstvo poslom muškaraca u obrazovanju i zadovoljstvo poslom žena u obrazovanju. Najvažniji zaključci, do kojih smo došli, su sledeći: zadovoljstvo poslom je veće u obrazovanju nego u privredi; zadovoljstvo poslom u privredi je veće kod muškaraca nego kod žena; zadovoljstvo poslom u obrazovanju je nešto veće kod žena nego kod muškaraca.

Ključne reči: zadovoljstvo poslom, muškarci, žene, kompanije u Srbiji, osnovne škole u Srbiji. Received: November 19th, 2013. Correction: November 23rd, 2013. Accepted: December 5th, 2013.

SJAS 2014, 11 (1): 34-42 ISSN 2217-8090 UDK: 005.591.6; 339.137 DOI: 10.5937/sjas11-5015 Original paper/Originalni naučni rad

THE IMPORTANCE OF MARKETING INNOVATION IN NEW ECONOMY Dejan Ilić1,*, Slavica Ostojić 2, Nemanja Damnjanović2 Union University - Nikola Tesla, Faculty for Strategic and Operational Management 29 Staro Sajmiste Street, Belgrade, Serbia 2 Faculty of Business Economics and Entrepreneurship 8 Mitropolita Petra Street, Belgrade, Serbia 1

Abstract: The new economy is greatly determined by the globalization process, radical and frequent changes, as well as the growing importance of knowledge application through the successful implementation of innovation. These determinants directly affect the fact that sustainable competitive advantage primarily reaches organizations that have developed the ability to improve the level of efficiency and effectiveness with the constant development of the total innovation performance. In the new economy, organizations that have the ability to develop and adopt the invention in a short period of time and profitably apply it in all areas of business reach competitive advantage over the competition in time. The growing importance of innovation in function of achieving a sustainable competitive advantage determined a brand new concept and innovation classification. Nowadays, the term innovation means not only a significant improvement in process and product technology, but it refers more to the innovation process in the field of human resources, especially in marketing management. For the above mentioned reasons, the paper pays special attention to the marketing innovation analysis and the increasingly significant impact it has on the process of achieving sustainable competitive advantage.

INTRODUCTION Productivity and competitiveness are the factors that stimulate high economic growth without inflation, but innovation is the factor which runs the new economy (Zjalić, 2007, pp. 155-182). The new economy is mainly characterized by the intensive use of knowledge, rapid changes and hyper-competition. Hyper-competition is a condition in which the competitors are emerging from the expected and unexpected directions with an aggressive approach, thus rapidly changing relationships and achieving competitive advantage (Pearlson and Shunders, 2010). 34

* E-mail: dejantilic@gmail.com

Key words: innovation, marketing innovation, sustainable development, sustainable competitive advantage, social networks.

The speed at which things are changing in the contemporary environment is an increasingly important parameter in achieving competitiveness. That is why the well-known author in the field of management, Adižes (2009), emphasizes that the change is not new, but it is new that the speed of change is increasing. In the future the only constants that will be strongly dominant are change and knowledge and they will provide the most appropriate solutions. The speed of change and development of hyper-competition on the basis of the globalization process have caused the transition from an economy based on the industrial revolution to the new economy (Ilić, 2004, pp. 99126) based on knowledge and innovation.

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SUSTAINABLE DEVELOPMENT AND SUSTAINABLE COMPETITIVE ADVANTAGE

Ilić D., Ostojić S., Damnjanović N.  The importance of marketing innovation

The sustainability is becoming one of the fundamental questions that should be the starting point of every human activity in specific modern economy. Basically, the concept of sustainability is integrating previously acquired experience, current business practices and vision for the future (Ilić et al., 2012, pp. 264-270). Sustainability as a strategic objective involves optimization of many interactions between nature, society and economy but in accordance with the Ecology criteria (Pokrajac, 2003, pp. 17-29). In all industries the concept of sustainable development integrates and coordinates the economic, scientific and technological processes, as well as different ways of natural resources exploitation. These findings further imply that only the successful implementation of innovation with a constant focus on improving profitability growth with environmental protection can guarantee sustainable development of organizations and the entire nations. Organization reaches a sustainable competitive advantage on the basis of sustainable development by strengthening the organizational culture that promotes innovation with open technology transfer and management approach of total customer satisfaction. The term total customer satisfaction is defined as the ability of the organization to deliver more value for the consumer in order to achieve a higher degree of loyalty. Total customer satisfaction represents a set of factors that differentiate the organization from its competitors and give it a unique position on the market (Porter, 2007). Innovation in the function of achieving total customer satisfaction sets a company apart from the competitor with respect to critical success factors (Kettunen et al., 2007). Sustainable competitive advantage is a relationship that involves the following: conducting business activity in more efficient, effective, and innovative way with a higher differentiation degree in order to deliver more value to the consumer compared to the reference competition (Ilić, 2012, pp. 13-35). Organizations tend to develop dynamic system identification and introduce innovation, because in this way they increase their own chances of changing the nature of competition, achieving a distinctive competitive advantage over direct competitors (Sawhney et al., 2006, p. 81). The improvement of the overall innovation of the organization’s performance is of crucial importance for higher differentiation and total customer satisfaction.

MARKETING INNOVATION AND THEIR IMPORTANCE

Innovation in the broadest sense is practical application of new ideas (Millson and Wilemon, 2008). With this broad definition it is necessary to make a distinction between the concept of creativity and innovation. Creativity refers to the ability to generate new ideas, while innovation refers to the activity which represents the process of implementation of new ideas and creation of new things (Stošić, 2007, p. 3). In addition to the drastic improvement of products and services, innovation is also related to the process that involves the collection and processing of ideas and their realization (Stošić, 2007, pp. 3-20). Innovation represents the implementation of new or significantly improved products, services, processes, new marketing method, or a new organizational method in business practices in the internal or external business organizations (OECD, 2005, pp. 9-25). All of the above applies to products, processes, methods that the organization developed for the first time and which are adapted or adopted by other organizations (OECD, 2005, pp. 9-25). A wellknown author in the field of innovation management, Trott, (2008, p. 15) defines innovation as a set of activities related to the process of gathering ideas, technological development, marketing, production of new or improved products and production processes and equipment. In the joint edition that deals with innovation, OECD and Eurostat point out that until recently innovation included improvement in the production processes and new product development, while today it includes innovation in terms of organization and marketing innovation (OECD, 2005, pp. 9-25). In the modern economy organizations that understand the new rules of marketing develop relationships directly with consumers (Scott, 2013, p. 15). The main objective of marketing innovation is to improve the identification process and profitable satisfaction of customer needs. By implementation of new marketing methods and activities organization aims to establish a closer relationship with customers and brings them into a situation when customers become promoters of the organization - a condition in which consumers are loyal to the organization and recommend it to their reference groups (Kotler and Keller, 2006, pp. 9-95). Despite the aforementioned, other objectives of marketing innovation are: penetration 35

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into new markets i.e. improving the visibility level and presence of the product in the market as well as achieving large scale and sales frequency. The basic marketing tools, i.e. basic marketing mix elements (so-called the 4P- product, price, place, and promotion) are appropriate combination of components through which organizations achieve their own marketing objectives and reach sustainable competitive advantage (Kotler, 2000). Marketing innovation is based on the promotion of the four instruments that are inter-related and focused on meeting the consumer needs by achieving a sustainable competitive advantage (Ferrell and Hartline, 2011, pp. 18-19). So, marketing innovation involves the use of completely new marketing strategies, marketing concepts or new marketing methods that have never been applied in the organization. They are based on the combination of the following elements (Stošić, 2007, pp. 3-20): ◆ Significant product design improvements (changes in form and packaging), ◆ Implementation of new pricing strategies, ◆ Implementation of an entirely new retail concept (introduction of completely new distribution channels), ◆ Implementation of an entirely new promotion concept (advertising on social networks). Product design innovation Marketing innovation in terms of changes in product design includes significant changes in the shape and packaging as integral parts of the marketing concept (Kotler and Keller, 2006). More specifically, marketing innovation in terms of product design includes significant changes in terms of packaging form or product style without affecting the functioning and usage characteristics of the product (Stošić, 2007, pp. 3-20). Marketing innovation of the design included significant changes of the following elements that an organization first applied with regard to all existing products (Stošić, 2007, pp. 3-20): the implementation of a completely new design in order to achieve dramatically different and special appearance; significant changes in appearance, shape, color and style in order to obtain a completely new, differentiated, distinctive look/appearance of the product. Marketing innovation in terms of product packaging would include significant changes in the following elements (Trott, 2008, pp. 424-438): significant improvement of the packaging protec36

tive function, materials, reliability and satisfaction when opening and using packaging, significant improvement of packaging identification that includes additional information on the use, promotional/ sales actions, significant improvement of the package shape and size. Innovation of pricing strategy According to the economic theory, price is a balance between supply and demand. That is the reason why the pricing strategy uses the turning profitability point as the basis of innovation. So, for all of these examples, the rule is that lower limit of price formation makes the turning point (point of return). The price level above the turning point is formed on a variable manner influenced by the demand level. Marketing innovation in pricing involves the use of a completely new pricing strategy that the organization applies for the first time in its products and services in a particular market (OECD, 2005, pp. 9-25). An example of marketing innovation in pricing is the application of a new variable price calculation based exclusively on demand factors for a particular product or service. For example, innovation is the application of the method in the organization for the first time and involves the approval of discounts in the store for consumers that have certain credit or preferential cards issued by organizations. Discounts may be financial in the form of lower prices or physical when a consumer gets a greater amount at the same price or receives a completely new product as a bonus. One more example is given as a marketing innovation. Marketing innovation may be the introduction of a new interactive method of “online” pricing on the organization website. “Online” service allows the consumer to choose the desired set of products on the organization’s website and receive a price that is formed exclusively on the basis of individually selected product characteristics (OECD, 2005, pp. 9-25). Innovation of sales channels The introduction of new sales channels and marketing innovation include implementation of new marketing methods that have never been applied in the organization. The introduction of new sales channels includes the implementation of entirely new marketing methods and selling products/services to customers. The introduction of new sales channels is marketing innovation while improving logistics

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(transport, storage and handling of the product) is not represented. The examples of marketing innovation related to the introduction of new distribution channels are: first, the introduction of licensing products, franchise, exclusive sales, and direct sales (the introduction of their own sales network i.e. their own chain of retail centers or development of direct trade via the Internet). Innovation of promotional methods

The basis of all promotional activity is a communication process. For this reason, the concept of promotion is a mechanism for communication and exchange of information between consumers and organizations. The task of promotion is to inform, remind and persuade consumers to act, purchase and consume certain products (Trott, 2008, pp. 351-385). Marketing innovation is the implementation of a new marketing method to promote products or services of a particular organization. Examples of brand new marketing promotion method are: ◆ The introduction of an entirely new kind of media - promoting products/services in a feature film, a TV show or on the Internet (the first introduction of the web site or promotion via internet social networks like Facebook, MySpace, Twitter; ◆ The introduction of completely new techniques, such as the use of celebrities in order to improve the promotion of products/ services; ◆ Significant improvement or modification brand-development and implementation of a completely new or significantly improved symbol that is drastically different from the current visualization (OECD, 2005, pp. 9-25). The main objective of marketing innovation in terms of branding is product positioning in the new market or creating a new image (introducing a brand new personalized presentation of products/services based on the specific requirements of individual customers). SOCIAL NETWORKS AND MARKETING INNOVATION RELATIONSHIP In the interactive era of the twenty-first century organizations are strategizing how to gain sustainable competitive advantage from the information they gather about customers (Peppers and Rogers, 2011, p. 4). This is the reason why organizations must manage

their customer relationships effectively in order to remain competitive (Peppers and Rogers, 2011, p. 3). There are transactional and relational marketing in the marketing literature (Ferrell and Hartline, 2011, p. 24). In transactional marketing key element is marketing mix. In relationship marketing, the relations with customers and business partners are of key importance (Rakić and Rakić, 2008, pp. 255-259). Relationship marketing is based on good communication (Feiertag, 1997, p. 18). Relationship marketing consists of “invisible network”, “focused message” and approach such as “listen and serve” (Levinson and McLaughlin, 2005, pp. 8-12). Establishing and maintaining relationships with business partners affect the effectiveness. Communication with customers enables the production of “real” products according to the customer needs and desires. Communication with suppliers enables the purchase of “real” inputs. Communication with distributors enables delivering products to consumers when needed. To establish and maintain communication, it is necessary to apply information technology. Another significant change is changing the customer role (Rakić and Rakić, 2003, pp. 95-104). It is often unproductive to allocate big sums of money to the forced media campaigns. During the crisis shopping habits and consumption are changing. The job loss and lower incomes are examples of market paralysis convergence and bad debts. Only powerful companies (large market players) directed funds to TV commercials trying to bring their brands to the customer’s living room. However, the impressive advertising costs of the strongest national media (RTS, Pink, B92, etc.) can smartly reduce and redirect resources to higher visibility on the shelves. It is desirable to direct part of the “marketing” money to the gathering places of their consumers - such as the Internet and social networks. It is important to achieve long-term brand positioning (Manić, et al., 2009, pp. 205-214). Thanks to the Internet, consumers are more connected and they are more active and more demanding. Technological advancements have enabled organizations to manage customer relationship more efficiently, but also empowered customers to “be informed and demand much more” (Peppers and Rogers, 2011, p. 3). Longterm relationships will not materialize unless these relationships create value for each participant. This is especially true for customers faced with many different alternatives among firms. It further directs the organization to engage customers in the process of defining a single common value concept (Ferrell and Hartline, 2011, pp. 23-24). 37

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In a competitive environment organizations cannot rely only on the internal environment of research and development. It is necessary to engage partners outside the company in accordance with the “connect and develop” model of innovation (Rakić and Rakić, 2007a, pp. 329-338). Marketing activity of the company must be harmonized to produce the best effects. Each form of communication has its own specific features including communication through social networks, which requires the creation of a special message for social networks. All these marketing innovations are of great importance for raising the total performance of the organization. However, in modern digital society, marketing innovations related to the exploitation of the Internet increasingly gain in importance. They are set aside in a special category called Internet marketing. In recent years Internet marketing and social media have become a “new hybrid component of integrated marketing communications that allow organizations to establish strong relationships with their consumers (Mangold and Faulds, 2009, pp. 357-360). In today’s economy, Internet marketing and especially the use of social networks for achieving more successful advertising, promotion and closer contact with consumers, have become increasingly significant. Internet marketing and online social network have become increasingly significant, because, “we are in the era of social marketing” (Reed, 2012, p. 3). Examples of the importance of advertising on social networks are shown in the following data: in July 2009 Facebook had 350 million users, MySpace 125 million and Twitter 75 million (Treadaway and Smith, 2010). Nowadays, Facebook has over 1.19 billion monthly active users (Facebook, 2013). This is the reason why the organization within the marketing budgets for advertising in 2014 allocated more resources than the previous year: 4.2% for TV, 5.5% more than in the past for billboards and even 27% for Internet advertising (Oglašivači najviše novca izdvajaju za TV, 2013). One of the most important aspects of marketing innovation is the promotion of organization and organizational products and services through social networks as Facebook, MySpace; creativity works-sharing sites as YouTube; collaborative websites like Wikipedia, and micro blogging sites as Twitter (Mangold and Faulds, 2009, pp. 357-360). Marketing on the social network “is not about you getting your story out; it’s about your customers; 38

it’s about being more transparent, earning trust, and building credibility” (Webber, 2009, p. 36). Social networks are the basis of the use of guerilla marketing, which focuses on achieving maximum results with minimum investment. Guerrilla marketing assumes innovation and creativity of those who deal with it or those who wish to apply (Levinson, 1989). When properly executed, advertising on social network can be a powerful guerrilla weapon (Levinson and McLaughlin, 2005, p. 108). Guerrilla Facebook Marketing weapons refer to Facebookspecific features, tools and resources that guerrillas can use to further their marketing plans (Levinson and Kelvin, 2013, p. 129). Facebook offers space for unconventional type of marketing without investing any money. Profile is created in a way to attract more “friends”. It is easy to express a desire for a particular brand, product or company which is beeing advertised. An example of guerrilla marketing is an American pizza chain Papa John’s. Thanks to a guerrilla campaign on Facebook, they gathered 148,000 fans. The campaign was designed so as that each new fan gets a free pizza delivered to their home (Stanojević, 2011, p. 168). MARKETING INNOVATION IN THE REPUBLIC OF SERBIA In order to perceive the situation and propose corrective actions regarding the marketing innovation, this paper analyzes the results of several different studies. The studies were about innovative activities of organizations operating in the Republic of Serbia. First results included in the analysis were taken from a study conducted in 2008-2010, (Republički zavod za statistiku, 2011, pp. 1-6). The sample of 3982 organizations included active small and medium enterprises (over 10 employees) and 492 large business systems. The results of the research show that the most common activities refer to innovation of the organization with 32.5%, followed by marketing innovation with 29.3%, and the least common one is product/service innovation with 27.4%. Percentage of organizations that did not innovate was even 52.1%. There were high rates of organizations in the time interval 2008-2010 that didn’t innovate (Republički zavod za statistiku, 2011, pp. 1-6). The figure shows a negative balance in terms of innovation for the majority of organizations (operating) in the Republic of Serbia. The Ministry of Finance and Economy announced that the Republic of Serbia accounts for 99.8% of total

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enterprises in the entrepreneurial sector (Izveštaj o malim i srednjim preduzećima i preduzetništvu u 2011, 2012, p. 15). Further analysis should incorporate the results of another study whose aim was to analyze current situation and possibilities for improvement of small and medium enterprises (SMEs). Research on small and medium enterprises (SMEs) was conducted by the Statistical Office of the Republic of Serbia. The study was published in the report on small and medium enterprises and entrepreneurship (Izveštaj o malim i srednjim preduzećima i preduzetništvu u 2011, 2012, pp. 15-66), and the results refer to the year 2010. The survey was conducted on a sample of 3,500 organizations including micro enterprises (1-10 employees) and entrepreneurs (regardless of the number of employees). Selected results of the survey were as follows: the effects of innovation are conducted in 54% of cases referred to the saving of raw materials and energy, 46% reduction in labor costs and only 22% have some form of safeguard intellectual property. The total number of respondents who protect any kind of intellectual property is 62% regarding the private brand, 21% of the design and only 8% of patents. When it comes to innovation, marketing results were as follows: packaging design changes or product/service 11.65%, new marketing methods to promote products 15.31%, new or changed methods of distribution 8.87%, the new pricing method 20.14%. The analysis of the results obtained from this research show that small and medium enterprises (SMEs) are primarily focused on the development of innovation with their own forces, and then in cooperation with other organizations and institutions. The effects of the introduced innovations in SMEs are mostly related to the improvement of product quality 28.82%, increase of the range of products and services 23.64%, application of new pricing methods 20.14 %, and the least significantly related to the reduction in costs per unit and improvement of internal and external communication - 5.31%. The next study involved the analysis of the qualitative research that was conducted in the period October-December 2011 in the territory of the Republic of Serbia (Ilić, 2012, pp. 208-238). The above qualitative research refers to the evaluation of the expert awareness level of various profiles of the impact of innovation in improving the competitive advantage of organizations. The method used in the interview includes qualitative form of research that is based on the discussion - a moderator and only one subject.

This type of research is conducted to provide a deeper insight in the state that is currently characteristic for the organization in the Republic of Serbia regarding innovation and competitive advantage, but also the level at which innovation is actually implemented in organizations. Respondents who participated in this research represent a deliberate pattern or “experts sample”. That means that the respondents were not selected randomly, but based on carefully defined criteria and based on their knowledge and expertise in the business success of the organizations in which they work. The results of this qualitative study show that, unfortunately, not enough effort and financial resources were invested in successful implementation of innovations in all fields. This particularly refers to the marketing innovation area despite the previously mentioned quantitative results that the level of marketing innovation in the Republic of Serbia of 29.3% exceeds the level of marketing innovation in the EU of 26.6% (European Commission and Statistical Office of the European Communities, 2011, pp. 79-95). According to the opinion of respondents in the conducted qualitative research, higher level of investment in marketing innovation is the result of confusion that most of the respondents have regarding the classification of unfounded minor stylistic changes in web sites and seasonal price changes and/or seasonal promotions, they classify them as marketing innovations, but these are not marketing inovations. However, there are positive examples of marketing innovation in the Republic of Serbia. One of them is marketing agency McCann Erickson. In 2010-2011 McCann Erickson improved the quality of services to clients in the fields of advertising, especially in the field of advertising on social network such as Facebook (Ilić, 2012, pp. 208-242). In support of the above conclusion it also lists data released by the Statistical Office of the Republic of Serbia and according to them in 2012 97.7% organizations use the Internet for business, while 47.5% of the Serbian population use the Internet daily (Republički zavod za statistiku, 2013). As for the number of Facebook users, according to research results published on the website Adriatalk.com, Serbia is ranked as number one in the region and the 18th in Europe (Banković and Gijić, 2010, pp. 390-395). The results of this study show that the total number of Facebook users in Europe exceeded 114 million. This trend further emphasizes the importance of promoting the organization through social networks and other forms of marketing innovation in the process of strengthening relationships with consumers. 39

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CONCLUSION

Facebook. (2014). Key facts. Retrieved October 5, 2013, from http://newsroom.fb.com/Key-Facts.

Companies can gain sustainable competitive advantage through differentiation based on creating a single common value concept for consumers and contributing to sustainable development. Sustainable development is an important aspect of marketing. Besides economic viability, company must achieve the goals of environmental sustainability. The companies preferred in the contemporary economic conditions are the ones managing to link innovation and marketing successfully. Innovation can be seen as an asset of the company, which is directly related to the feedback of marketing. Innovation is the main driver of competitiveness. In today’s digital era it is important to make maximum use of new communication technologies and the Internet - especially in marketing and sales. The real challenges lie ahead of the company management: which marketing tools to retain and amplify, which ones to leave out and which sales strategy is the most effective. Nowadays, it is not just enough to know what consumers are looking for. Those who are familiar with market trends can predict which products consumers will put emphasis on. The changes have become more frequent and more distinct. The changes have become “the law of the market”. However, the biggest threat is the increasing speed of changes. The change was a crucial factor for professionals in marketing and sales. Of course, sometimes it is best to maintain market position and retain market share. When the crisis waves begin to lose strength, it is ideal to have a good start in the competitive arena. You need to think of and plan the time after the crisis.

Feiertag, H. (1997). Relationship selling works only when practiced. Hotel & Motel Management, 212(6), 18.

REFERENCES Adižes, I. (2009). Kako upravljati u vreme krize: I kako je pre svega izbeći. Novi Sad: Asee. (in Serbian). Banković, D., & Gijić, N. (2010). Application of WEB 2.0 technologies in business. In: Application of new technologies in management, 2nd International Conference ANTiM 2010 (pp. 390-395). Tara: Faculty for Education of the Executives of the University of Business Academy. European Commission, & Statistical Office of the European Communities. (2008). Science, technology and innovation in Europe. Luxembourg: Office for Official Publications of the European Communities. 40

Ferrell, O.C., & Hartline, M.D. (2011). Marketing strategy (5th ed.). Mason, OH: South-Western Cengage Learning. Ilić, B.B. (2004). Tranzicija industrijske (tradicionalne) u novu (informatičku) ekonomiju. Ekonomski anali, 49(162), 99-26. (in Serbian). doi: 10.2298/ EKA0462099I. Ilić, D. (2012). Menadžment inovacija u funkciji stvaranja i održavanja konkurentne prednosti organizacija. Novi Sad: Alfa University, FORKUP. (in Serbian). Ilić, D., Veljković, D., & Ostojić, S. (2012). Sustainable development of organization via production of alternative fuel. In: Application of new technologies in management, 3rd International Conference ANTiM 2012 (pp. 264-270). Beograd: Faculty for Education of the Executives, Alfa University. Izveštaj o malim i srednjim preduzećima i preduzetništvu u 2011. (2012). Beograd: Ministarstvo finansija i privrede; Ministarstvo regionalnog razvoja i lokalne samouprave; Nacionalna agencija za regionalni razvoj (pp. 15-66). (In Serbian). Kettunen, J., Ilomaki, K., & Kalliokoski, P. (2007). Making sense of innovation management. Helsinki: The Federation of Finnish Technology Industries and Teknologiainfo Teknova Oy. Kotler, P. (2000). Marketing management. New Jersey: Prentice Hall. Kotler, P., & Keller, K. (2006). Marketing management (12th ed.). New Jersey: Prentice Hall. Levinson, J.C. (1989). Guerrilla marketing attack: New strategies, tactics, and weapons for winning big profits for your small business. Boston: Houghton Mifflin. Levinson, J.C., & Lim, K. (2013). Guerrilla Facebook marketing: 25 target specific weapons to boost your social media marketing. New York: Guerilla Marketing Press. Levinson, J.C., & McLaughlin, M.W. (2005). Guerrilla marketing for consultants: Breakthrough tactics for winning profitable clients. Hoboken, N.J: Wiley. Mangold, W.G., & Faulds, D.J. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357-360. Manić, M., Riznić, D., & Ostojić, S. (2009). Inovativne strategije marketinga i prodaje u uslovima globalne krize. In: Zbornik radova: Suočavanje sa globalnom ekonomskom krizom od strane kompanija i ekonomije, Sedmi Međunarodni naučni skup Megatrend univerzitet (pp. 205-214). Beograd: Megatrend univerzitet. (in Serbian).

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Millson, M.R., & Wilemon, D.L. (2008). The strategy of managing innovation and technology. Upper Saddle River, N.J: Pearson Prentice Hall. Oglašivači najviše novca izdvajaju za TV. (2013). Marketing mreža. Retrieved October 21, 2013, from http://marketingmreza.rs/oglasivaci-najvise-novcadaju-za-televiziju. (in Serbian). Organisation for Economic Co-operation and Development, & Statistical Office of the European Communities. (2005). Oslo manual: Guidelines for collecting and interpreting innovation data (3rd ed.). Paris: OECD Pub. Pearlson, K., & Saunders, C.S. (2010). Managing and using information systems: A strategic approach (4th ed.). Hoboken, N.J: Wiley. Peppers, D., & Rogers, M. (2011). Managing customer relationships: A strategic framework (2nd ed.). Hoboken, N.J: Wiley. Pokrajac, S. (2003). Održivi razvoj i moderna tehnologija kao ekološka raskršća savremene civilizacije. Beograd: Megatrend univerzitet. (in Serbian). Porter, M.E. (2007). Konkurentska prednost: Ostvarivanje i očuvanje vrhunskih poslovnih rezultata. Novi Sad: Asee. (in Serbian). Rakić, B., & Rakić, M. (2003). Radikalne promene: Primena marketinga u organizacijama i privredi u procesu globalizacije. In: Zbornik radova: Međunarodni naučni skup Radikalne promene u preduzećima i privredi u uslovima globalizacije, 28. novembar 2003. Beograd: Megatrend univerzitet primenjenih nauka. (in Serbian). Rakić, B., & Rakić, M. (2007). Changes in contemporary marketing in the conditions of globalization. In: Management and marketing under globalization: proceedings, International scientific conference contemporary challenges of theory and practice in economics (pp. 329-338). Belgrade: Faculty of Economics of the University of Belgrade, Publishing Centre. Rakić, B., & Rakić, M. (2008). Marketing i inovacije u funkciji razvoja organizacija i privrede. In: Razvojne strategije preduzeća i privrede: zbornik radova, Šesti međunarodni naučni skup, 28. novembar 2008 (pp. 255-259). Beograd: Megatrend univerzitet. (in Serbian).

Reed, J. (2012). Get up to speed with online marketing: How to use websites, blogs, social networking and much more. Upper Saddle River, N.J: FT Press. Republički zavod za statistiku. (2011). Indikatori inovativnih aktivnosti u Republici Srbiji, 2008-2010. Retrieved October 3, 2012, from http://webrzs.stat. gov.rs/WebSite/repository/documents/00/00/55/83/ IA01_2010_srb.pdf. (in Serbian). Republički zavod za statistiku. (2013). Upotreba informaciono-komunikacionih tehnologija u Republici Srbiji, 2013. Retrieved December 9, 2013, from http://webrzs.stat.gov.rs/WebSite/repository/documents/00/01/14/03/PressICT2013.pdf (in Serbian). Sawhney, M., Wolcott, R., & Arroniz, I. (2006). The 12 different ways for companies to innovate. MIT Sloan Management Review, 47(3), 75-81. Scott, D.M. (2013). The new rules of marketing & PR: How to use social media, online video, mobile applications, blogs, news releases, and viral marketing to reach buyers directly (4th ed.). Hoboken, N.J: John Wiley & Sons. Stanojević, M. (2011). Marketing na društvenim mrežama. MEDIANALI, 5(10), 165-180. (in Serbian). Stošić, B. (2007). Menadžment inovacija: Ekspertni sistemi, modeli i metode. Beograd: Fakultet organizacionih nauka. (in Serbian). Treadaway, C., & Smith, M. (2010). Facebook marketing: An hour a day. Indianapolis: Wiley Pub. Trott, P. (2008). Innovation management and new product development. Harlow, England: Financial Times/ Prentice Hall. Webber, L. (2009). Marketing to the social web: How digital customer communities build your business. Hoboken, N.J: Wiley. Zjalić, Lj. (2007). Inovativnost - nezaobilazan činilac razvoja. Međunarodni problemi, 59(1), 155-182. (in Serbian). doi: 10.2298/MEDJP0701155Z.

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ZNAČAJ MARKETING INOVACIJA U SAVREMENOJ EKONOMIJI Rezime: Savremena ekonomija je u najvećoj meri, determinisana procesom globalizacije, radikalnim i frekventnim promenama kao i rastućim značajom primene znanja kroz uspešno implementiranje inovacija. Navedene determinante direktno utiču na činjenicu da održivu konkurentnu prednost prvenstveno dostižu organizacije koje su razvile sposobnost unapređenja nivoa efikasnosti i efektivnosti uz neprestani razvoj ukupnih inovacionih performansi. U savremenoj ekonomiji, organizacije koje su razvile sposobnost da u što kraćem vremenskom intervalu usvoje invencije i na profitabilan način ih primene u svim oblastima poslovanja, dostižu konkurentnu prednost u odnosu na referentnu konkurenciju tokom vremena. Rastući značaj inovacija u funkciji dostizanja održive konkurentne prednosti je uslovio i sasvim novi pristup pojmu i novu klasifikaciju inovacija. Danas se pod pojmom inovacija ne podrazumeva isključivo proces značajnog unapređenja proizvoda i tehnologije, već se pojam sve više odnosi na proces inoviranja u oblasti upravljanja ljudskim resursima a naročito u oblasti marketing menadžmenta. Iz navedenih razloga, u radu je posebna pažnja posvećena upravo analizi marketing inovacija i sve značajnijem uticaju koji imaju na proces dostizanja održive konkurentne prednosti.

Ključne reči: inovacije, marketing inovacije, održivi razvoj, održiva konkurentna prednost, društvene mreže. Received: November 29th, 2013. Correction: December 25th, 2013. Accepted: February 21st, 2014.

SJAS 2014, 11 (1): 43-52 ISSN 2217-8090 UDK: 005.574:305-055.1/.2 DOI: 10.5937/sjas11-5298 Original paper/Originalni naučni rad

THE EFFECT OF GENDER ON NEGOTIATION BEHAVIOUR Gordana Dobrijević* Singidunum University, Department of Business 32 Danijelova Street, Belgrade, Serbia

Abstract: As men and women have different roles in society, their negotiating styles and behaviours are also different. The success of men and women in negotiations depends largely on the type of negotiation (integrative or distributive) and gender stereotypes prevailing in society. There is a general opinion that women are more cooperative, while men are more aggressive and competitive in negotiations. Our findings from the Serbian setting show a somewhat different picture: women do not use more cooperative strategies and tactics than men. Although men focus on winning, they also focus on problem solving; while women focus on conflict avoidance, and, to a certain extent, on mutual relationship. Women are also more sensitive to their counterpart’s age and gender. But, they are also less sincere in negotiations and focus on their own interests, rather than taking care of their own as well as other party’s interests. A major theoretical implication of this research is that the observed differences in the behaviour of female negotiators reflect the pressure to be successful in a male-dominated society where gender stereotypes are quite prominent.

INTRODUCTION Negotiation is one of the ways by which people deal with their differences and many challenges they encounter. There are many situations in life and in business that we try to solve by means of negotiation: friends negotiate to decide where to have lunch, nations negotiate about borders, and companies negotiate about buying or selling their products. People negotiate all the time, although often they are not even aware of it. Obviously, some people are better negotiators than others, due to individual differences. We all have a natural style that influences our negotiations with others, although we adapt that preferred style to the particular situation and participants. The main factors influencing the negotiation style are personality, culture, and gender (Dobrijević, 2009). * E-mail: gdobrijevic@singidunum.ac.rs

Key words: negotiation, men, women, gender differences, gender stereotypes.

This paper presents an analysis that builds on past research on gender and negotiation. The main purpose of this study was to investigate gender differences among professionals in Serbia. This study tries to contribute to the literature on negotiation in several ways. First, we combine theoretical constructs from the literature on negotiation and gender in general. We examine various gender differences and stereotypes, based on theoretical and empirical work of eminent authors. Second, we try to understand gender differences in the Serbian setting. Understanding gender differences is theoretically and empirically important because it can improve the negotiation outcome, especially for women. This paper also contributes to the literature on international management because of its focus on a particular nation. After decades of war and political and economic crisis, the whole Western Balkans has opened up to new opportunities and integration, and Serbia has 43

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recently signed the EU Stabilization and Association Agreement. SOCIAL ROLES OF MEN AND WOMEN Although the terms sex and gender are commonly used as synonyms, scientists make a clear distinction: sex refers to the biological categories of male and female, while gender refers to “the cultural and psychological markers of the sexes” – the features of role that distinguish men from women in some culture or society (Lewicki et al., 2010, p. 404). We can identify different gender roles, which do not necessarily correspond to the existing sexual stereotypes. Holt and Ellis (as cited in Canet-Giner and Saorín-Iborra, 2007, p. 212) defined gender roles as “expectations about what is appropriate behaviour for each sex”. Apart from the masculine and feminine profiles, research has shown other gender roles, such as androgyny and undifferentiated profiles (Brewer et al., 2002). While masculine profiles are characterised as competitive, assertive, analytical, dominant, and individualistic, feminine profiles are depicted as sympathetic, affectionate, soft-spoken, understanding, and sensitive to the needs of others. According to Brewer et al. (2002), androgynous profiles show high levels of both masculinity and femininity. They are more flexible and adaptable; they can play different roles, as appropriate in a given situation. Contrarily, undifferentiated individuals have low levels of both kinds of behaviour. However, we are not going to engage in the analysis of this undifferentiated profile, but focus on the differences between “traditionally” male and female gender/sex. According to Judith Briles (as cited in Wyatt, 1999), it seems that early childhood plays tell a lot about a person’s future business style, especially in negotiations. She thinks that the society we live in defines appropriate roles for both genders, as they are culturally conditioned. While men see business as a team sport and play aggressively, women perceive business as a series of personal meetings. They are generally taught to get along with others and be nice. In many cultures, e.g. Serbia, girls’ toys include various household appliances, by which they learn to be “good housewives”. According to Wyatt (1999), women negotiate for what is fair and men play to win. That is probably one of the main reasons why women achieve better results in cooperative negotiations, and men are better in competitive negotiations. 44

According to Wirls (as cited in Yeganeh and May, 2011), distinct gender roles lead to considerable inequalities in many social, political, economic, financial, educational, conjugal, and work-related issues. In business environment, women often imitate male behaviour in order to succeed in their career (Vanderbroeck, 2010). Various pieces of research (e.g. Reuvers et al., 2008; Eagly and Johnson, 1990) have shown that women and men (although equally successful as leaders) have different leadership styles – while women are more focused on employee well-being, men focus on domination over others and solving tasks, which corresponds to stereotypical male and female behaviour. A recent study by Vinkenburg et al. (2011) investigated stereotypes about the importance of leadership styles for the promotion of women and men to different levels in organizations. Inspirational motivation (optimism and excitement about the future) was seen as more important for men than women, particularly for a promotion to CEO. On the contrary, individualized consideration (development and mentoring of followers) was seen as more critical for women than men, especially for the advancement to senior management. In Serbia even the choice of one’s profession is many times strongly influenced by inherited stereotypes. Women normally engage in humanities (around 65 per cent), while men study engineering (75 per cent). Both genders are equally represented in medicine (Kolin and Čičkarić, 2010). Almost all of Serbian elementary school teachers are women. In Serbia we even had the opportunity of seeing TV advertisements promoting stereotype-free working environment where “even a young woman could be” an engineer or a manager. NEGOTIATION BEHAVIOUR Negotiation behaviour is tactical. Negotiators try to attain their goals by gaining their counterparts’ consent through influence. Various behavioural tactics are used in negotiations regardless of the negotiators’ general strategy, e.g. cooperative or competitive (Rao and Schmidt, 1998). These tactics can be verbal and non-verbal. Generally, when we talk about cooperative negotiation behaviour, we think of openness and information sharing, asking open-ended questions, listening, and creating empathy. This kind of communications normally leads to mutual understanding. On the other hand, competitive behaviour includes threats, demands,

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withholding information, poor mouthing, setting deadlines, etc. As such, this kind of behaviour leads to less effective communication. Canet-Giner and Saorín-Iborra (2007) present the distinction between integrative and competitive behaviours as a continuum and not as a dichotomy. This means that negotiating parties can display different behaviours involving integrative and competitive orientations, resulting in different levels of communicative effectiveness. In addition, negotiators can adopt different types of behaviour throughout the interaction (Lax and Sebenius, as cited in CanetGiner and Saorín-Iborra, 2007). While there have been many studies emphasizing the differences in cooperative-competitive orientation between men and women, some evidence also shows that these differences are insignificant (Westbrook et al., 2011). In a cross-cultural study, Lynn (as cited in Westbrook et al., 2011) surveyed students from 20 countries and found that men scored higher on competitiveness than women in only six of the 20. These were the USA, Canada, the UK, Germany, Iceland, and Ireland. It seems that men’s higher degree of competitiveness is not universal and may be more in line with cultural aspects of their country of origin. The authors believe that over time, and due to changes in organizational socialization and increased teamwork, the gap between men’s and women’s level of competitiveness gets narrower. Empirical results from their study showed no differences between men and women with a hypercompetitive attitude, supporting earlier theories that the gap in competitiveness between men and women is decreasing. GENDER AND NEGOTIATION BEHAVIOUR During the last several decades there have been many pieces of research on gender in negotiations, e.g. Wall (1976) and Druckman et al. (1977). The studies have shown two significant distinctions between male and female negotiators. Firstly, on average, men behave more competitively than women, and secondly, on average, men have better results than women (Kray, 2007). Some studies of competitive bargaining found that women are likely to be less competitive and have worse outcomes than men (Stuhlmacher and Walters; Walters et al., as cited in Amanatullah, 2008). There is a general perception that women are more cooperative while men are more aggressive and competitive (Babladelis et al., as cited in Westbrook

Dobrijević G.  The effect of gender on negotiation behaviour

et al., 2011). According to Calhoun and Smith (1999), women are also more likely to rate themselves as friendly and trustworthy. Results of a study carried out by Brahnam et al. (2005) indicate that women are more inclined to use a collaborative conflict resolution style and men tend to avoid conflict. Since cooperation is generally seen as more useful and avoidance more obstructing in the conflict resolution process, their study suggests that women may have more productive conflict resolution characteristics than men. The research of Brewer et al. (2002) shows that masculine gender role is more likely to be correlated with the dominating conflict style, feminine orientation with the avoiding conflict style, and androgynous orientation with the integrating conflict management style. There was no evidence about the correlation between gender role and the compromising conflict management style. According to Lewicki et al. (2010), there are five cognitive and behavioural processes that indicate gender differences in negotiation: 1. Men and women think of negotiations in different ways –what the negotiation is all about. While women concentrate on relationships, men concentrate on tasks; 2. Men and women communicate differently – while men tend to discuss positions, women disclose more personal information and emotions; 3. Men and women are regarded differently in negotiations – there is evidence that women are often treated worse than men in negotiations; 4. There are different effects of similar tactics when used by men and women – women who use exchange tactics are less successful than men; 5. Gender stereotypes influence negotiator performance – if they are aware of some gender stereotypes, they will act in ways that support those stereotypes. Gender stereotypes have a major impact on men’s and women’s success and behaviour in negotiations. Female empathy and better communication skills are the usual gender stereotypes. However, in the research carried out by Kray et al., 2002 (as cited in Kray, 2007, p. 163), reminding negotiators of these feminine features before a mixed-gender negotiation actually led women to outperform their male adversaries. Female negotiators approached negotiations more assertively and with higher expectations of their ability to succeed, which are two critical characteristics that can help any negotiator to reach 45

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a better outcome. Kray (2007) also says that context is a stronger predictor of negotiation performance than gender. The beliefs the negotiators bring with them to negotiations dictate the goals they set, their behaviour, and performance. Persisting is stereotypically a masculine response. Riley Bowles and Flynn (2010) studied how gender influences persistence in negotiation. They found that actual persistence behaviour in negotiation is not a simple result of gender stereotype. They claim that the impact of gender on persistence is better predicted by the gender pairing in a dyad than by the gender of an individual negotiator. Their results show that women persist more, but in more indirect ways, with male than with female naysayers. Their results challenge the gender-stereotypic reasoning that men persist more than women, showing that it is the gender composition of a negotiating dyad that matters more than the gender of an individual negotiator. Very often women fail to initiate negotiations, even if it would be in their best interest. Babcock and Laschever (2010) confirmed that in several pieces of research. Men ask for things they want and start negotiations much more often than women – two to three times as often. They believe this is the explanation of why men in average earn 7-8 per cent more than women. Women either silently accept what they are offered or complain, but they rarely ask for more. These authors emphasize the fact that the most important step in any negotiation is deciding to negotiate in the first place. A research by Yeganeh and May (2011) brought some new insight on cultural dimensions and the so called gender gap. The global gender gap index (GGI), introduced in 2006 by the World Economic Forum, is a “measure that captures national genderbased inequalities on economic, political, education, and health-based criteria” (Hausmann et al., 2007, as cited in Yeganeh and May, 2011, p. 109). The authors found that socio-economic development, cultural values, and the gender gap are closely intertwined. The results indicate that countries with higher conservative values (like Islamic nations) are more likely to emphasize the gender inequality, unlike the Nordic region on the other extreme. FACTORS THAT MAKE GENDER RELEVANT IN NEGOTIATIONS According to Riley and McGinn (2002), there are some situational factors that make gender relevant 46

to behaviour or expectations. They call them “gender triggers”. There are many different potential gender triggers in negotiation. They do not necessarily create identical outcomes (e.g. gender triggers do not always benefit male over female negotiators), but they implicitly or explicitly increase the negotiators’ awareness of gender as a social factor. Gender-based social roles are one form of the gender trigger. Gender roles can influence negotiators by putting restrictions on what is regarded as attractive or appropriate negotiating behaviour (Eagly, 1987, as cited in Riley and McGinn, 2002). Karakowsky and Miller (2006) claim that the role of gender in mixed gender, multi-party negotiations can appear through three critical elements: the proportional representation of the two sexes in the negotiation, their gender roles, and their perceived status. According to Rosabeth Kanter’s theory of proportional representation (as cited in Karakowsky and Miller, 2006) it is the numerical representation of men or women in a group rather than gender roles that dictates the behaviour of men or women. Individuals are in a minority position if they (e.g. women) account for less than 15 per cent of the organisation’s members. According to Kanter, individuals in this numerical minority position are usually seen as representatives of their social categories rather than as individuals. Stereotypes about what is appropriate behaviour for men and women maintain that men are more task-oriented, and focused on distributive and aggressive strategies, while women prefer win/ win negotiations, and have higher lever of socioemotional behaviour. Also, gender differences in behaviour will be affected by perceptions of the status or expertise that group members have. In a mixedgender, multi-party negotiation, individuals (males or females) who are in a numerical minority position, will exercise less influence compared to individuals who are in a numerical majority position. Therefore, negotiators in the minority will be less likely to use competitive tactics. In this research, Karakowsky and Miller reached two important conclusions about mixed-gender multi-party negotiations: 1. Men will exercise greater influence compared to women when the negotiation clearly contains the potential for a distributive outcome, which is a stereotypical male-oriented negotiation task; 2. Women will have greater influence compared to men when the negotiation clearly shows the potential for an integrative outcome (a stereotypical female-oriented task).

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Schroth et al. (2005) explored how gender can influence the intensity to which particular words prompt emotional responses in negotiations. They found out that, although some words and phrases induce emotional responses when used in negotiations, they do not always influence the perception of negotiations in the same way. Words that tell the other person what to do, or are rude normally evoke frustration or anger and lead to the user being perceived as unfair. However, when those words are used, observers, especially women, seem more optimistic that the negotiation will be successfully resolved. Regardless of the fact that women tend to be more relationship oriented in negotiations than men, the language that would seem to hurt a relationship was not seen as negative by women. Although rude comments and being told what to do made both men and women feel anger and frustration, women were more influenced by being told what to do (especially by another woman) than men, but men were more affected by rude comments (especially by other men) than women. Hanappi-Egger and Kauer (2010) analysed the contextual factors which lead to gender switching in bargaining situations. They see bargaining as a gendered process, not biologically determined. Their results showed that bargaining is a masculine construction. “The bargaining parties mainly have masculinely connoted scripts … in their minds when it comes to bargain” (pp. 505-506). For these authors, maleness or masculinity seems to be the key for successful bargaining. According to Amanatullah (2008), advocacy lessens gender differences in negotiations. In her empirical study self-advocating female negotiators agreed to lower salaries than men and other-advocating women, and they also used less competing conflict resolution styles than men, while in conditions of other-advocacy women and men used competing styles equally. According to this author, women’s timid behaviour is a rational reaction to avoid social costs that are provoked by women in self-advocating negotiations, which does not mean that women are unable or unmotivated to negotiate effectively. When these costs are removed, i.e. when negotiators represent somebody else, women behave and perform similarly to men. RESEARCH Based on our literature review, we investigated five specific hypotheses:

Dobrijević G.  The effect of gender on negotiation behaviour

H1. H2.

Men focus on winning more than women. Women focus more on relationship with the other side than men. H3a. Women negotiators use more cooperative strategies and tactics than men. H3b. Women negotiators are more open and sincere in disclosing information H4. Women negotiators are more sensitive to the age and gender of the opposing party. Methodology After reviewing the contemporary literature, the theoretical model was constructed and the differences were hypothesized. Data were collected via a questionnaire distributed by e-mail to 200 individuals. The questionnaire had fifteen closed-ended questions about various aspects of negotiations: negotiation strategy and planning, goal setting, concession making, influence of age and gender on negotiators, negotiation tactics, and mediation. Likert scale was used to scale responses in the majority of the questions. The data were subsequently analysed using quantitative procedures. Participants We chose a sampling strategy that would capture perceptions from different groups of managers and employees. No sampling frame was available. We used purposive sampling, trying to have participants from private and public sector, from national and international organizations, from Belgrade and the rest of Serbia, both men and women. There were 200 working adults, 104 men and 96 women, from various industries. Limitations The scope and geographical spread are limiting factors of this research which, to a large extent, influenced the limitations of the results obtained. It cannot be used to make generalizations about the entire population, since it is based on a small and unrepresentative number of cases. However, it does help us understand gender differences in negotiations. Results In order to confirm these hypotheses, we crossreferenced the answers to several questions with the respondents’ gender. 47

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H1. Men focus on winning more than women.

Only 1 per cent more men than women consider winning the most important thing in negotiations (figure 1). However, if we consider those who rated winning 1 and 2 (almost 32 per cent men, 27 per cent women), and those who give least importance to winning (4 and 5 – 40 per cent men, almost 49 per cent women), we can see that the overall results show that men value winning more than women.

H2. Women focus more on relationship with the other side than men. This hypothesis is partially confirmed. There is just a little difference between respondents who focus on mutual relationship: 12.5 per cent men and 14.58 women rated relationship 1, 16.35 per cent men and 18.75 women rated relationship 2. Also, to the question “Do you care only about your own interests, or also about the interests of others?” more women (12.5 per cent) than men (8.65 per cent) said they care only about their own interests (figure 2)

Figure 1. Focus on winning 1 – very important, 2 – important, 3 – moderately important, 4 – of little importance, 5 – unimportant

Figure 2. Own and others’ interests 48

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H3a. Women negotiators use more cooperative strategies and tactics than men. Men focus on winning more than women, but on the other hand, men also focus more on problem solving than women (see figure 3). Both genders equally rated conflict avoidance, but if we consider respondents who rated conflict avoidance 1 and 2, we get 31.25 per cent women and 13.46 per cent men. Also, 24.04 per cent men rated this feature as the least important, versus 15.62 per cent women (figure 4). As we stated earlier, more women (12 per cent) care only about their own interest than men (8 per cent).

Dobrijević G.  The effect of gender on negotiation behaviour

At the same time, the difference in women and men focusing on mutual relationship is not very significant. The hypothesis that women negotiators use more cooperative strategies and tactics than men was not confirmed. The results have only shown that men are more assertive in negotiations than women because, while women focus more on conflict avoidance and partly on mutual relationship, men are more interested in winning, clearly a competitive strategy (but also on problem solving, which is a cooperative strategy).

Figure 3. Focus on problem solving 1 – very important, 2 – important, 3 – moderately important, 4 – of little importance, 5 – unimportant

Figure 4. Focus on conﬂict avoidance 1 – very important, 2 – important, 3 – moderately important, 4 – of little importance, 5 – unimportant

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H3b. Women negotiators are more open and sincere in disclosing information.

CONCLUSIONS

Literature review has shown that women focus more on personal relationships with the opposing side. That led us to propose that women will be more open and truthful in disclosing information. This hypothesis was disconfirmed. The cross-analysis of gender and sincerity (figure 5) shows that men (33.65 per cent) speak the truth more often than women (26.04 per cent). Although, if we add those who are often honest, we get almost 90 per cent of all the respondents, which is quite promising, talking about the society in general. H4. Women are more sensitive to the age and gender of their opponent.

The main purpose of the study was to investigate gender differences in negotiation in general and to focus on Serbia in the empirical part of the study. Although in the literature there are contradictory opinions on the impact of gender on negotiation styles and strategies, experience has shown that men and women behave differently in negotiations. Men and women think of negotiations in different ways, they communicate differently during negotiations, and similar tactics have different effects in negotiations, depending on the gender that uses them. Probably the initial difference in pay between men and women in many cases comes as a result of the reluctance of women to start negotiations with the employer. Experience has shown that women are generally better in integrative negotiations, while men are more successful in distributive, although there are some pieces of research that disconfirm that opinion. Our empirical research has not confirmed the opinion that women use cooperative tactics more than men. We have reached the conclusion that male negotiators in Serbia are just more assertive than female negotiators. Men focus more on solving problems and winning, and women on conflict avoidance. Contrary to our expectations, more women than men care only about their own interests. Also, men are more sincere in negotiations than women.

The analysis of the results revealed another interesting difference in negotiation: women are more sensitive to the age (52.08 per cent women vs. 44.23 per cent men) and gender (31.24 per cent women vs. 22.11 per cent men) of the other party. That is in accord with the results obtained in a study by Riley Bowles and Flynn (2010). They found that, rather than simply conforming more than men, women adapt their behaviour to the gender of their negotiating counterparts. They become more persistent with male naysayers than with female ones, but doing so they use a different influence style (more low-status) with the male naysayers than with the female naysayers.

Figure 5. Sincerity 50

SJAS 2014  11 (1)  43-52

One explanation that logically presents itself is that, as Serbia is a male-dominated culture, women who want to succeed in the business environment have to be very assertive, and sometimes even ruthless. The analysis of the official EU and UN statistics in the research of Kolin and Čičkarić (2010) shows that women in Serbia are underrepresented in leading positions in governing and decision making in public policy. There are three times fewer women among the legislators, state agencies officials, CEOs, directors, and managers. Our study confirmed that men focus on winning more than women. We also partially confirmed the hypothesis that women focus on relationship more than men. The hypothesis that female negotiators in Serbia are more sensitive to the age and gender of the other party was fully confirmed. Our understanding of gender differences is particularly important in situations where the participants of negotiations are members of both genders, because in such situations the differences between men and women will be most visible. Rather than pretend that differences do not exist, we should understand them better. Of course, gender differences are only one element of individual differences between the negotiators. In some international negotiations, they will be even more prominent in case of societies where gender roles differ greatly. RECOMMENDATIONS FOR FUTURE RESEARCH The results of this study offer interesting opportunities for future research. While this particular study utilized a group of two hundred professionals limited to Serbia, it could be replicated on a sample that would represent the wider region of the Balkans. It would also be interesting to engage in a multiple case comparison of Serbian business negotiators with other cultures, according to Hofstede’s cultural dimensions (Hofstede, 1983; Geert Hofstede website, 2013) and Inglehart’s cultural clusters (Inglehart, 2000). The results could be used in negotiation planning with national and foreign partners, in order to enhance the negotiation outcomes. That would be interesting for negotiators from the Balkans, who, despite their recent differences, are bound to come into closer contact. It would also be of interest to negotiators who come from different cultures, since Serbia, as other countries from the region, is getting more open to the foreign investment.

Dobrijević G.  The effect of gender on negotiation behaviour

REFERENCES

Amanatullah, E.T. (2008). Negotiating gender stereotypes: Other-advocacy reduces social constraints on women in negotiations. Academy Of Management Annual Meeting Proceedings, 1-6. doi: 10.5465/AMBPP.2008.33650222. Babcock, L., & Laschever, S. (2010). Women don’t ask: Negotiation and the gender divide. In R. Lewicki, D.M. Saunder, & B. Barry (Ed.), Negotiation: Readings, exercises and cases (pp. 301-308). Singapore: McGraw-Hill International. Bowles, R.H., & Flynn, F. (2010). Gender and persistence in negotiation: a dyadic perspective. Academy of Management Journal, 53(4), 769-787. doi: 10.5465/AMJ.2010.52814595. Brahnam, S.D., Margavio, T.M., Hignite, M.A., Barrier, T.B., & Chin, J.M. (2005). A gender-based categorization for conflict resolution. Journal of Management Development, 24(3), 197-208. doi: 10.1108/02621710510584026. Brewer, N., Mitchell, P., & Weber, N. (2002). Gender role, organizational status, and conflict management styles. International Journal of Conflict Management, 13(1), 78-94. doi: 10.1108/eb022868. Calhoun, P., & Smith, W.P. (1999). Integrative bargaining: Does gender make a difference? International Journal of Conflict Management, 10(3), 203-224. doi: 10.1108/ eb022824. Canet-Giner, T.M., & Saorín-Iborra, C.M. (2007). The influence of gender role on negotiation development and outcome: A proposal for strategic alliance negotiations. Equal Opportunities International, 26(3), 209-231. doi: 10.1108/02610150710735499. Dobrijević, G. (2009). Faktori koji oblikuju pregovarački stil u poslovanju. Singidunum revija, 9(1), 183-195. (in Serbian). Druckman, D., Rozelle, R., & Zechmeister, K. (1977). Conflict of interest and value dissensus: Two perspectives. In D. Druckman (Ed.), Negotiations: Social psychological perspectives (pp. 105-131). Beverly Hills, CA: Sage. Eagly, A.H., & Johnson, B.T. (1990). Gender and leadership style: A meta-analysis. Psychological Bulletin, 108(2), 233-256. doi: 10.1037/0033-2909.108.2.233. Geert Hofstede website. (2013). Dimensions. Retrieved December 22, 2013, from http://geert-hofstede.com/ dimensions.html. Hanappi-Egger, E., & Kauer, A. (2010). Gendered scripts: Studying hidden assumptions in business contexts. Gender in Management: An International Journal, 25(6), 497-508. doi: 10.1108/17542411011069891. Hofstede, G. (1983). National cultures in four dimensions: A research-based theory of cultural differences among nations. International Studies of Management & Organization, 13(1-2), 46-74. 51

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Inglehart, R. (2000). Culture and Democracy. In S.P. Huntington & L.E. Harrison (Ed.), Culture matters: How values shape human progress (pp. 80-97). New York: Basic Books. Karakowsky, L., & Miller, D.L. (2006). Negotiator style and influence in multi-party negotiations: Exploring the role of gender. Leadership & Organization Development Journal, 27(1), 50-65. doi: 10.1108/01437730610641368. Kolin, M., & Čičkarić, L. (2010). Rodne nejednakosti u zapošljavanju, upravljanju i odlučivanju. Stanovništvo, 48(1), 103-124. (in Serbian). doi: 10.2298/STNV1001103K. Kray, L.J. (2007). Leading through negotiation: Harnessing the power of gender stereotypes. California Management Review, 50(1), 159-173. doi: 10.2307/41166421. Lewicki, R.J., Saunders, D.M., & Barry, B. (2010). Negotiation - readings, exercises and cases. Singapore: McGrawHill. Rao, A., & Schmidt, S.M. (1998). A behavioral perspective on negotiating international alliance. Journal of International Business Studies, 29(4), 665-694. doi: 10.1057/ palgrave.jibs.8490047. Reuvers, M., van Engen, M.L., Vinkenburg, C.J., & Wilson-Evered, E. (2008). Transformational leadership and innovative work behaviour: Exploring the relevance of gender differences. Creativity and Innovation Management, 17(3), 227-244. doi: 10.1111/j.14678691.2008.00487.x. Riley, H., & McGinn, K.L. (2002). When does gender matter in negotiation? Cambridge, Mass: John F. Kennedy School of Government, Harvard University. Retrieved October 15, 2013, from http://research.hks.harvard.edu/ publications/getFile.aspx?Id=51.

Schroth, H.A., Bain-Chekal, J., & Caldwell, D.F. (2005). Sticks and stones may break bones and words can hurt me: Words and phrases that trigger emotions in negotiations and their effects. International Journal of Conflict Management, 16(2), 102-127. doi: 10.1108/ eb022925. Vanderbroeck, P. (2010). The traps that keep women from reaching the top and how to avoid them. Journal of Management Development, 29(9), 764-770. doi: 10.1108/02621711011072478. Vinkenburg, C.J., van Engen, M.L., Eagly, A.H., & Johannesen-Schmidt, M.C. (2011). An exploration of stereotypical beliefs about leadership styles: Is transformational leadership a route to women’s promotion? Leadership Quarterly, 22(1), 10-21. doi: 10.1016/j. leaqua.2010.12.003. Wall, J.A. (1976). Effects of sex and opposing representative’s bargaining orientation on intergroup bargaining. Journal of Personality and Social Psychology, 33(1), 5561. doi: 10.1037/0022-3514.33.1.55. Westbrook, K.W., Arendall, C.S., & Padelford, W.M. (2011). Gender, competitiveness, and unethical negotiation strategies. Gender in Management: An International Journal, 26(4), 289-310. doi: 10.1108/17542411111144300. Wyatt, D. (1999). Negotiation strategies for men and women. Nursing management, 30(1), 22-26. Yeganeh, H., & May, D. (2011). Cultural values and gender gap: A cross-national analysis. Gender in Management: An International Journal, 26(2), 106-121. doi: 10.1108/17542411111116536.

UTICAJ RODA NA PONAŠANJE U PREGOVORIMA Rezime: Pošto muškarci i žene imaju različite uloge u društvu, njihovi pregovarački stilovi i ponašanja se takođe razlikuju. Pregovarački uspeh muškaraca i žena u velikoj meri zavisi od vrste pregovora (saradnički ili suparnički) i rodnih stereotipa koji su izraženi u datom društvu. Uobičajeno je mišljenje da žene više sarađuju, dok se muškarci više nadmeću i agresivniji su. Naše istraživanje u Srbiji pokazalo je malo drugačiju sliku: žene ne koriste više saradničke strategije i taktike nego muškarci. Iako se muškarci fokusiraju na pobedu, takođe se fokusiraju na rešavanje problema, dok se žene fokusiraju na izbegavanje konflikta i, u manjoj meri, na međusobne odnose. Žene su takođe osetljivije na godine i rod pregovarača druge strane. Ali, one su takođe manje iskrene u pregovaranju i fokusiraju se na vlastite interese, umesto da uzimaju u obzir i interese druge strane. Glavna teorijska implikacija ovog istraživanja je da opažene razlike u ponašanju kod pregovarača ženskog roda odslikavaju pritisak da uspeju u društvu u kojem dominiraju muškarci i u kojem su rodni stereotipi dosta izraženi.

Ključne reči: pregovaranje, muškarci, žene, rodne razlike, rodni stereotipi. Received: January 8th, 2014. Correction: January 28th, 2014. Accepted: February 1st, 2014.

SJAS 2014, 11 (1): 53-66 ISSN 2217-8090 UDK: 336.763.3 DOI: 10.5937/sjas11-4766 Original paper/Originalni naučni rad

DURATION AND CONVEXITY OF BONDS Slobodan Čerović1,*, Marina Pepić2, Stanislav Čerović3, Nevena Čerović4 Singidunum University, Department of Tourism and Hospitality, 32 Danijelova Street, Belgrade, Serbia 2 National Bank of Serbia 12 Kralja Petra Street, Belgrade, Serbia 3 Singidunum University, Master’s graduate student 32 Danijelova Street, Belgrade, Serbia 4 University of Belgrade, Faculty of Economics, Master’s student 6 Kamenička Street, Belgrade, Serbia 1

Abstract: The wide impact that interest rate changes have on business performance, the fact that all market participants are, more or less, exposed to interest rate risk, as well as high volatility in interest rates in recent years, make interest rate risk one of the most significant risks. It is impossible to neutralize interest rate risk completely, but it is desirable to reduce it to a minimum. In order to effectively manage it, interest rate risk must first be identified and measured. This paper aims to show the two methods of measuring the interest rate risk - duration and convexity. The concept of duration is a good indicator of changes in the price of bonds but only for small changes in the interest rates. In case of major changes, the duration gives overestimated/underestimated approximation of the bond price, because bond price-yield relationship is not linear. Therefore, when measuring interest rate risk, convexity of bonds must be taken into account. Modified duration and convexity taken together provide the best approximation of the sensitivity of bond prices to changes in interest rates.

INTRODUCTION The wide impact that interest rate changes have on business performance, the fact that all market participants are, to a higher or lesser degree, exposed to interest rate risk (regarding the value and structure of balance and off-balance positions sensitive to interest rate changes, volatility in interest rate, and duration of exposure to risk), as well as high volatility in interest rates during the recent years, make interest rate risk one of the most significant risks.Therefore, it is of the utmost importance to manage this kind of risk adequately. It is difficult to completely neutralize interest rate risk, however, in regard to the great impact that in* E-mail: scerovic@singidunum.ac.rs

Key words: Macaulay, modified, effective, empirical and dollar duration, duration of a portfolio, modified and effective convexity, convexity of a portfolio.

terest rate changes have on business performance, it is necessary to reduce it to a minimum. In order to manage it effectively, exposure to interest rate risk must first be identified and measured. This paper represents an attempt to clarify the two basic methods of measuring interest rate risk – duration and convexity, and to show their advantages, as well as drawbacks. The third method of measuring interest rate risk – value at risk (VaR) is not the subject of this paper. The paper will first explain the notion and characteristics of the concept of duration, then the types of duration, and finally the advantages and limitations of this concept. After that the concept of convexity will be discussed, i.e. characteristics, types, advantages 53

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

and limitations of this concept. Application of the concepts of duration and convexity to portfolio will be clarified as well.

The required yield is a yield generated by market for bonds with fixed maturity date and fixed level of risk. In case of multiple annual coupon payments, bond price will be (Šoškić and Živković, 2006, p. 259):

DURATION A bond is an instrument of indebtedness that obliges the bond issuer (borrower) to repay the lender (creditor) the borrowed assets plus the interest within a certain period of time (Fabozzi, 2000, p. 1). There are coupon and zero-coupon bonds. With coupon bonds a periodic interest (coupon) payment is present. With zero-coupon bonds yield is the difference between the purchase price of a bond and its face value, i.e. its selling price in case it is sold before maturity. The nominal yield is bond yield based on coupons (Šoškić and Živković, 2006, p. 236). Since coupon rate is fixed and not sensitive to market changes, it is not of importance to the investors when making a decision whether a bond investment is worthwhile. Therefore, current yield and yield to maturity are most often used as yield indicators. Current yield is a quotient of the coupon yield for a certain period and the purchase price (Mishkin and Eakins, 2005, p. 258). Current yield is greater than nominal (coupon) yield when the price of a bond is less than nominal, and vice versa, current yield is less than nominal when the price of a bond is greater than nominal. Current yield is sensitive to changes in bond price and therefore a good indicator of whether a bond investment is worthwhile. When reaching long-term decisions yield to maturity of a bond is used for yield calculation. The yield to maturity is the discount rate at which the value of current cash flows from the bond is equal to the price of the bond (Šoškić and Živković, 2006, p. 237). At the moment of the flotation of a bond yield to maturity is equal to the market interest rate. If the market interest rate changes during a period of time, the bond price will change as well. The price of a coupon bond is equal to (Šoškić and Živković, 2006, p. 259):

Ct M + t (1 + i)n t =1 (1 + i) n

= P ∑

(1)

where P is – price of a bond, C – coupon value, M – nominal bond value, n – number of years to maturity, i – required yield or market interest rate. 54

Ct M m m = P ∑ + t mn t =1  i   i  1 +  1 +   m  m n

(2)

where m is – number of coupon payments in a year. With changes in market interest rates the required yield for the bond changes as well. When the coupon rate is equal to the required yield, the bond price will be equal to the principal. When the coupon rate is greater than the required yield, the bond price will be greater than the nominal value and this bond will be selling at a premium. When the coupon rate is less than the required yield, the bond price will be less than the nominal value and this bond will be selling at a discount. Regarding zero-coupon bonds, as we said before, yield is the difference between purchase bond price and its nominal value, i.e. selling price if sold prior to maturity. The zero-coupon bond price is equal to the present value of the sum received on the maturity date and it is calculated according to the following formula (Šoškić and Živković, 2006, p. 260):

M (1 + i)n

(3)

Not only is the overall cash flow that bond rejects important for investment decision, but also the period in which it happens. Maturity of the bond gives information only on the date of the final payment, but not on the size and date of coupon payments prior to the last payment of coupon and principal. The longer the period to maturity and the higher the coupon rate and yield to maturity, the more important coupon payments become when compared to payments upon the maturity of the bond. Maturity of the bond, therefore, is not an adequate indicator of the time required to make investment in bonds worthwhile. Thus, the concept of bond duration has been developed. Duration is a measure of interest rate risk of bonds and it is used to determine the average period of ma-

SJAS 2014  11 (1)  53-66

turity of the bond. The concept of duration measures price sensitivity of bonds or bond portfolios to the changes in interest rates (Choudhry, 2005, p. 32). Bonds with longer duration have higher changes in price than bonds with shorter duration, and that represents a greater risk. Bond duration is an approximation of the percentage change in bond price regarding the change in interest rate of 100 basis points. It is calculated according to the formula (Fabozzi, 1996, p. 49):

P− + P+ 2P( ∆i)

(4)

where D is – duration of bond, P – initial bond price, Δi – change in yield, P+ - estimated bond value in case of yield rise for Δi, P- - estimated bond value in case of yield drop for Δi. Values for P+ and P- are obtained using the model for bond valuation. It is important to stress that the parallel shift of the yield curve is expected, that is, the yield change Δi is the same for all maturities. Let's suppose that the initial price of 9% 20 years bond (Fabozzi, 1996, p. 49) is 134.6722, and that the current yield is 6%. If the yield, for instance, is decreased by 20 basis points (from 6% to 5.8%), the bond price will increase to 137.5888. If the yield is increased by 20 basis points (from 6% to 6.2%), the bond prices will fall to 131.8439. Duration of the bonds in this case, according to the formula (4), will be 10.66. This means that the bond price would change by approximately 10.66% for a 100 basis points yield shift. Approximate percentage change in bond price for given market rate change and given duration is calculated in the following way (Fabozzi, 2007, p. 170): Approximate percentage = -D*(Δi)*100 change in price

(5)

Negative symbol in front of duration D indicates that price and yield stand in inverse relation. In the above example (9% 20-year bond with duration of 10.66 and price of 134.6722) approximate percentage change in price for a 10 basis points yield change (Δi=0.001) would be: -10.66*0,001*100=-1.066%. So, if yield rose by 10 basis points, bond price would decline by 1,066%. Approximation of price change is a fairly reliable indicator for lesser changes in

Čerović S. et al.  Duration and convexity of bonds

market rates. Nevertheless, for greater changes in interest rates, the results are not that good. Namely, because of the convexity of the price/yield curve (to be elaborated upon further on), estimated change in bond value for greater rate changes will result in underestimated/overestimated bond value. Duration and yield to maturity Relation between yield to maturity and duration is shown by the following formula (La Grandwille, 2001, p. 81):

dD −1 = − (1 + i ) S di

(6)

where S is dispersion measured by a variance of the bond payment number. Because of ‘-‘ symbol dD/ di will always be negative, which means that there is an inverse relation between duration and yield, i.e. duration drops with the rise of yield to maturity and vice versa. This of course applies to coupon bonds. With zero-coupon bonds duration is always equal to maturity because the whole sum is paid upon maturity (or upon possible selling of the bond beforehand). Macaulay duration The concept of duration has been present in analysis and portfolio management for several decades and a few modifications have been developed through time. The first concept originated some 70 years ago and it was named Macaulay duration after its author – Frederick Macaulay. He showed that the number of years to bond maturity is not adequate for measuring time component of the debt, and that the bond duration is a far better measure since it takes into account the payment of principal in the end, as well as the coupon payments. The Macaulay duration is a weighted arithmetic mean of cash flow maturity which the bond rejects, where participation of the current value of cash flows in the bond price is used as weight, i.e. weight for every cash flow is calculated by dividing the current value of cash flow by the bond price, in other words, Macaulay duration is calculated using the following formula (Choudhry, 2005, p. 33): 55

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

tCt

∑

t =1

∑

tCt

(1 + i ) =

t =t 1=t 1

(1 + i )

(7)= D

∑

t =1

where P is – bond price, t – period during which payment of coupon or principal occurs, Ct – value of cash flow in period t, i – yield to maturity of bond. This equation’s numerator contains the current value of all cash flows valuated according to the period of payment maturity, while denominator contains the bond price after the model of current value. Thus by applying the formula (1) we get the following formula:

tCt

∑

(1 + i )

(8)

(1 + i )

Bond A

Bond B

Nominal value

$1000

Maturity

10 years

Coupon rate

Bond A Year

Cashﬂow

PV at 8%

(1)

(2)

(3)

(4)

(5)

(6)

0.9259

37.04

0.0506

0.8573

34.29

0.0469

0.0938

0.7938

31.75

0.0434

0.1302

0.7350

29.40

0.0402

0.1608

0.6806

27.22

0.0372

0.1860

0.6302

25.21

0.0345

0.2070

0.5835

23.34

0.0319

0.2233

0.5403

21.61

0.0295

0.2360

0.5002

20.01

0.0274

0.2466

1040

0.4632

481.73

0.6585

6.5850

731.58

1.0000

8.1193

Total

PV of yheﬂow

PV as % of the price

1*5

Duration = 8.12 years Bond B 1

0.9259

74.07

0.0741

0.8573

68.59

0.0686

0.1372

0.7938

63.50

0.0635

0.1906

0.7350

58.80

0.0588

0.1906

0.6806

54.44

0.0544

0.2720

0.6302

50.42

0.0504

0.3024

0.5835

46.68

0.0467

0.3269

0.5403

43.22

0.0432

0.3456

0.5002

40.02

0.0400

0.3600

1080

0.4632

500.26

0.5003

5.0030

1000.00

1.0000

7.2470

Total Duration = 7.25 years Source: Reilly and Brown (2003, p. 769)

SJAS 2014  11 (1)  53-66

There are some characteristics of Macaulay duration. Firstly, Macaulay duration of a coupon bond is always less than maturity, since the concept of duration takes coupon payments into consideration; secondly, there is an inverse relation between how high the coupon rate is and the duration. Bonds with higher coupon payments have shorter duration because more cash flows arrive beforehand as coupon payments. Zero-coupon, i.e. strictly discount bonds have duration that equals maturity; thirdly, there is a positive relation between maturity and Macauley duration, where the duration rises according to decremental rate at the rise in maturity. This indicates that the bond with a longer maturity will almost always have greater duration. The relation is not direct because as the maturity grows, the present value of principal drops; fourthly, there is an inverse relation between yield to maturity and duration; fifthly, callability of a bond can influence the duration significantly, since the callability of bond changes the cash flow of bond and thus the duration as well. Modified duration Modified duration shows approximate percentage price change of a bond for the change in yield of 100 basis points (Choudhry, 2005, p. 37). The assumption is that the cash flow stays unchanged with the change in yield. Modified duration is calculated in the following way (Fabozzi, 1996, p. 53):

Modiﬁed = duration

Macauley duration

(9)

(1 + (yield to maturity / number of coupon periods in a year))

For example, a bond with Macaulay duration of 10 years, yield to maturity of 8% and semi-annual coupon payments would have the following modified duration:

0.08   D = 10 /  1 +  = 10 / 1.04 = 9.62 2   The alteration in price of non-callable bonds, for small yield changes, will be changing in proportion to modified duration. More precisely, predicted percentage of bond price change is equal to yield change

Čerović S. et al.  Duration and convexity of bonds

multiplied by modified duration (Reilly and Brown, 2003, p. 771):

∆P −Dmod * ∆i * 100 = P

(10)

where ΔP is – bond price change, P – initial bond price, -Dmod – modified duration, Δi – yield change in basis points. If we want to estimate the price change of a bond with Macaulay duration of 10 years, yield to maturity of 8% and semi-annual coupon payments for a 50 basis points change in yield (say, from 10.0% to 9.5%), the first step would be to calculate the modified duration, and than projected percentage change in bond price:

Dmod =10 / ( 1 + 0.8 / 2 ) =9.62 % ∆P =−9.62* ( −0.50) =4.81 Thus, the bond price will change by approximately 4.81% as a result of a 50 basis points yield decrease. If the initial price was $ 1000, after the change in yield the price would be 1048.1 ($ 1000 * 1.0481). Starting with the formula (10) we can reach formula for new price of a bond:

  ∆i  = New price  D*  / 100 + 1 * P 100   

(11)

Modified duration is always negative for noncallable bonds because of the inverse relation between yield change and bond price. We should, however, bear in mind that this takes into account only the approximation of price change, and that valid results for price change can only be obtained for very small changes in yield. The Macauley and modified duration are quite significant when considering volatility and interest sensitivity of a bond. However, it is very important to refer to significant limitations of these two concepts once more. Firstly, Macauley and modified duration give a good approximation only for small changes in yield. Two bonds with the same duration can have different change in price for major yield changes, depending on bond convexity. 57

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

Secondly, it is quite difficult to assess interest sensitivity of a bond portfolio in case of nonparallel shift of the yield curve. Duration of portfolio is calculated as weighted average of duration of the bonds from portfolio. Problem is non-existent as long as the yield curve shift is parallel. However, if the yield curve shift is not parallel, the question is which change in yield to take – short-termed, medium-termed or longtermed yield curve. Two portfolios that shared the same duration in the beginning can have different durations in the end, depending on how the yield curve shifted. The third drawback is related to the fact that these two concepts assume a bond without embedded option. The duration of a bond with embedded option would be somewhere between duration to maturity and duration to the first call, and the specific value depends on relation between current market rates and coupon rate. In order to overcome these drawbacks a new way of assessing the duration of a bond which takes into account the aforementioned cases has been developed.

(10 basis points) up or down and use of a model to determine expected market prices of a bond (P+and P-) for new yields. Suppose that bond with the following characteristics does not have an embedded option (Reilly and Brown, 2003, pp. 783-784):

Effective duration

As it is a bond without option, effective duration will be the same as modified.

Effective duration is a direct measure of the interest sensitivity of a bond in cases where it is possible to use valuation models for establishing price. The advantage of this concept is the possibility for duration to be longer than maturity, or to be negative, which can also be applied to the bonds with embedded option. Namely, effective convexity allows for the cash flow of a bond to be liable to change due to yield change when the bond with embedded option is in question. With small changes in market rates, and with bonds without embedded option, effective duration is equal to modified duration for small yield changes (Reilly and Brown, 2003, p. 783):

Deff =

P− + P+ 2PS

(12)

where P- is – estimated bond price after drop in interest rate, P+ - estimated bond price after rise of interest rates, P – current price of a bond, i.e. the price before yield change, and S – expected shift in futures structure. The formula assumes small changes in yield 58

Nominal value Coupon rate Maturity

$1000 6% 8 years

The initial yield to maturity

The initial price

100

and that the change in the yield is 10 basis points. Then you have the following: P- (for 5.90%) would be equal to 100.4276, and P+ (for 6.10%) 99.5746, while the effective duration would be: = Deff

P− − P+ 100.4276 − 99.5746 = = 4.26 2PS 2* 100* 0.001

Dmod = 4.39 / (1 +0.06 / 2) = 4.39 / 1.03 = 4.26

However, in the case of callable bond, the situation would be different. Let us say that the bond is callable after 3 years at 106. The use of the model to determine the bond price for 4% yield (P would be 108.2408) would give the following: for yield 3.90% (decrease of 10 basis points) P-would be 108.5563, and for 4.10% P+ 107.9232, while the effective duration would be: = Deff

P− − P+ 108.5563 − 107.9232 = = 2.92 2PS 2* 108.2408* 0.001

As expected, regarding that the value of the callable bond rises with the drop in yield, duration is shorter than the duration of the bond without embedded option. The effective duration of the callable bond for higher yields will be equal to the duration of the bond without embedded option because the value of the option is close to zero.

SJAS 2014  11 (1)  53-66

In order to better understand the influence of callability on the duration of bonds, it is necessary to consider factors which determine the price of the bond with embedded option. Call or put option can be embedded on the bond. The call option gives certain rights to the issuer, and the put option to the buyer (holder) of the bond. Callable bond is a combination of a non-callable bond and call option which ensures the certain right to the issuer, and thus has a negative influence on the price. Hence, purchasing a callable bond is the same as purchasing a non-callable bond + selling a call option, and the price is equal (Reilly and Brown, 2003, p. 778): Callable bond price

non-callable bond price

–

call option price

(13)

Everything that increases the value of call option will decrease the value of the callable bond. When interest rates drop, the non-callable bond price increases, as well as and the price of call option, so the change in the callable bond price will depend on which of these two prices changes faster. If, due to drop in interest rates, the value of call option rises faster than the value of non-callable bond, the value of callable bond will drop (negative duration), which is opposite to the conventionally inverse relation between change in yield and bond price. The effective duration can be negative, contrary to the modified duration. The duration of the callable bond will be somewhere between the duration to maturity and the duration to the first call, depending on the probability of the issuer utilizing his right from the option and calling the bond before maturity date, which in its turn depends on the level of interest rates in relation to coupon rates. The duration of a bond with embedded option is equal to (Reilly and Brown, 2003, p. 780): Duration of bond with embedded option

duration of non-callable bond

–

duration of call option

Čerović S. et al.  Duration and convexity of bonds

tive to shift in interest rates (e.g. mortgage ones), the duration is negative, that is, their price drops when interest rates drop. When it comes to the bonds with the possibility of a buyer charging them before maturity date, i.e. to the bonds with put option, there is positive influence of option on the bond value which rises with the rise in interest rates. This means that when interest rates rise, the price of this kind of bond does not drop as much as the price of the bond without embedded option, but when the rates drop, the price of the bond with put option shifts similar to the price of bond without embedded option (since the option value is close to zero). Therefore, the value of the bond with possibility of being charged beforehand is equal to the value of the bond without embedded option augmented by the put option value. The effective duration, as we have already mentioned, can be longer than maturity and that is the case with some kinds of assets where the interest sensitivity is extremely high. The effective duration assumes the appliance of interest models and models for determining bond prices that take into account the change in cash flows with the change in yield. Be that as it may, the problem occurs while measuring interest sensitivity for assets where it is impossible to predict the change in price based on change in yield. For example, the influence of interest rates change on stocks can be overcome by influence of rate of growth which cannot be predicted. The concept of empirical duration has been developed with the aim of securing some approximation of interest sensitivity of a bond even under these conditions. Empirical duration Empirical duration represents the real percentage change in price of assets for the given change in yield during a certain period of time (Reilly and Brown, 2003, p. 788):

(14)

At a high level of interest rates, the change in yield will not have great influence on the price of option. As a result, the duration of option will be close to zero, and the duration of callable bond will be nearly equal to the duration of non-callable bond and other way round. With options that are extremely sensi-

% ∆P = - Dmod * ∆i

(15)

Where Δi is change of interest rate in basis points divided by 100. We start from the assumption that Dmod and Δi are already known. The equation can also be written in the following way: 59

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

−Dmod

% ∆P = ∆i

(16)

However, Dmodis not a modified duration any more, but the empirical one, i.e.:

Demp = −

% ∆P ∆i

(17)

For example, if the yield is decreased by 150 basis points and the bond price is increased by 10%, the empirical duration would be: % ∆P 10 − = − = Demp = 6.67 ∆i −150 / 100

Thus, we can say that the empirical duration is an approximation for percentage change in price when the interest rate changes for 100 basis points.

ration, according to the following formula (Fabozzi, 1996, p. 54): W 1D 1 + W 2D 2 + W 3D 3 + ... + W nD n

(19)

Where w1,2…n are weights which stand for a share of market value of a bond for a total value of portfolio w1…wn, and n is number of bonds in portfolio. Another way of calculating portfolio duration is by using the absolute change in price of every bond in portfolio. The percentage price change is obtained by dividing the total change in price by the initial market value of portfolio. The portfolio duration cannot be longer than the longest duration of a single bond in portfolio, but it also cannot be shorter than the shortest duration of a single bond in portfolio. Therefore, the duration of portfolio is always between the shortest and the longest duration of individual bonds in portfolio. Advantages and drawbacks of the concept of duration

Dollar duration If two bonds have the same modified duration, it does not mean that the change in price for the absolute sum of these bonds will be the same. Two bonds, A and B, have the same duration of 10, but the price of bond A is 100 and of bond B is 80. If yield is changed by 100 basis points, the absolute change in the price of the bond A will be $10 (10*100*0.01), and for the bonds B $8 (10*0.01*80).The absolute change in bond price due to change in yield is calculated according to the following formula (Fabozzi, 1996, p. 50): Price change = - Dmod* price in $ * change of rate

(18)

Change in bond price obtained from this equation is called dollar duration. Accordingly, the dollar duration shows the absolute change in bond price due to rate change of 100 basis points. PORTFOLIO DURATION There are two ways for calculating portfolio duration. The first one is a result of weighted average du60

The concept of duration is a good indicator of percentage change in price only for small changes in yield. With large changes in yield, the duration is a wrong measure since it shows overestimated/ underestimated approximation of the price change in relation to real change in bond price. For small changes in yield, the percentage change in price is almost the same, regardless of the rise or drop in yield, while for the great changes in yield the percentage change in price is not the same when it comes to rise or drop in yield. Chart 1 displays the relation between bond price and yield. Duration is linearization of convexity. If change in yield occurs, the tangent helps us estimate a new price. If a vertical line is drawn anywhere on the horizontal line of yield, the difference between X-axis and tangent line shows approximate change in price for the initial yield y*. For small changes in yield the tangent is close to real priceyield relation. However, the more the current yield changes in relation to the initial yield, the greater is the duration based price approximation error. The reason for this is the convex shape of the price-yield curve. The greater the convexity, the less accurate the use of concept of duration only will be.

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

Chart 1: Change in price Source: Fabozzi (2007, p. 173)

curve is not a straight but a curved line. Convexity is a measure of the curvature of the price-yield curve (Hull, 2009, p. 90).

CONVEXITY Concept and characteristics Bearing in mind the price-yield relation, modified duration may be defined as the percentage change in price in response to nominal change in yield (Reilly and Brown, 2003, p. 774):

Dmod =

dP / di P

(20)

where dP/di is the tangent to the price-yield curve for the given yield rate. As we can see from Chart 1, for small changes in yield the tangent provides a good reflection of the changes in bond price. However, for major changes in yield, the tangent reveals a lower bond price than the price-yield curve. Such erroneous estimation occurs because modified duration is a linear approximation of a non-linear price-yield relation. Consequently, all the approximations based exclusively on modified duration underestimate the increase in price caused by a decrease in yield and overestimate the decrease in price that follows an increase in yield. Chart 1 also shows that price changes are not symmetrical when it comes to yield increasing and decreasing. The error in estimation is greater when interest rates drop than when they rise, for when yield drops, prices rise at an incremental rate, whereas when yield rises, prices drop at a decremental rate. So, the price-yield

Modified convexity Since modified duration is a measure of the curve slope for the given yield, convexity indicates a change in duration. Mathematically, convexity is the second derivative of the price-yield function per yield divided by price, that is, the percentage change of dP/di for the given change in yield (Reilly and Brown, 2003, p. 776):

Convexity =

d 2 P / di2 P

(21)

The price of a bond equals the present value of dicounted cash flows, so the price can easily be calculated at any given moment if the coupon rate, maturity and yield to maturity are known. The priceyield curve displays a set of prices for specific bonds (in terms of maturity and coupon rate) at a certain point in time. The convex price-yield relation will differ with bonds that have different cash flows, and/or maturity and coupon rate. For example, the price-yield relation for bonds having shorter maturity period and a high coupon rate will be an almost straight line because the price does not change that much with the change in 61

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

yield. Conversely, the price-yield relation for bonds with a longer maturity period and a low coupon rate will be a convex line. Between two bonds of the same duration but different convexity, it would be logical to choose the one with higher convexity, because it is bound to have a better price whether the yield is rising (the price of the bond will decrease less) or falling (the price of the bond will increase more). Convexity measures the deviation of the priceyield curve from its linear approximation. For noncallable bonds convexity is always positive, meaning that the price-yield curve is located above the line which is indicator for modified duration and the tangent to the curve.

Convexity varies for different sections of the price-yield curve, just as modified duration varies for different points on the price-yield curve because of the slope allternations. Maturity and coupon rate stay unchanged, and it is the yield to maturity rate (which changes) that indicates the section of the price-yield curve in question. Convexity may also be calculated by the following formula (Fabozzi, 2007, p. 180):

Convexity =

P+ + P− − 2P 2P ( ∆i )

(24)

Suppose that the current price of a 6.7% 5-year bonds is 102.7509, and that increase in yield by 10 basis points result in decline in the price to 102.3191, and that yield drop of 10 basis points result in bond price increase to 103.1849 (Fabozzi, 2005, pp. 215216). Effective convexity according to the formula (24) would be:

Calculation of convexity Convexity is calculated in the following manner (Reilly and Brown, 2003, p. 777):

d 2 P / di2 = P (22) 2 103.1849 + 102.3191 − 2*102.7509 d P / di2 = Convexity = 21.41 = 102.7509*(0.001)2 Current value of chas flows

Convexity =

d 2P di 2

1 (1 + i) 2

 n CFt  (t 2 + t )  t∑  =1 (1 + i) 

The effect of convexity on price is calculated in the following manner (Reilly and Brown, 2003, p. 778):

(23)

Change in price = 1/2 * price * convexity * (Δ of yield)2 due to convexity

Calculating the convexity (Reilly and Brown, 2003, p. 777) of the 12% 3-year bond with the yield to maturity of 9% per annum would be as follows: 1

Year

PV 9%

PV CF

t +t

4*5

120

0.9174

110.09

220.18

120

0.8417

101.00

606.00

120

0.7722

92.66

1111.92

1000

0.7722

772.20

9266.40

P=1075.95 1/(1+i)2 = 1/(09) 2 = 0.84 11204.50 * 0.84 = 9411.78

Convexity =

d 2 P / di 2 9411.78 = = 8.75 P 1075.95

(25)

11204.50

be:

In the previous example, the price change would ½ * 102.7509 * 21.41 * (0.001) 2 = 0.0011

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

Attributes of convexity Attribute 1: As the required yield increases, convexity of a bond drops and vice versa, as the required yield drops, the convexity of a bond rises. The slope of the tangent becomes less sharp as the required yield increases. A straighter tangent indicates a lower modified duration as the required yield increases. Conversely, the tangent becomes steeper with the decrease of the required yield, and the modified duration rises. This leads to the conclusion that convexity actually measures the rate of change of monetary duration of a bond as a result of the market yield change. Atributte 2: For the given yield and maturity, the lower the coupon rate the higher the convexity of a bond. Attribute 3: For the given yield and modified duration, the lower the coupon rate the lower the convexity. Zero-coupon bonds have the lowest convexity for the given modified duration. Atributte 4: Convexity of a bond increases at an incremental rate with the increase in a bond duration. The implication hereof is that if an investor trades this bond for another with a duration twice as long, the convexity shall more than double. Modified convexity assumes that the cash flow rejected by a bond does not change with the change of interest rates. Moreover, modified convexity is not a reliable indicator in the case of bonds with embedded option. In order to overcome these drawbacks, a concept of effective convexity has been developed. Effective convexity Effective convexity assumes that cash flow varies depending on the change in yield. It is calculated by the following formula (Reilly and Brown, 2003, p. 783):

Convexityeff =

P+ + P− − 2P P ( ∆i )

(26)

where P- is - estimated bond price after fall of interest rates, P+ - estimated bond price after rise of interest rates, P – current bond price, i.e. price before change of interest rates, and Δi – anticipated change in yield. So the formula is the same as for

modified convexity. There is a difference, however. Namely, valuation models used for calculating bond prices affected by a change in yield must here take into account that cash flow varies with the change of interest rates, i.e. that in bonds with embedded option cash flows vary considerably depending on the level of interest rates. Convexity of a bond with a call option Suppose that the 6.25% 5-year bond with current price 99.8030 is callable between 2nd and 5th year and that increase in yield by 10 basis points result in decline in the price to 99.4932, and that yield drop of 10 basis points result in bond price increase to 100.1086 (Fabozzi, 2005, p. 215, p. 219). Effective convexity according to the formula (26) would be: Convexity =

100.1086 + 99.4932 − 2*99.8030 = −42.1 99.8030*(0.001)2

Bonds without embedded option (noncallable) have positive convexity, because when yield drops, the bond price rises at an incremental rate. On the other hand, with bonds that have a call option, when the interest rates fall, the bond price rises at a decremental rate, up to the point where all changes halt. Such behaviour of the price-yield curve in the face of yield changes is called negative convexity and it is one of the risks accompanying a callable bond. Starting from the yield y* (Chart 1), the rise in interest rates results in the drop of the value of the call option, for when interest rates exceed the coupon rate by large, the probability of the issuer resorting to his option right is small, so the option’s value diminishes as well. In this case the price of the callable bond is similar to the price of the noncallable bond. In the opposite case, the drop of interest rate below y* increases the probability of the issuer using the right from the option and redeeming the bond, thus increasing the value of the option itself. As a result, the price of a callable bond differs from the price of a noncallable bond, where the increase in price of the callable bond is initially slower than the one of the noncallable bond, and then it stops. Convexity of a bond with a put option Suppose that the 5.75% 5-year bond with the current price of 100.1089 is putable between 2nd and 5th year and that 10 basis points increase in 63

SJAS 2014  11 (1)  53-66

Čerović S. et al.  Duration and convexity of bonds

yield result in decline in the bond price to 99.8424, while drop in yield by 10 basis points result in price increase to 100.3819 (Fabozzi, 2005, p. 215, p. 220). Effective convexity according to the formula (26) would be:

Duration and convexity

Accordingly, there are two factors influencing the bond price changes in response to the change in yield: modified duration of a bond and its convexity. A relative influence of any of these factors on the change in price shall depend on the bond properties 100.3819 + 99.8424 − 2*100.1089 Convexity = 65 2 (maturity and coupon rate) and the amplitude of the 100.1089*(0.001) yield change. Modified duration may be useful in determining the approximate percentage bond price Effective convexity of a bond with a put option change for a given change in yield, but the informaremains positive for all interest rate changes. Howtion is valid only for minor changes in yield. In case ever, the convexity of such a bond is reduced as the of major changes in yield and/or bonds with large interest rates rise. This is due to the fact that the modified convexity, the impact of convexity must also probability of using the put option is low when the be considered, while otherwise the estimated price market rates are lower than the coupon rate, so the change would be overestimated or underestimated. price of such a bond changes in the same manner as The price change due to duration of the 12% the price of an ordinary bond, and vice versa. Since 18-years bond (Reilly and Brown, 2003, p. 779) with the price-yield curve must be quickly adjusted to the yield to maturity of 8%, price of 126.50, modified this change, the convexity of the bond with a put duration of 8.38, and the convexity of 107.70 would option is large. be equal to the modified duration multiplied by the change in yield and divided by 100 (formula 1.10), and the price ∑(modiﬁed duration of every investment * value of change due to convexity would every investment) be equal to a half of the price Modiﬁed duration = multiplied by convexity and the value of a portfolio square of the of yield change (formula 1.25). If the decline in ∑ (convexity of every investment * value of every yield is first 100, and then 300 investment) basis points, we would get the Convexity = following: value of a portfolio

Convexity of a portfolio Convexity of a portfoilio is acquired by first calculating the convexity of each bond in the portfolio and then calculating the weighted average convexity of all the bonds in a portfolio, where weights represent the share of the bond‘s value in the total value of the portfolio. If the fall in interest rates is foreseen, bonds with greater convexity will generate greater income. In the same way, the loss incurred because of unforeseen increase in interest rates is smaller with a greater convexity bond. Hence, it is insignificant whether interest rates fall or rise, the convexity nonetheless enhances the performances of the portfolio. Subsequently, if the greater volatility of interest rates is predicted, the convexity of the portfolio should be improved. 64

A: Yield change: -100 basis points Change - duration: -8.38 * (-100 / 100) = 8.38% 8.38% * 126.50 = 10.60 Change - convexity: ½ * 126.50 * 107.70 * 0.012 = 0.68 The combined eﬀect: 126.50 +10.60 +0.68 = B: Yield change: -300 basis points Change - duration: -8.38 + (-300 / 100) = 25.14 25.14% * 31.80 = 126.50 Change – convexity: ½ * 126.50 * 107.70 * 0.032 = 6.11 The combined eﬀect: 126.50 +31.80 +6.11 = 164.41

This impact of convexity will be smaller if the change in yield is high but the convexity of the bond is low (due to the high coupon rates or short maturity), because the price-yield curve is almost a horizontal line in that case. Modified duration and convexity considered together provide the best approximation of the sensitivity of the bond price to the interest

SJAS 2014  11 (1)  53-66

rates change. They have a disadvantage, however, of assuming the parallel shifts in yield curve. With increase in duration, convexity grows at an incremental rate. The larger the share of convexity, the less precise the percentage price change provided by duration. This is most starkly visible with considerable changes in yield. Also, duration and convexity are used for bonds with low credit risk. They are not to be heavily relied upon when dealing with a higher credit risk bonds, because neither duration nor convexity are good indicators of the sensitivity of the bond price to the interest rate change. In 1995 Barber J.R. arrived at the approximation of the bond price sensitivity based on duration and convexity. The bond price equals:

CFt t t = 1 (1 + y) n

P=∑

(27)

The expanded Taylor‘s line would be: ΔP/P 0 = -DΔy+1/2(C-D 2)(Δy) 2

(28)

where D and C represent modified duration and convexity respectively, and Δy is the change in yield. The previous formula yields erroneous results for major changes in yield. Far better results are obtained by using a logarithmic approximation: ΔP/P 0 = exp[-DΔy+1/2(C-D 2)(Δy) 2]-1

(29)

The logarithmic approximation provides more accurate results in the case of large changes in yield. The formula (27) provides actual bond prices. The other two formulas (28 and 1.29) give approximate bond prices. The Barber study revealed that with lesser interest rate disturbances (up to 100 base points), both approximative formulas give results similar to the one from the first formula. However, with greater changes in interest rates, e.g. 300 base points, the logarithmic approximation of price is more precise than the conventional approximation models. RESUME Not only is the overall cash flow that bond rejects important for investment decision, but also the period

Čerović S. et al.  Duration and convexity of bonds

in which it happens. Maturity of the bond gives information only on the date of the final payment, but not on the size and date of coupon payments prior to the last payment of coupon and principal. The longer the period to maturity, the higher the coupon rate and yield to maturity, the more important coupon payments are. Maturity of the bond, therefore, is not an adequate indicator of the time required to pay off investment in bonds. Due to this, the concept of bond duration has been developed. Duration is a measure of interest rate risk of bonds and it is used to determine the average period of maturity of the bond. Duration measures price sensitivity of bonds or bond portfolios on the changes in interest rates. There are different types of duration. Macaulay and modified duration give a good approximation of the interest sensitivity of bonds butonly for small changes in yield, and, unfortunately, cannot be used in the case of major changes in yield, and in the case of bonds with embedded option. Hereof, effective duration has been developed. The advantage of this concept is that it allows duration to be longer than maturity, and to be negative, so it can be used for bonds with an embedded option while it allows the bond cash flow to change due to changes in yield. However, as the effective duration involves the use of interest models, the problem arises when measuring the interest sensitivity of assets for which it is not possible to give precise predictions for the price based on the change in yields. In order to provide an assessment of the sensitivity of bond in these cases, the concept of empirical duration has been developed. Duration is the approximate percentage change in bond price for a change in interest rates. However, the information is relevant only for small changes in yield. In the case of a major change in yield, estimates based only on modified duration underestimated price increase caused by the decrease of yield and overestimate the drop in price due to the increase in yields. This misperception arises because the modified duration is the linear estimation of non-linear price-yield relation. Thus, the price-yield curve is not straight but curved line. Convexity measures deviation of the price-yield curve from its linear approximation. Like duration, convexity also suffers from certain drawbacks. Modified convexity assumes that the cash flow of a bond does not change with a change in interest rates, so it is inadequate for the bonds with embedded option. To overcome these deficiencies, effective convexity has been developed. Effective convexity assumes that the cash flow changes with the change in yield. 65

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Čerović S. et al.  Duration and convexity of bonds

Two factors determine the bond price changes due to changes in interest rates: the modified duration of the bond and its convexity. The relative significance of these factors depends on the characteristics of a bond (maturity, coupon rate) and the size of the interest rate change. The best approximation of the sensitivity of a bond to interest rate changes is obtained by a combination of modified duration and convexity. However, it should be noted that the approximation of bond price changes due to changes in interest rates is based on the assumption that the yield curve shifts are parallel. REFERENCES Barber, J.R. (1995). A note on approximating bond price sensitivity using duration and convexity. The Journal of Fixed Income, 4(4), 95-98. doi: 10.3905/jfi.1995.408123. Choudhry, M. (2005). Fixed-income securities and derivatives handbook: Analysis and valuation. Princeton, N.J: Bloomberg Press. Fabozzi, F.J. (1996). Measuring and controlling interest rate risk. New Hope, PA: Frank J. Fabozzi Associates.

Fabozzi, F.J. (2000). Bond markets, analysis and strategies. Upper Saddle River, N.J: Prentice Hall. Fabozzi, F.J., & Mann, S.V. (2005). The handbook of fixed income securities. New York: McGraw-Hill. Fabozzi, F.J. (2007). Fixed income analysis. Hoboken, N.J: Wiley. Hull, J. (2009). Options, futures and other derivatives. Upper Saddle River, N.J: Prentice Hall. La Grandville, Olivier de. (2001). Bond pricing and portfolio analysis: Protecting investors in the long run. Cambridge, MA: MIT Press. Mishkin, F.S., & Eakins, S.G. (2005). Financial markets and institutions. Boston: Addison Wesley. Reilly, F.K., & Brown, K.C. (2003). Investment analysis and portfolio management. Mason, OH: South-Western/ Thomson Learning. Steiner, R. (1998). Mastering financial calculations: A step by step guide to the mathematics of financial market instruments. London: Financial Times. Šoškić, D.B., & Živković, B.R. (2006). Finansijska tržišta i institucije. Beograd: Centar za izdavačku delatnost Ekonomskog fakulteta. (in Serbian).

TRAJANJE I KONVEKSNOST OBVEZNICA Rezime: Veliki uticaj koji promene kamatnih stopa imaju na uspešnost poslovanja, činjenica da su svi tržišni učesnici, više ili manje, izloženi kamatnom riziku, kao i velika volatilnost kamatnih stopa poslednjih godina, čine kamatni rizik jednim od najznačajnijih rizika. Kamatni rizik je nemoguće u potpunosti eliminisati, ali ga je poželjno svesti na najmanju moguću meru. Kako bi se efikasno upravljalo kamatnim rizikom najpre se mora prepoznati i izmeriti izloženost ovoj vrsti rizika. Ovaj rad ima za cilj da ukaže na dve metode merenja kamatnog rizika - na trajanje i konveksnost. Koncept trajanja je dobar pokazatelj promene cene obveznice ali samo za male promene prinosa (kamatnih stopa). U slučaju većih promena, trajanje daje precenjenu/potcenjenu aproksimaciju promenu cene obveznice, jer odnos cena obveznice – prinos nije linearan. Zbog toga se prilikom merenja kamatnog rizika u obzir mora uzeti i konveksnost obveznice. Modifikovano trajanje i konveksnost uzeti zajedno daju najbolju aproksimaciju osetljivosti cene obveznice na promenu kamatnih stopa.

Ključne reči: Mekulijevo, modifikovano, efektivno, empirijsko novčano trajanje, trajanje portfolia, modifikovana i efektivna konveksnost, konveksnost portfolia. Received: October 29th, 2013. Correction: November 21st, 2013. Accepted: November 25th, 2013.

SJAS 2014, 11 (1): 67-73 ISSN 2217-8090 UDK: 338.48-61 DOI: 10.5937/sjas11-5741 Original paper/Originalni naučni rad

STANDARDIZATION AND CLASSIFICATION OF EVENTS IN TOURISM BASED ON A SYSTEMS APPROACH Aleksandra Golob1,*, Tadeja Jere Jakulin1 University of Primorska, Faculty of Tourism Studies - Turistica, Obala 11a, Portorož, Slovenia

Abstract: In this article we wanted to present the importance of event tourism for a destination and categorization of events considering the quality of organization, the quality of staff working on the event, the quality of the event program and the quality of event services. Our theoretical contribution to science is presented by the systems approach method which provides a clear overview of the researched topics and adequate support to decision making. The systems approach method is aimed at understanding the problem and finding an optimal solution. Our intention is to achieve the desired results and positive changes in the field of event tourism using the theory of systems. Within the systems approach method, we also used qualitative modeling of the CLD model of legislative system of events and investments in the events. We have presented our suggestions for achieving these elements through quality standards and classification of events, which leads to optimal categorization of events. Events take place every day, throughout the year, in and out of season, and their number increases each year. This is the main reason for giving more attention to the development of event tourism in the future. High quality events can distinguish us from other destinations and provide a clear advantage over the competition.

INTRODUCTION Event tourism attracts crowds of visitors and tourists to a particular destination due to its attractiveness and diversity. Events that delight people, guests in hotels and business systems, local communities and the whole world, have started to rise rapidly (Jere Lazanski, 2004). Events are interesting because of their transience, unique landscape, number of performers, organizers and crowds of visitors. Organizational environment, as an external system, is connected with other systems which have an influence on it and consequently influences the internal environment of the company (Jere Lazanski, 2006). The main aim and purpose of events is to * E-mail: aleksandra.golob@gmail.com

Key words: the standardization and classification of event, the quality of event, the categorization and specialization of event, modeling, systems approach, CLD model, the legislative system of events.

create positive economic, social and environmental outcomes which would affect development of the destination and the quality of life of local people. However, all that is added value, which gives us a chance to be different from competition. We often talk about quality events that create positive image, which consequently results in an increase of site visits and events in tourist destination. Event tourism has two meanings: ◆ “The systematic planning, development, and marketing of events as tourist attractions, promotions for other developments, image builders, and animators of attractions and destination areas; event tourism strategies should also cover the management of news and negative events. 67

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

◆ A market segment consisting of those people who travel to attend events, or who can be motivated to attend events while away from home” (Getz, 1997, p. 16). We can also add that it is very important for all relevant stakeholders in tourism to be aware that events can create competitive advantage that has a positive effect on the environment attraction and tourist destination. Certainly, events, because of their diversity and frequency, have positive influence on the quality of leisure time for local population as well as for tourists. Visitors acquire new knowledge by participating in various events (both cultural and artistic). Would we still doubt the importance and necessity of introducing standardization and classification of events after all that? “Modern events can be created in order to recall historical, ethnologic, geographic, sports, music and other facts, which were described, written, sung, filmed and revived in a certain place, time, scale, with certain people, means and performance. The purpose should address, and be compatible with, the stated objectives of the event organizational institution” (Jere Lazanski, 2004). The idea of tourism system has been developed on the basis of already established systems theory. Jere Lazanski (2010) has systematically linked the systems, modern system theory and Mayans, and therefore contributed to science as the Mayans became the predecessors of the systems science. However, the basic definition of general systems theory was made by Ludvig Von Bertalanffy (1968) in his classic work “General Systems Theory” and also by authors who were dealing with it: Kljajić (1994); Jere Lazanski (2009, 2012); Smith - Acuña, (2011) and others. Bertalanffy (1968) points out that the general system theory is solving the problem of modern society as an open system, while emphasizing that science should not be divided, but must be combined. Literature review reveals that system theory is applied to various fields of science: in cybernetics (Kljajić, 1994), mathematics, biology (Maturana and Varela, 1998) and also in tourism (Jere Lazanski, 2009); particularly in connection with tourism systems (Leiper, 1990; Baggio and Sainaghi, 2011; Baggio, 2013); tourist destination (Vodeb, 2010); a system of sustainable development (McDonald, 2009; Stubelj and Bohanec, 2010; Nguyen et al., 2011; Camus et al., 2012), as an approach to innovation (Mulej, 1994; Mulej and Ženko, 2002); or otherwise like a systemic perspective to the management ideas (Fatur and Likar, 2009; Ropret et al., 2014) and so on. 68

Methods of system thinking are fundamental methodological principles in our analysis. They have been used for over 40 years and eventually became highly developed. They ask from us not to look at the processes as isolated events and not to perceive their causes as some other events, but to see the organization as a system composed of parts that are in interaction with each other. From systemic point of view, business processes are systems consisting of people and technologies with the purpose of designing, producing, trading and deploying the idea of a product or service. In management we usually come across the problems for which we assume to be the results of external events. Theoretically, systems and systematic thinking are emphasized, as these processes have been gaining in importance and development. The systematic approach deals with the entire system and not with the individual parts of elements, representing their interdependence at the same time. In the context of systems approach, we used qualitative modeling of casual loop diagrams. Systems approach represents an aspect of integrity, which includes both, the importance of structure of the observed problems, as well as visual indicators of the problem. This aspect is becoming more and more appreciated nowadays, because we do not get to the optimal solution with the classic analytic approach, as it is only dealing with visible indicators of the problem. The systems approach, defined by Kljajić (1994) as a fundamental approach to problem solving, has been used in the research, so as to find the best or at least good enough solutions taking into account the integrity and limitations of the system. Our guidelines for organizing quality events, which can be achieved only through legal system for events, are given below. We also present the construction of qualitative cause and effect casual loop diagram (CLD) in the field of the legislative system of events. LITERATURE REVIEW STANDARDIZATION AND CLASSIFICATION OF EVENTS Due to the abundance and diversity of events, it is necessary to introduce the system of quality assurance and to standardize the events. This would prevent good events on the market from getting lost in the critical mass and flood of the similar events. Because of the increasing demand, we have come to

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

the point where we have to regulate all these services due to the diversity of events being offered to us on through the classification and standards. Cvikl states a daily basis. Table 1 shows us the variety of events. that establishment and implementation of quality systems in accordance with the Educational, Political, state Sports Recreational standards is the objective of quality control scientiﬁc activities in the company. Standards are important for harmonization and mutual Seminars, Games and VIP-visit, recognition quality system that meets the sports, congresses, Professional Rally / assembly and amateur. standards and provides several benefits. Entertainment workshop, inauguration. events. A standard defines and provides quality conference. and a criterion for achieving the required quality (adapted from Cvikl, 2008). Cultural Entertainment Business Private Ribnikar (1998) defines standardizaFairs, tion as an agreement or a law establishing Festivals, Concerts, markets, rules, which would provide a solution for Social carnivals, exhibition, celebrations, the future potential problems. Standardiauction, parade, awards, social events. zation also enables specialization and coPR events, religious events. performances. operative working units, provides consistmeetings. ent quality products, streamline and brings Table 1: The diversity of events depending on the type of events greater productivity at work, allows large Source: (Adapted from Getz, 1997, p. 7) scale production and simplifies control services. It also reduces production costs. Even though almost everything is already standCATEGORIZATION OF EVENTS ardized, there are still new areas opening up. Wherever it is necessary, the standards will continue to Categorization contributes to the safety of a tourbe developed, revised and supplemented (Slovenian ist as a consumer. It is a form of verification of the Institute for standardization1 2007). So why wouldn’t owners and managers, professional basis for promowe go further and also propose standards for events? tion and work of employees and also the opportunity to look for better solutions through innovations. Statistical Office of the Republic of Slovenia (2007) Categorization is seen as a minimum that needs to be defines classification as “a break-down of something provided for tourists. It should therefore be perceived taking into account equal or similar characteristics. ” as a constant path to quality improvement (Bizjak, Therefore it classifies individual events within indi1997). When we mention the word categorization, vidual criteria. We propose that these criteria relate the first idea we think of is the classification of acto the volume and the level of events (local, regional, commodation facilities and the minimum technical national or international events), the size of the orrequirements that must be met by the landlord busiganizing team, the legal organizational structure ness. According to that, the categorization of events of the organization (private / profit, non – profit / defines the way of identifying conditions of labeling voluntary, government agencies / public – private the events with stars or other symbols. We propose groups), which deals with events as well as with types a star because this symbol has been already accepted of events. The reasons for such characteristics are as a synonym for quality. The categorization is based different. First of all, it is because of the diversity of on minimum standards, which means that each imthe event organizers, then the diversity of institutions plemented event meets minimum standards fully and dealing with the organization of events and finally because of that it is marked with the symbol of cat1 “Slovenian Institute for standardization (SIST) is the egory or quality. These events, which will be marked Slovenian national standards body responsible for preparing with the symbol of quality, are distinguished accordand adopting voluntary standardization documents, and ing to the different quality standards and services. representing the interests of Slovenia in the international (ISO and IEC), and European (CEN, CENELEC, ETSI) We suggest the following rate of complexity of organizations for standardization, in which it holds full the whole event: memberships. SIST ensures equal involvement of all interested parties in standardization activities thus enabling the co◆ an appropriate and satisfactory event (**), development of European and international standardization” ◆ suited event (***) – quality must be good, (SIST, 2011).

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

◆ first class event (****) – quality must be very good, ◆ exclusive, luxury event (****) – quality must be perfect, without blemish. We must be aware that standardization and classification of events, which also provides optimal categorization of events, will lead us to European norms and open our demanding tourism market to potential beneficiaries of such forms of tourism. The number of events increases each year and therefore even excellent events fade within a crowd of others. The proposed system of events standardization and classification would encourage both sponsors and potential investors and prevent possible abuse of consumer rights as well. Finally, the system also enables the visitors to compare the level of quality of events among different tourist’s destination. QUALITY THROUGH SPECIALIZATION FOR EVENTS

Cvikl (2008) defines quality as a reflection of the roadworthiness of tourism product and meeting the expectations and demands of tourists as much as possible. So, the organizers of events must satisfy the wishes and needs of consumers or visitors in order to achieve their pre-set goals. Quality is the characteristic of a product or service that differs it from other similar types of products in some detail and peculiarities. In market economy there are many manufacturing or service companies committed to the highest quality products and services at minimum possible costs (Ribnikar, 1998). In event tourism it is very difficult to determine and assess the level and quality of supply. Cvikl (2008) considers that it is extremely difficult to evaluate and assess the most important features of customer’s services and the extent to which their expectations in terms of quality should be satisfied.The reason for this lays in the fact that the visitors have completely different perceptions of quality, set forth by their beliefs, values or motives. The visitors’ motives, the reason they decide to attend an event or even opt for a short trip or vacation, are presented below. Their decision is influenced by: ◆ uniqueness – the opportunity to experience something new, ◆ sociability – meeting and talking with people, nice atmosphere, 70

◆ education – the opportunity to learn something new and authentic, ◆ event packages – social and travel experience, ◆ participation in events – watching friends and relatives who participate in events (adapted from Getz, 1997, p. 110). It is easier for event organizers to ensure better quality when they organize events for a specific target group and take into account previously listed subjects. This can be achieved only through specialization of events, which helps to increase the confidence in tourism products on the market. Specialization of events is mostly done because of knowledge that the whole range of events needs to be closer to the wishes and needs of participants. Visitors will recognize the type of event by the specialization symbol given by the event organizer. Thereby, we could meet their expectations and requirements better. So what is the specialization of events? It could be defined as identification of the organizer’s activities for each type of event, which could be legally obtained through the symbol of specialization demonstration. Slovenian Dictionary defines specialization as: 1. orientation, limiting the activity of the narrow scope; 2. acquisition of specific, in-depth knowledge in the specialized field of a profession. So, the main purpose of specialization is to achieve: ◆ greater visibility of supply, ◆ building trust related to the events quality, ◆ increased competitive ability, ◆ better understanding of price difference, ◆ better market process of known target group, ◆ target information and advertising, ◆ designing unique and specific event. METHOD OR DYNAMICS OF SYSTEM THINKING

The application of systems methodology, which is backed up with a systems approach or thinking, is the main methodological principle behind our analysis. System thinking is always supported by an appropriate modeling; therefore, we will show the construction of qualitative cause and effect casual loop diagram (CLD) in the field of the legislative system of events.

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

as a whole. The negative or control circle illustrates the limiting factor in development. Although it is inevitable, it can be controlled by a company. A diagram is abstract enough to allow qualitative analysis of the system and a pre-sign of circles of reverse connections. This is a structural analysis of the systems model. This step is very important and this technique allows us to define virtually any phenomenon in a rational way” (Jere Lazanski, 2009). DISCUSSION

We came to the conclusion that a competitive advantage and added value of tourist destinations can be achieved by improving the quality of events. Figure 1: Construction of the CLD model in the ﬁeld of the legislative “Gradually, with global tourism, events system of events that please people are starting to prevail in tourism and hotel business systems, both We have developed a CLD model or systems modin their hometowns and all around the world. Event el which presents the Slovenian legislation system management and event tourism are starting to bethat has a positive impact on public events (+). Public come essential features for local and global tourist events, in turn, have a positive impact on other events authorities” (Jere Lazanski, 2004). (private, sports, recreational, cultural, educational) (+), and these events improve the attractiveness of Event tourism has very important role in the dethe environment offered by Slovenian event envivelopment of tourism because it attracts tourists out ronment (+). The legal system has a positive impact of season and thus prolongs the season itself. There (+) on the classification of events, which in turn has is a growing number of events and event tourism is a positive impact (+) on investments in events and becoming more important. It is essential that events sponsors, who consequently positively influence (+) take place throughout the year and not only during the attractiveness of event environment. The attracthe high season. This shows us that the number of tiveness increases the number of visitors (+), which events is on the rise every year. According to the Stacauses an increased uncertainty (risk) of a venue tistical office of the Republic of Slovenia (STAT), the (+), and the risk in turn reduces the attractiveness number of events is increasing (number of events in of the environment (-). Public events have a negative the cultural institutions in 2009: 8.855; 2010: 11.121; impact on the conservation of the environment (-), 2011: 11.453, 2012: 17.473), which tells us that the which in turn reduces the attractiveness of an area competitive advantage and added value are vital in (-). Circles of positive feedback mean development, differentiation from the competition. Jere Lazanski but it must be stressed that any downfall in the circle (2008) also points out that unhappy event visitors, is followed by growth. For example, if environment poor ticket sales and cancellations lead to a failure of is ecologically unsafe, therefore less preserved, that an event in general. Focusing on events like these is reduces the attractiveness of the area, which is neceslike wearing blinkers; we can only react to each event sarily followed by a chain reaction in reducing the instead of planning and developing it. This confirms number of visitors. It is also followed by the expected that such events are numerous, as well as previously loss of revenue from admissions and by a reduction in mentioned moments of risk, which is why standinvestment related to the event. It is important to be ardization and classification of events is urgent and able to assess risks and benefits wherever the circles necessary. This could be solved by the introduction with negative feedback and positive feedback meet. of a comprehensive regulatory system, which would set and define minimum standards that should be “These models are rich in their content and relevant in development determination of the system considered by event organizers. This would probably 71

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

lead to poor performances, reduce the moments of risk and thus, we facilitate the path to excellence. Mainly, we could boost tourism development, which would be based on quality complementary offer – the events. Finally, the unique events in the future could be the main motive for the arrival of tourists to a particular tourist destination. Due to their diversity, flexibility and complexity as well as the complex interrelated elements that contribute to their quality, events are herein considered in the light of scientific approach, through the theory of systems supported by system thinking. It can be concluded from our study that the adoption of an act or law on standardization and classification of events at the national level is necessary for successful further development of event tourism.

ticularly sustainably oriented events, as sustainable development is the priority area in tourism (SRST 2012 - 2016). While reviewing the current legislation we found that it is fragmented, opaque and scattered in various documents, and thus not so easily available to event organizers. This confirms the assumption that topics need to be treated systematically – which allows the holistic interpretation. This is the only way to cross disciplinary boundaries and understand the dynamic event management as well as to manage the chaos complexity. To manage this, it is necessary to establish the system that will provide information, management and operation of the system as a whole.

CONCLUDING OBSERVATIONS

Bertalanffy, L.V. (1968). General system theory: Foundations, development, applications. New York: George Braziller. Baggio, R. (2013). Studying complex tourism systems: A novel approach based on networks derived from a time series. In: XIV April International Academic Conference on Economic and Social Development, 2-5 April 2013, Moscow. Retrieved September 17, 2013, from http:// arxiv.org/ftp/arxiv/papers/1302/1302.5909.pdf . Baggio, R., & Sainaghi, R. (2011). Complex and chaotic tourism systems: Towards a quantitative approach. International Journal of Contemporary Hospitality Management, 23(6), 22. Bizjak, S. (1997). Kakovost v gostinstvu: Priročnik za izvajanje kategorizacije. Celje: Fit Media. (in Slovenian). Camus, S., Hikkerova, L., & Sahut, J.M. (2012). Systemic analysis and model of sustainable tourism. International Journal of Business, 17(4), 366-378. Cvikl, H. (2008). Podlage za posodobitev sistema kategorizacije nastanitvenih obratov v Sloveniji. Academica Turistica, 3-4, 10-16. (in Slovenian). Fatur, P., & Likar, B. (2009). Ustvarjalnost zaposlenih za inovativnost podjetja: Sistemski vidik managementa idej kot gradnika uspešne organizacije. Koper: Fakulteta za management. (in Slovenian). Getz, D. (1997). Event management and event tourism. New York: Cognizant Communications Corporation. Jere Lazanski, T. (2004). Hotel animation in light of the event management in tourism. In M. Ambrož (Ed.), Strategic partnerships for the development of tourist destinations: Abstracts (p. 56). Portorož: Turistica, Visoka šola za turizem. Jere Lazanski, T. (2006). Sistemsko mišljenje v prireditvenem okolju. In: Event management 2006 (pp. 71-78). Ljubljana: Planet GV. (in Slovenian).

In qualitative modeling we were looking for the most appropriate and best solution to eliminate our problem or question about how to achieve high quality and unique events, thereby creating added value of Slovenian tourism. Therefore, we have come to a simple solution. It is necessary to transform the current legislative system of events and prepare a document of standardization and classification of events. Many areas, not only those related to tourism, have adopted specific legislative systems, where certain standards of quality and categorization are set (for example: as it is regulated in the field of classification of accommodation, standardization for conferences, categorization of scientific publications, categorization of advertising space and much more). So, why shouldn’t we adopt standards of quality for events as well, as there are certain minimum standards and norms that are required to be achieved for the quality and safe events? In addition, none of the regulatory systems regulates the field of standardization and classification of events at the national level. The adoption of the Act on standardization and classification of events is a great asset, because it creates an added value for all events directly. That will also differentiate us from the competition. The fact is that we always talk about quality events and events that are creating a positive image, which consequently additionally increase visits. Because of these facts we shall not suppress the future development possibilities in the field of regulation of the legislative system of events, par72

REFERENCES

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Golob A., Jere Jakulin T.  Standardization and classi�ication of events in tourism

Jere Lazanski, T. (2009). Sistemski pristop in modeliranje kot metodi za oblikovanje strateških odločitev v turizmu: znanstvena monografija. Portorož: Turistica, Visoka šola za turizem. (in Slovenian).

Nguyen, N.C., Bosch, O.J., & Maani, K.E. (2011). Creating ’learning laboratories’ for sustainable development in biospheres: A systems thinking approach. Systems Research and Behavioral Science, 28(1), 51-62.

Jere Lazanski, T. (2010). System thinking: Ancient Maya`s evolution of consciousness and contemporary systems thinking. In: Computing anticipatory systems: CASYS ‘09: Ninth International Conference on Computing Anticipatory Systems, 1303(1), 289-296. doi: 10.1063/1.3527166.

Ribnikar, I. (1998). ABC ekonomskih izrazov. Ljubljana: Dafis. (in Slovenian).

Jere Lazanski, T. (2012). Systems thinking for co-creative decision-making in tourism. In M. Skakun (Ed.), Conference Proceedings (pp. 37-42). Belgrade: College of tourism. Leiper, N. (1990). Tourist attraction systems. Annals of Tourism Research, 17(3), 367-384. Maturana, H.R., & Varela, F.J. (1998). Drevo spoznanja. Ljubljana: SH - Zavod za založniško dejavnost. (in Slovenian). Mcdonald, R.J. (2009). Complexity science: An alternative world view for understanding sustainable tourism development. Journal of Sustainable Tourism, 17(4), 455-471.

Ropret, M., Jere Jakulin, T., & Likar, B. (2014). The systems approach to the improvement of innovation in Slovenian tourism. Kybernetes, 43, (3-4). SIST. (2011). Sistem standardizacije v Sloveniji. Retrieved March 17, 2011, from http://www.sist.si/index. php?option=com_content&view=article&id=74&Item id=106. (in Slovenian). Smith-Acuña, S. (2011). System theory in action: Applications to individual, couples, and family therapy. Hoboken, N.J: John Wiley and Sons. Stubelj Ars, M., & Bohanec, M. (2010). Towards the ecotourism: A decision support model for the assessment of sustainability of mountain huts in the Alps. Journal of Environmental Management, 91(12), 2554-2564. Vodeb, K. (2010). Turistična destinacija kot sistem. Portorož: Fakulteta za turistične študije - Turistica. (in Slovenian).

STANDARDIZACIJA I KLASIFIKACIJA DOGAĐAJA U TURIZMU NA OSNOVU SISTEMSKOG PRISTUPA Rezime: U ovom članku želeli smo da prikažemo važnost turizma događaja za destinaciju i kategorizaciju događaja, imajući u vidu kvaliteta organizacije, kvalitet osoblja zaduženog za realizaciju događaja, kao i kvalitet programa i usluga samog događaja. Naš teorijski doprinos nauci dat je u okviru metode sistemskog pristupa koja omogućava jasan pregled tema istraživanja, kao i odgovarajuću podršku donošenju odluka. Metod sistemskog pristupa uvek teži razumevanju problema i pronalaženju optimalnog rešenja. Namera nam je bila da postignemo željene rezultate i postignute promene u polju turizma događaja koristeći teoriju sistema. U okviru metode sistemskog pristupa, koristili smo i kvalitativno modelovanje CLD modela zakonodavnog sistema događaja i investiranja u iste. Dali smo predloge za postizanje ovih elemenata, kroz usvajanje standarda kvaliteta i klasifikaciju koja vodi ka optimalnoj kategorizaciji događaja. Svakog dana, tokom čitave godine, u sezoni i van sezone, organizuju se događaji u turizmu, čiji se broj konstantno povećava. To je glavni razlog zbog čega više pažnje treba posvetiti razvoju turizma događaja u budućnosti. Visoko kvalitetni događaji nas mogu izdvojiti od konkurencije i obezbediti nam konkurentsku prednost.

Ključne reči: standardizacija i klasifikacija događaja, kvalitet događaja, kategorizacija i posebno označavanje događaja, modelovanje, pristup sistemu, CLD model, zakonodavni sistem događaja Received: March 19th, 2014. Correction: March 27th, 2014. Accepted: April 3rd, 2014.

SJAS 2014, 11 (1): 74-83 ISSN 2217-8090 UDK: 336.761; 005.334 DOI: 10.5937/sjas11-5820 Review paper/Pregledni naučni rad

OPTIONS, GREEKS, AND RISK MANAGEMENT Jelena Paunović1,* Wiener Städtische osiguranje a.d.o. Belgrade 1 Trešnjinog cveta Street, Belgrade, Serbia

Abstract: Options are financial derivatives representing a contract which gives the right to the holder, but not the obligation, to buy or sell an underlying asset at a pre-defined strike price during a certain period of time. These derivative contracts can derive their value from almost any underlying asset or even another derivative: stock-options, options on bonds, swap options (options on swaps), weather options, real options and many others. Options have existed for a long period of time but they became widely popular after Fisher Black, Myron Scholes and Robert Merton developed a theoretical pricing model in 1973 known as the Black–Scholes model. Options became a standardized product traded on the Chicago board of options Exchange (CBOT) through the clearing house guarantees. Nowadays, options are both market and OTC (over the counter) traded and are mainly used for portfolio hedging and speculation. In this paper I am going to study market risk management from the perspective of options trader, and I will show how to describe the risk characteristics of plain vanilla European stock options contracts by going through the “Greeks” which are defined as quantities that represent option’s sensitivity to risk. Finally, I will construct portfolios that will eliminate these risks.

THE BLACK–SCHOLES MODEL Options are financial derivative contracts that give the right to the holder, but not the obligation, (Jeremić, 2009) to buy or sell an underlying stock at a pre-defined strike price K within a certain time period. Fisher Black, Myron Scholes and Robert Merton (1973) provide a formula that will price any European option assuming a particular model for the underlying price dynamics (they won the Nobel Prize).The Black–Scholes (Black and Scholes,1972) model was derived out of the following assumptions: 74

* E-mail: jelena.paunovic80@gmail.com

Key words: financial derivatives, OTC market, hedging, risk, speculations, Black–Scholes model, Greeks.

◆ Stock prices follow a geometric Brownian motion, volatility is constant, there are no transaction costs or taxes, trade is continuous, there are no limits on short-selling, no dividends, and risk free interest rate is constant (Nations, 2012). Most of these assumptions can be relaxed in order to describe the real world better. In this model, stock prices move continuously and the pricing argument is exactly the same replication argument as in the binomial trees option’s pricing (Živković and Šoškić, 2007).

SJAS 2014  11 (1)  74-83

If we consider all the above - mentioned assumptions, their model allows us to solve the price of the option in a particularly elegant way. Six factors are affecting the price of an option: ◆ the spot price of the stock at the moment T denoted as St. ◆ the Exercise or strike price denoted as K, at which the financial security can be bought or sold. ◆ the option expiration time denoted as T. ◆ the Volatility of the underlying stock denoted as σ. The option price is a function of all these variables so the European call can be written as follows: Call Price = C(S(t),K,T,r,σ). The Black–Scholes formula for the value of a European call option on a non-dividend paying stock is given by (Kolb, 2003): c BS ( St , K ,= T , r , σ ) St N ( d1 ) − Ke

− r (T − t )

N ( d 2 ) . (1)

N(x) is the probability that a N (0, 1) random variable is less than x, and

d1 =

ln( St / K ) + (r + 0.5σ 2 )(T − t ) , σ T −t

d2 =

ln( St / K ) + (r + 0.5σ 2 )(T − t ) σ T −t

d2 = d1 − σ T − t .

(2)

(3)

c BS ( ST , K ,= T , r , σ ) N ( d1 ) St − Ke − r (T −t ) N ( d 2 ) (4)   ∆

as c

( St , K , T , r , σ ) =∆St + B ,

is the “hedge ratio” delta and it gives the number of shares of the stock to hold at time t in order to replicate the call. The key variable which determines the option price is volatility, σ. The strike and the maturity are determined by the contract, the underlying asset price is monitored, and the risk free rate is easily approximated by, for instance, LIBOR or by the overnight interest rate swap. Certainly, Black–Scholes options prices are not what we shall see in the market. If the model was entirely correct, options with the same expiration date for the same stock would have the same implied volatility which is not to be encountered on the market. However, the traders use the implied volatility to calculate the price of options. The observed relation between the implied (Black and Scholes,1972) volatility and the strike price for a given maturity is called the volatility smile. The relation between the implied volatility and maturity for a given strike is called the structure of volatility. We’ve just had a quick reminder of the Black– Scholes model and its assumptions; so we are now ready to start analyzing risk exposures and the characteristics of the main risks associated with a more complex portfolio of underlying stock positions. OPTIONS AND RISK MANAGEMENT

Ln is the natural logarithm; σ is the volatility of the continuously compounded return of the stock. If we re-write

Paunović J.  Options, Greeks, and risk management

(5)

we can see a similarity to the one-period replication model of the binomial trees. Actually, the Black–Scholes is derived by no arbitrage (Mullaney, 2009), as it replicates an option by a dynamic portfolio of a stock and a bond. It is the limit to the binomial model when the number of branches goes to infinity. The detailed derivation of the Black–Scholes model and the binomial tree model falls out of the scope of this paper. We can see from what is given above that the call option can be replicated by buying a delta amount of stock and by selling B amount of bonds. In this case N (d1)

The following example will be used throughout this paper: Let’s suppose we are trading options for J.P. Morgan and we write an (at-the-money) European call for $5 with T=10 weeks. The underlying stock is traded at $50, sigma=50%, and the risk-free rate is 3%. The Black–Scholes model gives us the price of the call option: $4.5. In order to make a risk-free $0.5 profit we could buy the same option for $4.5 elsewhere or spend $4.5 on a replicating portfolio (by buying a synthetic option for example) that has the same payoff. This is possible in theory, however, in practice, perfect replication of the option’s payoff is not real. We cannot perfectly hedge all the risk associated with the call we have just written. That could be done if the binomial tree model perfectly described the stock price dynamics (which is not the case in the real world) and if we traded without transaction costs (which is also impossible). 75

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Paunović J.  Options, Greeks, and risk management

Unfortunately, the lognormal distribution of the price dynamics in the Black–Scholes model does not describe the stock price dynamics perfectly. On the other hand, in the real world, we can’t trade continuously (Jonson, 2007) - the transaction costs can be substantial and the volatility of the underlying risk free stock isn’t constant as assumed by the theoretical Black–Scholes model. If the Black–Scholes model was perfect, the options markets wouldn’t even exist, as each option would have only one real price. In practice, options traders behave in the following way – they identify different risk sources that change the value of our call: the stock price S(t), the time T, the volatility and the interest rate r. Then, they form an approximate replicating portfolio for the written call option. The value of this portfolio should change by about the same amount as that of the option (at least for small changes in the factors). In order to determine how sensitive the options are to the particular risk source one should look at the “Greeks” options (Hull, 2002) - quantities denoted by Greek letters representing options’ sensitivities to risk. They are the key to options risk management.

= vs

∂St ∂St = o,= ps = 0. ∂σ ∂r

Thus, a stock has just a delta equal to 1 and all the other Greeks are zero valued. Now, for a European call option, this is how its price changes when only one factor varies whereas the others are fixed: ◆ The Delta (Δ) describes the derivative’s sensitivity to the price of the underlying security S. We can see from the Black–Scholes formula that the delta of call and put option is: ∂C ∂P ∆ c= = N (d1 ) > 0 , ∆ p = =− N (−d1 ) < 0 , (8) ∂S ∂S and we can see that

∆ c → 0 as S → 0 and ∆ c → 1 as S → ∞ . A delta of a call option typically looks like the graph given in the following chart (Hull, 2002):

THE “GREEKS” In order to construct the approximate replicating portfolio, we have to know by how much the value of the option changes as various risk factors change (Hull, 2011). Using calculus, for small changes in the risk factors, the value of the call option changes by: dC =

∂C 1 ∂ 2c ∂C ∂C ∂C dS + (dS ) 2 + dt+ dσ + dr , (6) 2 ∂ S 2 ∂ S ∂ t ∂ ∂r σ      Delta

Gamma

Theta

Vega

Rho

or using the Greek symbols Δ, Γ, Θ, ν and p, we have: 1 dC = ∆ c dS + Γ c (dS ) 2 + Θc dt + vc dσ + pc dr , (7) 2 These Greeks depict the market risk associated with the option. In order to understand the following examples, we are first going to compute the Δ, Γ, Θ, ν and p, for the underlying stock: ∆= s

∂St ∂St ∂∆ s = 1 , Γ= = 0, = 01 , Θ= s s ∂St ∂t ∂St

The above-given charts make the following assumptions: delta, gamma, theta, rho and vega are seen as a function of time-to maturity, for three different levels of moneyness (with K=100 (the solid line, at the money), K=80 (dashed line, in the money) and K=120 (dotted line, OTM)). In all these examples S=100, sigma= 0.56, and r = 5%.

SJAS 2014  11 (1)  74-83

The Gamma describes the derivative’s convexity and is given by:

Γ= c

∂∆ c ∂d1 N '(d1 ) N '(d1= ) = > 0 . (9) ∂S ∂S Sσ T − t

The Gamma of the call option is always equal to the gamma of the put:

−∂ (−d1 ) Γp = N '(− d1 ) =Γ c . ∂S We can see that

Γ → 0 as S → 0 Γ → 0 as S → ∞ ,

Γ is high when S ≈ K .

(10)

Paunović J.  Options, Greeks, and risk management

The Theta describes a derivative’s sensitivity to the time to maturity (T). It captures the time-decay and it is given by the following formula using Black–Scholes: Θc =

−∂ ∂c = ( SN (d1 ) − Ke − r (T −t ) N (d 2 )) ∂t ∂ (T − t )

Θc =− S

∂N (d1 ) ∂N (d 2 ) + Ke − r (T −t ) − rKe− r (T −t ) N (d 2 ) . (11) ∂ (T − t ) ∂ (T − t )

When simplified, it becomes:

SN '(d1 ) =

Se − ( d2 +σ

T −t )2 /2

2π In fact, Gamma tells us how much delta we gain − σ T −t )d 2−σ 2(T −t )/2 as the underlying stock rises. It also reveals another = SN '(d1 ) SN = '(d 2 )e Ke− r (T −t ) N '(d 2 ) , (12) important thing and that is by how much a deltahedged derivative becomes unhedged (Ross et al., and with 2012a). We’ll deal with this in further details at the end of the paper when we’ll be building hedging ∂ (d1 − d 2 ) ∂ (σ T − t ) σ . (13) = = portfolios. ∂ (T − t ) ∂ (T − t ) 2 T −t A gamma of a call option typically looks like the graph given in the following chart: Taking them together we get:

= Θc

− N '(d1)σ S 2 T −t

− rKe − r (T −t ) N (d 2 ) < 0 .

(14)

As theta is negative all the time, the value of the call decreases as time elapses which makes sense (Ross et al., 2012b). However, for the put option we have to identify the put-call parity:

∂ (C − f ) ∂f Θp = =Θc + ∂t ∂ (T − t ) − N '(d1)σ S = Θp + rKe − r (T −t ) N (− d 2 ) . 2 T −t

(15)

The first term of the theta (put) is negative because the variance of the stock price at maturity T decreases over time (Augen, 2011). The second term is positive because the present value of the strike grows with less time to maturity. The put receives the strike, so this tends to make the put more valuable as time goes by. A theta of a call option typically looks like the graph given in the following chart: 77

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Paunović J.  Options, Greeks, and risk management

The Vega describes the option’s sensitivity to the volatility of the underlying stock and is given by:

∂C

υc = = S T − t N '(d1 ) > 0 , ∂σ υ = p

∂p = υc . ∂σ

(16) (17)

Now we have:

∂N (d1 ) ∂d1 = N '(d1 ) , ∂r ∂r

υ≈0 for S<K, ν is the largest for S≈Ke-r(T-t),

(19)

and ∂N (d 2 ) ∂ (d1 − σ T − t ) ∂d1 = = N '(d 2 ) N '(d 2 ) , (20) ∂r ∂r ∂r

The Vega is really valuable because the Black– Scholes model is assumes/implies constant volatility. Volatility traders use complex statistical models (ARIMA, GARCH etc.) to predict the options implied volatility and thus make decisions if an option is over or under-valued (Fontanills, 2005). The Vega of a call option typically looks like the graph given in the following chart: 78

∂ ( SN (d1 ) − Ke− r (T −t ) N (d 2 )) ∂r ∂N (d1 ) ∂N (d 2 ) = − Ke − r (T −t ) + (T − t ) Ke − r (T −t ) N (d 2 ). (18) pc S ∂r ∂r

= pc

We can easily see that:

υ≈0 for S>K .

The Rho describes the option’s sensitivity to the risk free interest (Natenberg, 1994) rate changes and is given by:

and

SN '(d1 ) = Ke − r (T −t ) N '(d 2 ) ,

(21)

so finally we get:

pc = (T − t ) Ke − r (T −t ) N (d 2 ) > 0 .

(22)

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Paunović J.  Options, Greeks, and risk management

By put-call parity:

RISK MANAGEMENT WITH THE GREEKS − r (T − t )

∂ (C − S + Ke ∂r p p = pc − (T − t ) Ke− r (T −t ) pp =

pp = −(T − t ) Ke − r (T −t ) N (−d 2 ) < 0 .

(23)

The value of the call always increases when interest rates rise (Passarelli, 2011), while the current value of the strike price K drops. The opposite is true for the puts. The Rho of a call option typically looks like the graph given in the following chart:

The basic idea of portfolio hedging is that the value of a portfolio can be made invariant to the factors affecting it. For example let’s say we have a portfolio that consists of three assets (Vine, 2011):

V = n1 A1 + n2 A2 + n3 A3 ,

(25)

with: V the total value of the portfolio (McDonald, 2009), n(i) the number of shares of asset I and A(i) the market value of one share of asset i. Then the sensitivity of this portfolio to some factor x is given by the first derivative:

∂A ∂A ∂A ∂V = n1 1 + n2 2 + n3 3 . ∂x ∂x ∂x ∂x

(26)

The aim of x-hedging is to pick the n(i) so that the value of the entire portfolio remains constant when the factor x changes, which is equal as picking the n(i) so that:

∂A ∂A ∂A ∂V = n1 1 + n2 2 + n3 3 = 0 . ∂x ∂x ∂x ∂x

(27)

When x changes by one unit, the value of the entire portfolio will stay approximately constant. What is important to notice here is that it takes n assets to hedge against n-1 sources of risk. If we have 3 assets in the portfolio we can only hedge away two risks (Augen, 2008). DELTA HEDGING

The quantities we have just derived are the main sources of an option risk. However, there are some other “Greeks” such as The Lambda, the Volga, and the Vanna, which are much less common and measure the delta per invested dollar, the second order sensitivity to volatility and the sensitivity of delta to volatility, respectively. For a call option, they are given by = λc

∆ c ∂ 2 C ∂vc ∂∆ ∂2C = , = c . (24) and 2 ∂σ C ∂σ ∂σ∂S ∂σ

A portfolio is called Delta neutral or delta hedged if the delta of the portfolio is equal to zero. Similar to our previous example but this time with x = S(t). The portfolio will be delta neutral if we pick the number of shares n(i) so that:

∂A ∂A ∂A ∂V ∆ portfolio = =n1 1 + n2 2 + n3 3 ∂s ∂s ∂s ∂s ∆ portfolio = n1∆1 + n2 ∆ 2 + n3 ∆ 2 = 0 . (28) If we create such portfolio, it is going to be invariant to changes in underlying stock price S(t). Coming back to our J.P. Morgan example from the beginning of the paper where we wrote the call option for $5: 79

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Paunović J.  Options, Greeks, and risk management

Let’s say we have

= S 50,= K 50, T = −t

DELTA AND GAMMA HEDGING

10 ,= σ 0.50 and= r 0.03 . 52

In order to delta-hedge this option, we shall first compute the delta with the Black–Scholes model - we get ΔC=0.554. As we have written the call, and knowing that the delta of the stock is equal to 1, we will buy the shares such as ns ×1 − 0.554 = 0 ⇔ ns = ∆S = 0.554 shares of the underlying stock. GAMMA HEDGING

However, if we want to do both, gamma and delta hedge, we would need to buy another option because the stock has 0 gamma, as it was seen before (Cottle, 2006), for example a call with the strike K = 55$. To have both the gamma and the delta of the portfolio equal to zero we have to solve the following system of equations:

ns ∆ s + nc55 ∆ c55 + nc50 ∆ c5 o =0,

(30)

ns Γ s + nc55 Γ c55 + nc50 Γ c5 o =0.

(31)

The Black–Scholes model gives us: A portfolio is called Gamma neutral or Gamma hedged if the Gamma of the portfolio is equal to zero. Similar to our previous example with 3 assets, we have x = S(t). The portfolio total gamma is given by the second derivative in respect to the underlying stock S(t):

∂ 2V ∂∆ portfolio Γ portfolio = 2 = ∂S ∂S ∂A ∂A ∂A Γ portfolio = n1 1 + n2 2 + n3 3 ∂S ∂S ∂S Γ portfolio = n1Γ1 + n2 Γ 2 + n3Γ 2 .

and

∆ c55 = 0.382 , Γ c55 = 0.0348 . By solving the system of equations we get:

ns = 0.158 and nc55 = 1.037 ,

(29)

We’ve previously seen that when we shorten the money call for $4.5 and go long 0.554 shares, our portfolio will be delta hedged. Now the problem with delta hedging is only the following: ◆ If the underlying stock S(t) makes a little move from $50 to $51, the value of the call C will go from C(50,50, 10/52, 0.50, 0.03) = 4.498 to C(51,50,10/52, 0.50, 0.03) = 5.070. Our portfolio will get a slight loss of 0.554(5150) – (5.070-4.498) = -0.018$. ◆ If the underlying S makes a bigger move from $50 to $60, the value of our call will then go from C(50,50,10/52,0.50,0.03) = 4.498$ to C(60,50,10/52,0.50,0.03) = 11.541$ ◆ In the second case, the value of our portfolio would then get a more significant loss of 0.554(60-50) – (11.541-4.498) = 1.54$ for a $10 increase of the underlying stock. Our delta hedged position still has a considerable risk exposure for a large move in the underlying stock. This is where gamma hedging becomes interesting because it can improve the quality of the hedge. 80

0.554 , Γ c5 o = 0.0361 , ∆ c5 o =

which is the number of stock and call options with $55 strike that would make our portfolio both delta and gamma neutral. In this case if the underlying stock S makes a little move from $50 to $51 (Bodie et al., 2010c), the portfolio would look as follows: C50(51) - C50(50) = 5.067 - 4.498 = 0.569 for the call with K=50$ and

C55(51) - C55(50) = 3.002 - 2.602 = 0.400 for the call with K=55$.

The total value of the portfolio will increase by: 0.158∙10 + 1.307∙5.501 - 1∙7.084 = 0.201$ which is a very good hedge. Now if the underlying stock S makes a bigger move from $50 to $60 (Bodie et al., 2010a), the portfolio would look as follows: C50(60) - C50(50) = 11.581 - 4.498 = 7.084 for the call K=50$ and

C55(60) - C55(50) = 8.104 - 2.602 = 5.501 for the call K=55$.

The total value of the portfolio will increase by: 0.158∙10 + 1.037∙5.501 - 1∙7.084 = 0.201$, which is much less than if we only delta hedged the portfolio (the variation would’ve been $1.55).

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However, in order to do this hedge it should not be forgotten that it takes 3 assets to form such portfolio.

Paunović J.  Options, Greeks, and risk management

denoted as P* (Bodie et al., 2010b) which is equivalent as if we said that the portfolio is Gamma neutral:

P* = C − P∆ ∆ c − Pp pc − PΘ Θc

P* = ( SN (d1 ) − K e − r (T −t ) N (d 2 )) − SN (d1 )

VEGA, THETA AND RHO HEDGING

1 − N (d1 )σ S P* = − ( − rKe − r (T −t ) N (d 2 ) r 2 (T − t )

The mechanics of these hedging strategies are similar to Delta and Gamma hedging. Instead of N '(d1 )σ S equating the delta to zero, we are going to set Rho P* = (36) or Vega equal to zero (Cohen, 2005). These Greeks 2r (T − t ) are important but less important than the other two by using the Black–Scholes formula along with the Greeks mentioned before. We can construct portfoprices per unit of delta, rho and theta. lios that have pure exposures to individual Greeks by hedging all the other risks away (Sincere, 2006). So we have: For example, if we only want exposure to Vega that N '(d1 ) = Γ p* = ∆ p* 0 , (37) would mean that we will be “trading volatility”. Sσ (T − t ) Θ= 0.v= σ S 2 (T − t )Γ c p* p*

THE PRICE OF GREEKS

(38)

and Each one of these risk exposures has its own price p p* = 0 . (Passarelli, 2012). The simplest example would be to price the cost of a unit exposure to delta. In order to get the price of gamma we have to solve the following equation: ◆ As the underlying stock S is a pure exposure to delta, one unit of delta would then cost the N '(d1 )σ S price of the underlying stock S(t). p * 2r (T − t ) σ 2 S 2 = = ◆ If we want to price the Rho (Chen and SeN '(d1 ) Γ p* 2r bastian, 2012), its value would be zero as the Sσ (T − t ) duration costs nothing. Proof: The Greeks of a bond are: 2 2

∆ B =Γ B =vB =0

p* ( (32) =

∂Bt = rBt ,T ' ∂t

(33)

∂B PB = t = −(T − t ) Bt ,T " ∂r

(34)

Θ=B

so when we go long or short one bond, the price of Rho Pρ=0. Knowing this, we can compute the cost of the Theta: If we buy a bond that costs Bt and hedge the rho risk (no cost), our pure theta exposure of rBt costs us Bt, so Bt ,T 1 . (35) = PΘ = rBt ,T r Now in order to find the price of Gamma (which is more complex) we are going to look for the price of a delta, rho, and theta hedged call option portfolio

σ S 2r

) Γ p* ,

(39)

it means that $1 invested in any delta, rho and theta hedged call would give us the same amount of gamma which is

p * σ 2S 2 = P Γ p* / p* = 2r / σ S  Γ Γ= 2r , (40) p* 2

To summarize, we have

P∆ S= = , PΓ

σ 2S 2 2r

Pv 0,= PΘ 1/ r ,(41) = , Pρ 0,=

So the price of any European option (Carter, 2012) V in terms of its Greeks can be written as:

V= P∆ ∆ + PΓ Γ + Pρ p + Pv v + PΘ Θ V = S∆ + (

σ 2s2

1 )Γ +   Θ , 2r r

(42) 81

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Paunović J.  Options, Greeks, and risk management

which is equivalent to: 1 rV = rSCs + σ 2 S 2Css + Ct . 2

(43)

We can see from the above given, that ultimately we get the Black–Scholes partial differential equation (Ianieri, 2009) that governs the price dynamics of any derivative. CONCLUSION The options market is a constantly changing market. In Serbia, it is currently at an initial stage and its main purpose will be to allow investors to hedge the existing positions and minimize the risk exposure. In order to do so, the traders and the hedgers will have to fully understand “Greeks” options which are defined as the quantities that represent sensitivities of the option’s price to a particular source of risk. The Greeks are the best tools for building portfolios despite of market conditions. In this paper we offered an insight into risk management options in a straightforward way and we also derived the Greeks from the Black–Scholes model in order to show how they could be used to create strategies that profit from the option’s time to maturity, volatility and risk-free interest rate changes. We also provided several real life examples on how the Greeks could lead to a more accurate pricing and trading which will further on alert a hedger to over or undervalued options that could be exploited for a profit. REFERENCES Augen, J. (2008). The volatility edge in options trading: New technical strategies for investing in unstable markets. Upper Saddle River, N.J: FT Press. Augen, J. (2011). The option trader’s workbook: A problemsolving approach. Upper Saddle River, N.J: FT Press. Black, F., & Scholes, M. (1972). The valuation of option contracts and a test of market efficiency. The Journal of Finance, 27(2), 399-417. doi:10.1111/j.1540-6261.1972. tb00969.x. Bodie, Z., Kane, A., & Marcus, A.J. (2010a). Investments. New York, NY: McGraw-Hill Irwin. Bodie, Z., Kane, A., & Marcus, A. J. (2010b). Investments and portfolio management. New York, NY: McGrawHill Irwin. Bodie, Z., Kane, A., & Marcus, A.J. (2010c). Student solutions manual for investments. New York, NY: McGrawHill Irwin. 82

Carter, J.F. (2012). Mastering the trade: Proven techniques for profiting from intraday and swing trading setups. New York: McGraw Hill Professional. Chen, A.D., & Sebastian, M. (2012). The option trader’s hedge fund: A business framework for trading equity and index options. Upper Saddle River, N.J: FT Press. Cohen, G. (2005). The bible of options strategies: The definitive guide for practical trading strategies. Upper Saddle River, N.J: FT Prentice Hall. Cottle, M.C. (2006). Options trading: The hidden reality: Ri$k Doctor guide to position adjustment and hedging. Chicago: RiskDoctor. Fontanills, G. (2005). The options course: High profit & low stress trading methods. Hoboken, N.J: John Wiley & Sons. Hull, J.C. (2002). Options, futures, and other derivatives (5th ed.). New York, NY: Prentice Hall College Div. Hull, J.C. (2011). Student solutions manual for options, futures, and other derivates (8th ed.). Upper Saddle River, N.J: Pearson Prentice Hall. Jeremić, Z. (2009). Finansijska tržišta. Beograd: Univerzitet Singidunum. (in Serbian). Jonson, B. (2007). Options trading 101: From theory to application. New York: Morgan James Publishing Kolb, R. W. (2003). Futures, options and swaps. Malden, MA: Blackwell. Ianieri, R. (2009). Options theory and trading: A step-by-step guide to control risk and generate profits. Hoboken, N.J: Wiley. McDonald, R.L. (2009). Derivatives markets. New Jersey: Prentice Hall. Mullaney, M. (2009). The complete guide to option strategies: Advanced and basic strategies on stocks, ETFs, indexes, and stock indexes. Hoboken, N.J: Wiley. Natenberg, S. (1994). Option volatility and pricing strategies: Advanced trading techniques for professionals. New York: McGraw-Hill. Nations, S.B. (2012). Options math for traders: How to pick the best optionstrategies for your market outlook. Hoboken, N.J: Wiley. Passarelli, D. (2011). The market taker’s edge: Insider strategies from the options trading floor. New York: McGrawHill. Passarelli, D. (2012). Trading option Greeks: How time, volatility, and other pricing factors drive profits. Hoboken, NJ: Wiley. Ross, S., Westerfield, R., & Jaffe, J. (2012a). Corporate finance. New York: McGraw-Hill. Ross, S., Westerfield, R., & Jaffe, J. (2012b). Solutions manual for corporate finance. New York: McGraw-Hill. Sincere, M. (2006). Understanding options. New York: McGraw-Hill.

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Vine, S. (2011). Options: Trading strategy and risk management. Hoboken, N.J: Wiley. Živković, B., & Šoškić, D. (2007). Finansijska tržišta i institucije. Beograd: Centar za izdavačku delatnost Ekonomskog fakulteta. (in Serbian).

Paunović J.  Options, Greeks, and risk management

OPCIJE, GREEKS, I UPRAVLJANJE RIZIKOM Rezime: Opcije su finansijski derivati koji predstavljaju ugovor koji daje pravo vlasniku, ali ne i obavezu, da kupi ili proda određenu aktivu po ugovorenoj ceni izvršenja u toku određenog vremenskog perioda. Derivatni ugovori mogu da dobiju vrednost od skoro svake određene aktive ili čak drugih derivata: postoje opcije na akcije, opcije na obveznice, opcije na svopove, vremenske opcije, prave opcije i mnoge druge. Opcije postoje duži vremenski period, ipak postaju popularne nakon što su Fisher Black, Myron Scholes and Robert Merton razvili teoretski cenovni model poznat kao Black–Scholes model. Opcije postaju standardizovan produkt trgovine na Čikaškoj berzi opcija (CBOT) posredstvom garancije klirinske kuće. Danas, opcijama se trguje na berzama ili van-berzanski (OTC ) i one se uglavnom koriste za portfolio hedžing i spekulacije. U ovom naučnom radu akcenat je stavljen na tržišno upravljanje rizikom posmatrano iz ugla trgovaca opcijama, kao i na opis karakteristika rizika plain vanilla Evropskih opcionih ugovora putem “Greeks” kvantitativa, koji predstavljaju opcionu osetljivost na rizik. Na kraju rada konstruisan je portfolio koji će ukloniti navedene rizike.

Ključne reči: finansijski derivati, OTC tržište, hedžing, rizik, spekulacije, Black–Scholes model, Greeks. Received: March 31st, 2014. Correction: April 1st, 2014. Accepted: April 3rd, 2014.

INSTRUCTIONS FOR AUTHORS

Singidunum Journal of Applied Sciences is a biannual, peer-reviewed journal which publishes significant original scientific research and reviews. The Journal is devoted to the publication of research results in the following areas: economy, management, tourism and hospitality, computer science and law. It is essential that authors write and prepare their manuscripts according to the instructions and specifications listed below. The length and effectiveness of the peer review process will largely depend upon the care used by authors in preparing their manuscripts. Therefore, contributors are strongly encouraged to read these instructions carefully before preparing a manuscript for submission, and to check the manuscript for conformance before submitting it for publication. The manuscripts must be written in English using Microsoft Word (*.doc or *.docx). Make sure that your manuscripts are clearly and grammatically written. Please note that authors who are not native-speakers of English can, to a certain amount, be provided with help in rewriting their contribution in correct English. The Editorial Board expects the editors, reviewers and authors to respect the well-known standard of professional ethics. Types of contributions: ◆ Original papers - (about 10 typewritten pages) report original research which must not have been previously published. ◆ Preliminary communications - (up to 3 pages) report unpublished preliminary results of sufficient importance to demand rapid publication. ◆ Subject reviews - (about 15-20 pages) present an overview of the author’s current research with comparison to data of other scientists working in the field. Manuscripts should be submitted using the Online Submission System. The manuscript must be uploaded as a *.doc or *.docx file (tables and figures should follow the text, each on a separate page). No articles will be published without first undergoing an anonymous refereeing procedure (please read carefully Editorial policy). To facilitate the reviewing process, authors are encouraged to suggest up to three persons competent to review their manuscript. Such suggestions will be taken into consideration but not always accepted. The editor reserves the right to make the final decision with respect to publication. If you have any questions, do not hesitate to contact the Managing Editor at sstanisic@singidunum.ac.rs. 84

SJAS 2014

Instructions for authors

Manuscripts should be typed in English (standard British English) with 1.15 spacing in A4 format leaving 2.5 cm for margins. Manuscript elements: 1. Title page with: 1. title (and short title) 2. name(s) of author(s) 3. name and address of workplace(s) â&#x20AC;&#x201C; affiliation(s) 4. personal e-mail address(es) 2. Abstract 3. Keywords 4. Introduction 5. Methodology 6. Results and Discussion 7. Reference lists 8. Tables (each on a separate page) 9. Figures (each on a separate page). Each of these elements is detailed below.

1. TITLE PAGE 1.1. Title (and short title) We suggest the title should be relatively short but informative. If a long title is necessary, please prepare an optional short title. 1.2. Name(s) of author(s) A list of all authors of the paper should be prepared. We need full first name and full last name. Initial(s) for middle name(s) is optional. 1.3. Name and address of workplace(s)- affiliation(s) Authors' affiliations should be indicated in this section. Either endnote or footnote are not recommended. 1.4. Corresponding authorâ&#x20AC;&#x2122;s e-mail address One e-mail address is needed. It will be used as the corresponding author's email address in all contacts with the authors.

2. ABSTRACT An abstract must accompany every article. It should be a brief summary of the significant items of the main paper. The abstract should give concise information about the content of the core idea of your paper. It should be informative and not only present the general scope of the paper but also indicate the main results and conclusions. The abstract should not normally exceed 200 words. It should not contain literature citations or allusions to the tables or illustrations. All non-standard symbols and abbreviations should be defined. In combination with the title and keywords, the abstract is an indicator of the content of the paper. Authors should remember that online systems rely heavily on the content of titles and abstracts to identify articles in electronic bibliographic databases and search engines. They are therefore requested to take great care in preparing these elements.

3. KEYWORDS List of keywords proposed by the authors, separated by commas. Up to 5 key terms can be selected. We would suggest to avoid repeating the title. 85

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Instructions for authors

4. TEXT General rules for writing: ◆ use simple and declarative sentences, avoid long sentences, in which the meaning may be lost by complicated construction;

◆ be concise, avoid idle words; ◆ make your argumentation complete; use commonly understood terms; define all nonstandard symbols and abbreviations when you introduce them; ◆ Latin words, as well as the names of species, should be in italic, as for example: i.e. or e.g. ◆ explain all acronyms and abbreviations when they first appear in the text. Generally a standard scientific paper is divided into: ◆ introduction, ◆ main text, ◆ conclusion. Footnotes/Endnotes/Acknowledgements: We encourage authors to restrict the use of footnotes. If necessary, please make endnotes rather than footnotes. Information concerning research grant support or the assistance of colleagues should appear in a separate Acknowledgements section at the end of the paper, not in a footnote.

5. REFERENCE LIST A complete reference should give the reader enough information to find the relevant article. Please pay particular attention to spelling, capitalization and punctuation. The article should contain no fewer than 25 references, preferably published recently. Completeness of references is the responsibility of the authors. Please avoid references to unpublished materials, private communication and web pages. The surname of the author and the year of publication appear in parentheses after the citation, for example (Fisher, 2010). If more than one publication by the same author appear in one year, they must be distinguished by an a, b, etc., for example 2001a, 2001b. In case of quoting the actual words of another author, the page number should be provided, e.g. (Hollard, 2010, p. 23). If the name naturally occurs in the sentence, only the year is given in parentheses, e.g. “Benoliel (1999) thinks…” If there are two authors, the surnames of both should be given (Fisher and Hollard, 2009). If there are more than two authors, the surname of the first author only should be given, followed by et al. (Wilson et al., 2008). However, full names of all authors should be given in the list of references. The original journal title is to be retained in the case of publications published in any language other than English (please denote the language in parenthesis after the reference in the Reference list). 1. Book a. Book (one author) Format: Author. (Year of publication). Book title. Place of publication: Publisher. Example: Baxter, R. (1982). Exactly solvable models in statistical mechanics. New York: Academic Press. b. Book (two or more authors) Format: Author1, Author2, & Author3. (Year of publication). Book title. Place of publication: Publisher. Example: Kleiner, F.S., Mamiya C.J., & Tansey R.G. (2001). Gardner’s art through the ages (11th ed.). Fort Worth, USA: Harcourt College Publishers. 86

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Instructions for authors

c. Book chapter or article in an edited book Format: Author(s) of chapter. (Year of publication). Chapter title. In Editors of the book (Ed.), Book title (Chapter page range). Place of publication: Publisher. Example: Roll, W.P. (1976). ESP and memory. In J.M.O. Wheatley & H.L. Edge (Ed.), Philosophical dimensions of parapsychology (pp. 154-184). Springfield, IL: American Psychiatric Press. d. Proceedings from a conference Format: Author(s). (Year of publication). Title. In Conference name, Date (Page range). Place of publication: Publisher. Example: Field, G. (2001). Rethinking reference rethought. In Revelling in Reference: Reference and Information Services Section Symposium, 12-14 October 2001 (pp. 59-64). Melbourne, Victoria, Australia: Australian Library and Information Association. e. E-book Format: Author(s). (Year of publication). Title. Publisher. Retrieving date, http address. doi. Example: Johnson, A. (2000). Abstract Computing Machines. Springer Berlin Heidelberg. Retrieved March 30, 2006, from SpringerLink http://springerlink.com/content/w25154. doi: 10.1007/b138965. f. Thesis Format: Author(s). (Year of publication). Title. Information, Place of publication. Example: Begg, M.M. (2001). Dairy farm women in the Waikato 1946-1996: Fifty years of social and structural change. Unpublished doctoral dissertation, University of Waikato, Hamilton, New Zealand. g. Government publication Format: Institution name. (Year of publication). Title. Place of publication: Publisher. Example: Ministerial Council on Drug Strategy. (1997). The national drug strategy: Mapping the future. Canberra: Australian Government Publishing Service. 2. Article a. Journal Article (one author) Format: Author. (Year of publication). Article title. Journal Title. Volume (issue), range of pages. doi. Example: Nikora, V. (2006). Hydrodynamics of aquatic ecosystems: Spatial-averaging perspective. Acta Geophysica, 55(1), 3-10. doi: 10.2478/s11600-006-0043-6. b. Journal Article (two or more authors) Format: Author1, Author2, & Author3. (Year of publication). Article title. Journal Title. Volume (issue), range of pages. doi. Example: Cudak, M., & Karcz, J. (2006). Momentum transfer in an agitated vessel with off-centred impellers. Chem. Pap. 60(5), 375-380. doi: 10.2478/s11696-006-0068-y. 87

SJAS 2014

Instructions for authors

c. Journal article from an online database Format: Author(s). (Year of publication). Article title [Electronic version]. Journal Title. Volume (issue), range of pages. Retrieved date of access, from name of database. doi. Example: Czajgucki Z., Zimecki, M., & Andruszkiewicz, R. (2006, December). The immunoregulatory effects of edeine analogues in mice [Abstract]. Cell. Mol. Biol. Lett. 12(3), 149-161. Retrieved December 6, 2006, from PubMed database on the World Wide Web: http://www.pubmed.gov. doi: 10.2478/ s11658-006-0061-z. d. Newspaper article (no author) Format: Article title. (Publication date). Journal Title. page. Example: Amazing Amazon region. (1989, January 12). New York Times, p. D11. 3. Other formats a. Web page Format: Author/Sponsor. (last update or copyright date). Title. Retrieved date of access, from URL. Example: Walker, J. (1996, August). APA-style citations of electronic resources. Retrieved November 21, 2001, from http://www.cas.usf.edu/english/walker/apa.html. b. Lecture note Format: Author(s). (Date of presentation). Lecture title. Lecture notes distributed in the unit, at the name of the teaching organisation, the location. Example: Liffers, M. (2006, August 30). Finding information in the library. Lecture notes distributed in the unit Functional Anatomy and Sports Performance 1102, University of Western Australia, Crawley, Western Australia. c. Patent Format: Author. (Year). Patent number. The location. Issue body. Example: Smith, I. M. (1988). U.S. Patent No. 123,445. Washington, D.C: U.S. Patent and Trademark Office. d. Standard Format: Issue body. (Year). Standard name. Standard number. The location. Example: Standards Association of Australia. (1997). Australian standard: Pressure equipment manufacture. AS4458-1997. North Sydney. e. Computer software Format: Author(s). (Year). Title [computer software]. The location: Company. Example: Ludwig, T. (2002). PsychInquiry [computer software]. New York: Worth. 88

SJAS 2014

Instructions for authors

Tables and figures and/or schemes should not be embedded in the manuscript but their position in the text indicated. In manuscript tables and figures should follow the text, each on a separate page.

6. TABLES Authors should use tables to achieve concise presentation or where the information cannot be given satisfactorily in other ways. Tables should be prepared with the aid of the Word table function, without vertical lines. The minimum size of the font in the tables should be 10 pt. Tables should not be incorporated as graphical objects. Styles and fonts should match those in the main body of the article. Tables should follow the text on the end of the manuscript and should be numbered consecutively using Arabic numbers and their position in the text should be indicated. Each table should have an explanatory caption which should be as concise as possible.

7. FIGURES Authors may use line diagrams to illustrate theses from their text. The figures should be clear, easy to read and of good quality. Styles and fonts should match those in the main body of the article. Lettering and lines should be of uniform density and the lines unbroken. Axis labels should be in bold face. Units should be placed next to variables in parentheses. Figures should follow the text on the end of the manuscript and should be numbered consecutively using Arabic numbers and their position in the text should be indicated. Mathematical equations should be embedded in the text. Complex equations should be prepared with the aid of the Word Equation editor. All equations must be numbered, Arabic numbers, consecutively in parenthesis at the end of the line, as presented:

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CIP - Каталогизација у публикацији Народна библиотека Србије, Београд 33

Singidunum Journal of Applied Sciences : economics, management, tourism, information technology and law / editor-in-chief Milovan Stanišić. - Vol. 9, No. 1 (2012)- . Belgrade (Danijelova 32) : Singidunum University, 2012- (Loznica : Mladost grup). 28 cm Dva puta godišnje. - Je nastavak: Singidunum revija = ISSN 1820-8819 ISSN 2217-8090 = Singidunum Journal of Applied Sciences COBISS.SR-ID 188621836