Summer 2013 SAMT Journal

The swiss

technical A n a ly s i s Journal

Sommer Herbst Autunno estate Automne été Summer Autumn 2013

The Swiss Association of Market Technicians GenÈvE • Lugano • ZÜrich

• Summer 2013 • The Swiss Technical Analysis Journal

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Zürich

Willkom m e n

Benvenuto Bienvenue

Welcome

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Genève l

From the President’s Desk

Lugano

Dear SAMT members & industry colleagues The first launch edition of “The Swiss Technical Analysis Journal” was a great success.

I would like to express my thanks to everyone involved with the SAMT Journal and to the growing support that we are receiving from the local and international financial community. It is our intention to publish the Journal three times per year.

Since the last publication in spring 2013, there were plenty of events across Switzerland, featuring a range of interesting technical and market-related topics. The year of 2013 is proving to be a very active one across each of our SAMT tri-lingual chapters; within the Zürich (German), Geneva (French) and Lugano (Italian) regions.

Our regional chapter heads do a really great job of organizing plenty of interesting events and they are willing to continue to build even more value for our SAMT members. Moreover, SAMT’s true strength is based on the growth and strength of its members and I wish to congratulate everyone that has achieved their CFTe diploma after the recent examinations, and also Jean-François Owczarzak for winning the prestigious Bronwen Wood Prize.

We are very proud of our SAMT member achievements and wish them much success with their future aspirations.

Yours sincerely,

Daniel Daniel Stillhart, President of the Swiss Association of Market Technicians (SAMT)

The Swiss Technical Analysis Journal • Summer 2013 •

SAMT Chapters and programmes

chapter meeting general information Geneva - Swiss French Chapter The Swiss French chapter meetings are co-ordinated by Ron William, Mobile: + 41 78 947 53 87

ronwilliamPR@gmail.com

Meeting location is often: Bloomberg | Rue du Marche 40 | 1204-Geneva

Time: 17:45-20:00

Lugano - Swiss Italian Chapter The Swiss Italian chapter meetings are co-ordinated by vivanalysis@bluewin.ch

Alberto Vivanti, Tel. + 41 91 966 11 67

Mario Valentino Guffanti, Tel. + 39 33 691 91 70 mario@guffanti.net Meeting location is near Lugano: Centro di Studi Bancari | Villa Negroni | 6943-Vezia (accessible by bus line #5). Time: 17:00-18:30

Zürich - Swiss German Chapter The Swiss German chapter meetings are co-ordinated by Daniel Stillhart, Tel. +41 79 692 52 92

daniel.stillhart@frankfurterbankgesel-lschaft.ch

Patrick Pfister, Tel. +41 76 588 76 79

trading_patrick@yahoo.com

Meeting location is generally: Hotel City | Löwenstrasse 34 | 8001-Zürich

Time: 18:00-19:00

2013 Summer Programme Calendar Tuesday, 9 July

Geneva Chapter Monthly Meeting

FinGraphs.com: Markets Made Easy Jean-François Owczarczak, CFTe, Management Joint Trust, S.A., Geneva

Location: Hôtel Bristol Genève | 10, rue du Mont-Blanc | 1201-Geneva

Tuesday, 17 September

Time: 17:45-20:00

Geneva Chapter Monthly Meeting

Katie Stockton, CMT, Chief Market Strategist, MKM Partners, Stamford, CT USA

Location: Bloomberg | Rue du Marche 40 | 1204-Geneva

September (date to be anounced)

Time: 17:45-20:00

Lugano Member Evening and Dinner

Location: to be announced

• Summer 2013 • The Swiss Technical Analysis Journal

The swiss technical Analysis Journal Volume One, Issue 2 Summer 2013

Journal Committee Mario V. Guffanti, CFTe + 39 33 691 91 70 mario@guffanti.net Ron William, CMT, MSTA + 41 78 947 53 87 ronwilliamPR@gmail.com Design & Production Barbara Gomperts +1 978-745-5944 (USA) bgomperts@gmail.com

Contents

From the President’s desk Daniel Stillhart

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The Swiss association of market technicians Chapters and Programmes

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Panel discussion featuring Robert Prechter & Martin Pring Ron William, CMT, MSTA

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A Book Review & Interview with Perry Kaufman Mario Valentino Guffanti, CFTe

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Cusp Catastrophe Theory: A Model for Technical Analysis Hank Pruden, Ph.D.

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SmartView Model Alessandro Angeli, CFTe, MFTA

21

The Volatility-Based Envelopes (VBE):

a dynamic adaptation to fixed width moving average envelopes Mohamed El Saiid, MFTA

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Markets made easy Jean-François Owczarczak, CFTe Follow SAMT on

The Swiss Association of Market Technicians GenÈvE • Lugano • ZÜrich

www.samt-org.ch

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The Swiss association of market technicians SAMT Achievers

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Board of Directors

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Journal Submission Guidelines and Advertising Rates

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Membership

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Education

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Partner Societies

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The Swiss Association of Market Technicians (SAMT) is a not-for-profit organization that does not hold a Swiss Financial Services License. It is the aim of the SAMT to promote the theory and practice of technical analysis, and to assist members in becoming more knowledgeable and competent technical analysts, through meetings and encouraging the interchange of materials, ideas and information. In furthering its aims the SAMT offers general material and information through its publications and other media.

The information provided on this Journal has been compiled for your convenience and made available for general personal use only.

SAMT makes no warranties implied or expressly, as to the accuracy or completeness of any information contained on the Journal. The SAMT directors, affiliates, officers, employees, agents, contractors, successors and assigns, will not accept any liability for any loss, damage or other injury resulting from its use.

SAMT does not accept any liability for any investment decisions made on the basis of this information, nor any errors or omissions on the Journal. This Journal does not constitute financial advice and should not be taken as such. SAMT urges you to obtain professional advice before proceeding with any investment.

The material may include views and statements of third parties, which do not necessarily reflect the views of the SAMT. Information on this Journal is maintained by the people and organization to which it relates. The SAMT believes that the material contained on this Journal is based on the information from sources that are considered reliable. Although all care has been taken to ensure the material contained on this Journal is based on sources considered reliable we take no responsibility for the relevance and accuracy of this information.

Before relying or acting on the material, users should independently verify its accuracy, currency, completeness and relevance for their purposes.

Conference Location InterContinental Mark Hopkins San Francisco One Nob Hill, San Francisco, CA USA Reservations +1 415.392.3434 (Group Code: QS9) Reservation Deadline: Monday, 9 September 2013 Room Rates Single Bed & Breakfast (one person): USD $307/night Double Bed & Breakfast (two people): USD $344night

Sponsorship Opportunities Benefits of Sponsoring: • Distinguishing your product in the marketplace • Developing new contacts • Feedback on brand • Networking & cross promotion • Personal access to a target audience More details available on the IFTA conference website.

• Summer 2013 • The Swiss Technical Analysis Journal

How will the NEXT few years be characterized?

Inflation, Deflation or both?

Panel discussion featuring Robert Prechter, CMT, President of Elliott Wave International & Martin Pring, Chairman of Pring Turner Capital, moderated by Ron William, CMT, MSTA, Founder & Principal Strategist of RW Market Advisory During the annual symposium of

Ron William: What is the best strategy to help preserve capital given your stances on either of the inflationary or deflationary pressures ahead?

the Market Technicians Association, April 2013, two of the world’s most renowned veteran market technicians, Robert Prechter, CMT, President of Elliott Wave International and Martin Pring, Chairman of Pring Turner Capital, shared their key insights during a moderated panel discussion with Ron William, CMT, MSTA, Founder & Principal Market Strategist of RW Market Advisory, on one of today’s most widely debated questions about Inflation & Deflation pressures and how both risk scenarios would impact your investment decisions and portfolio returns. Please select link to review the full online video.

Martin Pring: Our firm (Pring Turner Capital) has just come out with a new ETF (The AdvisorShares Pring Turner Business Cycle ETF) (DBIZ) and I think that would be the place to go. In the past, obviously, being long commodities has been a good place to be or commodity resource-based stocks or basic industry stocks have also been good places to overcome inflationary trends. So I see no reason why they wouldn’t still be a good idea.

Robert Prechter: I think it’s extremely hard to preserve capital. With the abandonment of real money in the monetary system, it’s become nearly impossible to be a quiet little saver, because wherever you put your money other people are going to get their hands on it. Or it’s possibly going to disappear overnight. So it’s one of the hardest tasks in the world. That’s why one of the things that I have been recommending in the past few years is actual cash. I mean cash stored away in a nice safe place or in multiple safe places. I think it’s going to become very handy.

Gold is the only real money. I believe Bitcoins will become real money eventually, but it’s gold at the moment.

Gold, however, is extremely overpriced and overvalued in my view, and I don’t think it’s a good buy at this time. Of course, I didn’t see it going this high in the first place. Still, I think we will have

another buying opportunity for gold later on, when everything bottoms.

Preserving capital is kind of tough. You might decide to have cash in different currencies such as the Swiss franc. But the world is always changing and we are always keeping our eyes open for where the dangers can be. As we saw in Cyprus, even if someone had a million Euros in cash stashed away, suddenly they couldn’t transport it out of the country.

In some of the countries that I mentioned earlier such as Norway, France and Sweden, they are talking about making it illegal to spend more than a thousand Euros in one transaction. So there are so many ways that your prudence can be thwarted. It’s a very difficult environment to preserve capital.

RW: Switching to the currency world, there is a growing debate on how either inflationary or deflationary pressures are likely to affect on the US dollar. What is your current view on the US dollar and how do you see that trend playing out?

MP: Well as I highlighted in my presentation, on monthly charts, the US dollar looks very strong here. I did an exercise last month looking at the longterm momentum of all the principal cross rates including the Euro, the Japanese yen, the Canadian dollar, the Australian dollar and the British pound and they all favoured the US dollar on a long-term basis. So it seems to me that the proof is the US dollar is likely to move up, not as I said before, because it’s a great currency, but because all the others are so much worse.

The Swiss Technical Analysis Journal • Summer 2013 •

RP: I agree with Martin on this and the way that he put it in his speech is exactly right. When we look at the dollar index we are not looking at the purchasing power of the dollar, we are only looking at the dollar’s performance related to other currencies. So my opinion about the question is, which currency is likely to be deflating the most? That’s the one that is likely to go up more, because as debt starts to dissolve and disappear, remaining dollars and euros will be more valuable. That’s why cash is always worth something in a deflationary situation.

or more specifically, between the years of 1929-1931 can be pretty violent. So those are two of the key determinants of yield on a long-term basis.

RP: I think yields will go up if we have inflation, surely, and I believe they will go up if we have severe deflation for the reasons that I went over. In fact, when Greece went through its period of austerity, rates soared into double digits.

That’s the type of risk you have within a deflationary environment. It sucks buying power from all the other places like a black hole.

Despite this factor, One thing to keep my shop has been in mind is that the “The history of [interest] rates is that they bullish on the dollar Federal government index for quite are tied into two things; one is the amount currently pays of commodity or CPI inflation... Then of some time, mostly out about 6% of course, the other one becomes the credit because of the very its budget just to aggressive number default risk and if that becomes pretty high, cover interest. So if of vocal bets against then that will send up rates too. But that Treasury rates start it, all the people who tends to be more of a temporary thing, rather to go up, it would have been saying the than a [long-term] trend driver. But still, be a really bad sign US dollar is likely to even those temporary moves as we saw in for the budget. crash, or it’s going the 1930s, or more specifically, between the to zero, thanks to years of 1929-1931 can be pretty violent.” RW: The next the US Federal question, on the - Martin Pring Reserve. We felt that current US stock market outlook, was an impossible is probably one that I received the psychology for a continuing falling dollar. We don’t think the bull market is most number of requests [from leading institutional representatives and many over yet; it still has a long way to go.

MTA symposium delegates]. The US RW: One of the interesting points in both of your presentations was the similar perspectives on long-term US Government yields, suggesting an exhaustion and potential (upside) reversal, in terms of both the cyclical and secular trend. Can I ask the both of you about the potential psychological drivers behind that within either an inflationary of deflationary cycle?

MP: The history of rates is that they are tied to two things; one is the amount of commodity or CPI inflation that takes place which is about the closest correlation that you can come to on any particular relationship with bond yields.

Then of course, the other one becomes the credit default risk and if that becomes pretty high, then that will send rates up, too. But that tends to be more of a temporary thing, rather than a [longterm] trend driver. But still, even those temporary moves as we saw in the 1930s,

stock market has recently posted new all-time highs, driven by relatively strong breadth and a historically strong fouryear cyclical recovery. How sustainable is the current bull-trend and what parallels may exist from prior secular bear trends, notably the 1973 peak, which many industry analysts are highlighting as a potential road map template.

MP: I don’t know because my work does not forecast magnitude or duration of trends, unless I have a price pattern or something similar that would just give me an objective. All I can do is follow the direction of the indicators and right now my longer-term indicators, the ones that measure the primary trend, the majority of them are suggesting that prices are going to go higher and the trend is up.

One of the really strong characteristics of a typical bull market in stocks is usually when short-term interest rates start to move up and as we know the Fed had

• Summer 2013 • The Swiss Technical Analysis Journal

kept rates down to zero and so we don’t have a sign of a top at this point.

So I can’t tell how far it’s going or when it’s going to get there, all I can say is that right now all my indicators are bullish and therefore I am bullish, notwithstanding a short-term correction, obviously. But until that stuff starts to turn, I’ve got to stay bullish. I’ve learnt the lesson the hard way, that if I tell the markets what to do, then I am usually wrong and end up with blood on my face.

RW: What about the psychology in prior secular bear markets? What key lessons are important and are there any parallels that we should be aware of for now and the eventual endgame of a secular bear market?

MP: Well having said that I am bullish on the primary trend, of course, my work suggests that we are still in a secular bear market for inflation-adjusted stocks. We are still about 20% from the peak in the S&P 500, so we could still see a 20% rise and still remain with a secular bear market or trading range.

RP: Well I should have learnt more lessons the hard way, but I can tell you flat The things that I’m looking for to out that I am as bearish as I can possibly suggest that I am seeing an end to the be in studying 200 secular movement, years – well 300 or a downward years really when When Frost and I wrote our book way back movement in realyou throw in Britain in 1978, we said there is a big bull market adjusted rates in coming and it’s going to lead to what we – of stock price stocks, would be called grand super cycle top, and I think the movements.

This things like the S&P/ is one of the most fact that we have had these multiple manias Case-Shiller price is a reflection of that model working. For amazing junctures earnings ratio which that I have ever seen. example, in 2000 we had the all-time high typically registers to Now, I felt the same in the NASDAQ; you know, that’s the only a number of 6 times index that rose a hundred times, just like way in 2000 and the at the end of a bear same way in 2007. margin debt did. In 2006, 2007 and 2008 market, yields on we had three manias packed in together.

In fact, I couldn’t the S&P 500 are We had the peak in real estate in 2006, believe investors got usually 6-7%, they a second chance, we had stocks in 2007 and commodities in are currently 2-3% much less this third 2008, packed together very closely. - Robert and currently the one. In the decline Prechter Shiller ratio is about of 2009, how many 23 times. people said “Oh if I Moreover, the Tobin could just get to breakeven, I would get Q ratio which measures the replacement out of the market”. Well okay, now they value of stocks typically peaks at a secular are more than breaking even, but are they peak at $1.15 or something like that and getting out of the market? ends the secular bear at around $.30. Last We just had a record in January of inflows I saw about three or four months ago it was into mutual funds, and the last time it about $.80. So I would be looking for a lot was that high was during Septemberof these fundamental indicators, which I October of 2007. So for the third time really regard as sentiment indicators, to we have had peak indications within the be moving to those extremes. stock mania. I think we are setting up, RP: I agree 100% with that. We have not for the first time, a reversal in all three seen a classic bear market low since 1982, markets: stocks, commodities and bonds. which is the last time those figures where So I think that we have a triple whammy coming up. I certainly would not want to in bear market bottom territory. We also saw them in 1974, 1942 and 1949, which own anything. I think it’s pretty safe to be short, personally. But I have been wrong were all great buying opportunities. plenty of times, so please don’t do what I We have seen nothing like them. There tell you to do. have been no corrections worthy of a major bear market low. We got a nice panic in 2008-2009, but it was from really high levels, and some of the indicators The Swiss Technical Analysis Journal • Summer 2013 •

that I showed you never even corrected from the high of extreme optimism and extreme complacency. But it’s coming up. You know, markets go up and they go down, and the world is never going to be a place where we are always optimistic or always pessimistic.

When Frost and I wrote our book way back in 1978, we said there is a big bull market coming and it’s going to lead to what we called grand super cycle top, and I think the fact that we have had these multiple manias is a reflection of that model working. For example, in 2000 we had the all-time high in the NASDAQ; you know, that’s the only index that rose a hundred times, just like margin debt did. In 2006, 2007 and 2008 we had three manias packed in together. We had the peak in real estate in 2006, we had stocks in 2007 and commodities in 2008, packed together very closely.

This time gold made a new all-time high along with stocks. Stocks have continued for another year, but I still think that this is a lagging sort of exhaustion move. With new highs peaking last year, I think that’s the beginning of the end, the beginning of the turn downward. But we will see.

We have seen things stretch farther than normal, twice already. As I have said several times, maybe hedge funds will go from thirty times leverage to a hundred and fifty times leverage. Who knows?

RW: A question in line with the title “Inflation, Deflation or Both?” What are each of your views on the potential fusion (or duality) between inflation and deflation? Part of this will be down to timing (i.e. long-term structural deflation, interrupted by short periods of cyclical inflation or vice versa).

MP: We have the cycles that alternate between inflation and deflation. In fact, inflation breeds its own deflation, because if you have a huge run up in commodity prices for example, that means oil and food prices go up and that sucks out purchasing power and also pushes up interest rates, causing the economy to correct. So I believe that it’s a transitional continuation of the two. The only thing different is the degree that happens in each cycle.

RP: I’m pretty much in agreement. I think that we started to see a change to deflationary psychology between 2000 and 2006 on a very long-term basis. It takes time for these things to develop.

People talk about austerity. You know the Federal government is even scaling back its budget by a small amount. They are arguing about it, and that’s something new. The psychology is slowly seeping to another side of the ledger.

On a short-term basis, yes, it is cyclical.

Between 2006 and 2008 we had deflation.

Since 2009 we’ve had a reflationary trend, and that’s the one that I think has lost its upside momentum. It hasn’t quite rolled over in the US, but it has already rolled over in Europe. Now that the cyclical is joining the secular its looks like a very interesting time in the years ahead.

RW: On a final note, I would like to ask Robert Prechter if he could kindly share a few words of insight on the study of Socionomics and its focus on causality ahead of your up and coming annual conference.

RP: [“Socionomics is the study of social action that expresses social mood.

Social mood arises endogenously from unconscious herding impulses inherited through evolution, and is patterned according to the Wave Principle”]. The following week we have our third annual Social Mood Conference in Atlanta, Georgia.

It’s a great gathering of minds, really brilliant people, from academia to the professions. It is one long day with 12 different speakers. We discuss social mood and the effect of social mood on markets, culture and society. So come join us if you can. Look it up on the web for more information at www.socionomics.net (Read more: Socionomics Explained and follow on Twitter: @Socionomics).

Investing in the Second Lost Decade by Martin J. Pring, Joe D. Turner & Tom J. Kopas Part One & Part Two Video Series that accompany the book.

Conquer the Crash: You Can Survive and Prosper in a Deflationary Depression

by Robert R. Prechter, Jr. The world’s few deflationists: www.deflation.com Financial and Socionomic Theory, new DVD: “Robert Prechter at Oxford, Cambridge and Trinity”; read about it at www.socionomics.net To contact the moderator of this interview: Ron William, CMT, MSTA Email: ronwilliamPR@gmail.com Website: www.ronwilliam.com

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Book Review

Title: Author: Publisher and date:

Trading Systems and Methods (Fifth Edition) Perry J. Kaufman John Wiley & Sons – NJ – Jan 2013 – 1,212 pages

A Book Review & Interview with Perry Kaufman Mario Valentino Guffanti, CFTe

The Review The term “heretics” of finance was the nickname for technical analysts coined by Professor Andrew Lo, based on the fact that the academic world, at the beginning, saw technical analysis as a sort of alchemy and thought that technical analysis was to financial analysis as astrology was to astronomy. Despite these first historical misgivings, a high number of academics have studied technical analysis and have come to several interesting conclusions regarding its benefits and pitfalls2.

1

For that reason we can say that technical analysis, as body of knowledge, has been built thanks to trading practitioners, who studied the market indepth and built their first sound theories, and also by subsequent studies from the academic world that, mainly in the last decades, have reinforced some of technical analysis axioms.

We also have the support from a third category of people, who do not come from an academic world, but have a strong scientific background. This is the case of Perry Kaufman who began his career as a “rocket scientist,” first working on the Orbiting Astronomical Observatory (OAO-1), the predecessor of the Hubble Observatory, and then on the navigation for Gemini, later used for Apollo missions, and subsequently in military reconnaissance. In 1971 he became involved in the futures markets and has remained there.

There is a certain connection between the construction of a trading program and the world of rockets; in fact, the earliest systematic programs used exponential smoothing, a technique developed in aerospace for estimating the path of missiles.

Perry Kaufman is definitely one of the scholars of reference in the field of technical analysis with regard to trading systems. One of the cornerstones of Kaufman’s work has been the book Trading System and Methods, first published in 1978, and considered “the most authoritative and comprehensive work” in the industry.

In this article I will review the new fifth edition of that work, published in January 2013, trying to figure out if it is simply a reprint of the fourth edition with some updating, or a work in its own right, distinguishing it from previous editions.

Kaufman’s book is one of the Chartered Market Technician Level 2 Exam reading assignments.

At first glance it could be seen by the student as very difficult to digest its contents: two kilos of book with 1,212 pages, plus a website containing more than 400 programs and spreadsheets.

But in reality, it is a book where you don’t need to finish all the 1,212 pages to grasp the concept and value of the book itself. It can be read non-sequentially, in selected pieces, without losing context. It is possible to learn the basics of an argument after reading just a few pages.

For this reason this book has been compared to an encyclopedia of trading systems, or to a comprehensive guidebook and cookbook of trading methods.

The Swiss Technical Analysis Journal • Summer 2013 • 11

But in reading this fifth edition you see that there is another new peculiarity that has also been highlighted by the author: the added coherence from one section to another, and from one chapter to another. The search for an attempt to make the material flow from section to section as a continuous learning process. That is just not to give some blocks of recipes about trading, but to build a disciplined, coherent framework and a step-by-step course that provides the opportunity to increase our own culture on this subject in a critical and constructive way.

The objective of the author is to supply a complete understanding of the tools and techniques needed to develop and/or choose a trading program that has a good chance of being successful. There is no one Holy Grail technique, because all the experts in this field understand that it is not possible to know what will happen in the future; instead, the book evaluates the conditions under which certain methods are likely to do better, and situations that will be harmful to specific approaches. It is unlikely that any two traders will develop exactly the same system, but the challenge is to find a system that will adapt to future changes, that is, it should be robust, and the greater the knowledge of the trader, the more likely it will succeed.

To have a trading method that works in many different situations, and keeps working for as long as possible, is to have a robust solution.

Because of its importance, there are comments throughout the book addressing the robustness of various methods and ways to enhance that quality.

But the main enhancement that we can find throughout the book, and which distinguishes this new edition from the older ones, is the concept of risk control, from the individual trade level, to the strategy rules, to the portfolio.

The previous edition was published in 2005, and from that period until today we saw too many black swans3 in the financial markets.

That has demonstrated the forecasting or measuring risk in this “new normal”4 financial environment is not useful. Kaufman has shifted his attention to the management and control of risk, that is, more reactive and useful than the old solution.

The book is richer by 38 pages than the fourth edition, but the content is much greater. This is because all the TradeStation and spreadsheet programs disseminated in these pages have been removed and collected in a website built just for this new edition. On that website it is possible to download a large amount of material. As of the end of April, it contained 43 Excel spreadsheets, 25 MetaStock new functions, and for TradeStation we had 140 indicators, 117 strategies and 98 functions. That means more content than the previous edition, especially in the arbitrage section.

The book is structured in four parts: first we have an introduction, where the author speaks of the role of technical analysis and describes the resources and the objectives of the book (chapter 1). The second part is dedicated to the foundations: basic concepts and calculations (chapter 2) and charting (chapter 3).

The central part of the work is about trading techniques (chapters 4-20): the book remains organized in the same way, with the types of strategies covered starting with trend-following, momentum, cycles, and seasonality, then moving to the more complex arbitrage, intraday trading, and pattern recognition. In the last part we have the way in which we can build robust trading systems (chapters 21-24).

The Interview Mario V. Guffanti (MVG) - Hi Perry, it’s a great pleasure having you in an interview about your new fifth edition of “Trading Systems and Methods.”

Perry Kaufman - Thank you, Mario. It is my pleasure to talk with you.

MVG - What are the main changes and additions that have been made to this new edition?

Perry Kaufman - If you don’t mind, I’ve made a brief list of the changes because I knew you would ask this question: 1. I’ve made the notation consistent throughout the book, where before I used the notation of the various works that I was drawing on.

2. I’ve moved all the code and large tables to the website and only show a small piece of the tables. That allowed me to keep the book the same size but put in much more content.

3. I’ve tested nearly all of the “systems” in the book, and coded them, where before I may have simply summarized the concepts and formulas.

4. I’ve added more systems overall and in particular in the arbitrage section.

5. I’ve added risk analysis and more description throughout the book because I wanted to be sure that I was being clear. I’ve added some important concepts in the chapter on risk.

6. I’ve removed some old material and some sections that seemed to be repeated or of little value. I need to continue to do much more of this if the book is going to stay the same size.

7. I’ve added my concept of “noise” in chapter 1 and tried to explain its implications to all systems.

8. I’ve been more vocal about directing the reader towards some methods and away from others, or showing that they are very similar. For example, with long-term trend following and with typical momentum indicators, the results are nearly the same if you choose the right calculation period.

Most of the charts and examples have been updated. Some readers may have a hard time relating to gold at $500 when it’s $1,500.

MVG - If we look for a definition of what is technical analysis in the main classical books used as a basis to learn and study this discipline, I mean the cornerstone books also used in the first level of examination for technical analysts, such as Murphy5, Pring6, and Edwards and Magee7, the topic is defined as the study of price, using charts to forecast the movement of future prices, or the identification of trends. In your introduction you affirm that technical analysis is no longer just the study of chart patterns or the identification of trend, but it encompasses intramarket analysis, complex indicators, mean reversion, mathematical forecasting, and the evaluation of test results.

How much do you think your concept is really applied in the professional field and what has been the advantage for you in having this kind of forma mentis?

Perry Kaufman - It’s true that technical analysis started as chart interpretation. Even today I’m sure that every trader looks at a chart to confirm whether the market is in an up or down trend, or looks overbought or oversold. Even when the trading is entirely systematic, it is safe to confirm your signals by looking at a chart (at least from

12 • Summer 2013 • The Swiss Technical Analysis Journal

time-to-time). But I feel strongly that technical analysis has evolved because we identify trends and extremes automatically now. By using a computer instead of a pencil and ruler, we are able to find more situations, trade more markets, and create a risk-adjusted portfolio where we could never do that manually. Even high-frequency trading can be just identifying “micro-divergence” instead of macro patterns.

It’s really the same thing we’ve always done, just made faster and faster.

Drawing trendlines across the bottom of swing lows can be done with a computer, and various formulas for trendlines (moving averages, linear regression) have replaced the manual approaches, and perform well. And, large investors seem to want a systematic solution because discretionary trading can be successful, but can also be unreliable and difficult to manage. Many feel that exploiting certain market patterns, whether trending or meanreverting, have a more predictable outcome than chart interpretation, or fundamental analysis.

It is also possible to analyze world markets, and identify when those markets go out-ofline. Without a computer programmed to identify anomalies, it would be impossible to take advantage of all the opportunities.

One of the biggest challenges of “technical analysis” is to develop systems that show realistic results. At the beginning of computerized testing there was a significant failure due to overfitting. Most analysts have now learned that the “best” historic results are not likely to show what will be returned in the future. Taking a massive set of test results and reducing them to something realistic is what I would now call “the Holy Grail.” And I think we are getting closer to doing that. We can never be perfect because future price patterns will never be the same as past patterns, so no past results will represent the future. But it can be close in the sense that you can estimate the likely returns, and the risk associated with those returns, over some reasonably long time periods. You just never know how the profits and losses will distribute in the future.

MVG – The events in international financial markets in recent years have led to reconsider the risk factors in the investment decision process. You affirm in your book that understanding how to reduce risk before the fact is much more productive than identifying it afterward. For that reason you introduced risk analysis throughout the book. An academic study published at the beginning of 20138 demonstrated that institutional portfolio managers who consider technical analysis to be very important for their investment decisions, outperform those who did not use it, especially during down months, that is, in negative market environments. Can we say that your new book, by reconsidering the role of risk analysis, could be considered not a really updated edition but a work in its own right?

Perry Kaufman – I hope so, and you’ve hit on the difference between “risk measurement” and “risk management.” Since 2008 risk has taken on a different dimension. Before that, the typical belief was

that diversification into different markets was enough. That turned out not to be true. What is true is that “money moves the market,” not fundamentals. When there is market stress, everyone pulls their money out, causing all markets to reverse. That caused a correlation of 1.0, and a very, very unhappy situation for investors.

The book now takes the philosophy that trying to predict which market or which system will work best in the future is an unproductive approach. When you apply equal risk to every trade, equal risk to every sector, and so on, you are saying that you cannot know what the future will bring, but that over time, we expect our trading to work. I believe that is both the safest approach to risk management and a major step towards bringing expectations and reality closer together.

Trying to predict future risk is clearly never going to be perfect. Using past data can only reflect the risk in that data, so more data is always going to be better. The most common ways of measuring risk, annualized volatility and value-at-risk, are both good measures of current risk, but the only control over future risk is capping leverage. For many traders the idea of capping leverage means they get lower returns. But they also don’t get wiped out.

In futures, there is already built in leverage, typically 4:1 when you consider holding funds in reserve. If you are leveraging up in lowvolatility periods, then you need to cap that added leverage at not much more than 3 for a number of reasons explained in the book.

Then you have compounded leverage of 12:1, which seems more than enough. There are some UCITS funds that don’t allow leverage of more than three times the market exposure, which may seem very low, but certainly serves their purpose of controlling future risk.

I would also like to point out that diversification into different strategies, such as trend following and arbitrage, is much safer than diversification into different markets. Again, we have become aware of that because of the failure of 2008. Trading different strategies will maintain the integrity of the portfolio through a much wider range of market performance.

MVG - When I began reading the book I noted that chapter 2 has a new part about “standard measurements of performance.” You say that these performance measures will be used throughout the book when comparing different systems and they will be discussed further in chapter 21, System Testing. Could you explain how this differs from the fourth edition?

Perry Kaufman - This edition is much more complete with regard to testing systems. To allow readers to compare results, I’ve chosen the most popular statistic, the “information ratio,” the annualized returns divided by the annualized volatility (standard deviation). I believe that is the single best measure, although other statistics can also be important. So it is the combination of more tests, better display of results, and consistent use of the information ratio that should help readers compare one method with another.

The Swiss Technical Analysis Journal • Summer 2013 • 13

MVG - How would traders decide which type of system would be best for them? Are there general rules of thumb or do you have your own method to solve this problem?

Perry Kaufman - That’s a very difficult question. Most traders are not a “blank slate,” they have preferences such as trend following or shortterm trading. If that is the case, then they can go to the chapter on that strategy and compare the rules and results of many approaches. They will need to concentrate on the reward to risk ratio, but they may want frequency of trading or larger profits per trade. Those are all personal decisions, but important ones. You will never be a success by trading a system that fights with your personality.

If you have no preference, then I suggest you start with long-term trend following. It’s easy and it works. It doesn’t demand much time, and entering the orders at a specific time is not critical. As you develop more skill, keeping some part of your portfolio in trend following still makes sense. Then you need to look for a strategy that gives you diversification. That would mean pattern recognition, arbitrage (for example, pairs) or some other mean reversion program. It will mean faster trading and keeping an eye on the market more, so that might not work for someone with a full-time job. But the point is to find some other way of trading that would complement trend following. My own favorites are the Taylor Trading Technique, intraday breakouts, and pairs, but they must all be adapted to the trader’s style and carefully tested. The book gives guidelines for doing this correctly.

MVG - In the medical field we have moved from a physical semiotics to instrumental semiotics in the last few years. That is the where the good old medical doctors were competent to generate a diagnosis with a high probability of accuracy through a physical examination of the person before confirming it with an instrumental diagnosis. Today, relying too much on machinery could diminish the quality of the treatment, and focusing too much on technical readings and instruments for a cure may end up with the wrong analysis. Keeping the holistic approach seems the best course. It seems to me that the same is also happening in the world of trading systems, one point that you have highlighted in your book: namely the use and abuse of the computer. At the time of Charles Dow, when the use of computers was non-existent, those who created the first trading rules were heavily focused on the markets, on their price curves, and the psychology behind them. What is the secret to keeping this mindset in this super-technological world and having a sound and underlying premise to base our trading ?

Perry Kaufman - You’ve hit on a brilliant question, can a computer replace a person in making these decisions? I think the simplest way to view it is to compare a person who uses the full power of a computer to optimize a strategy, putting in as many rules and formulas as possible, without regard to whether any of those are meaningful. I’ve seen this done with neural network applications. The idea is to let the computer tell you what works and doesn’t work. Let it discard all the unnecessary data. I find that the completely wrong approach. You cannot find a successful system by data mining. The results will look brilliant but have no chance of working.

The only way to find a successful trading strategy is to understand the market and to observe its patterns. You then arrive at what we both call a “sound premise.” For example, you believe that interest rates are the result of monetary policy, so you use long-term trend following to track the effect of that policy on interest rate futures. Or, you decide

that Hewlett-Packard and Dell should show similar price movement, so you want to arbitrage them when they move apart. Both are based on a fundamental understanding of the market, not on technology. Of course, having decided that arbitrage is a great way to trade, you can now use technology to speed up the trading signals and – voila! – you have high-frequency trading. So the answer is “holistic,” that is, you combine the common sense of the trader with the power of technology, but the traders common sense is the more important part.

MVG - In your new edition you’ve added some new subsections.

I saw three associated with the topic: “Early Exits from a Trend” (chapter 8), “Kaufman on Stops and Profit Taking” and “Entering a Position” (chapter 23). Can you tell why these were important enough to merit new subsections?

Perry Kaufman - Some of these deal with both the technique and philosophy of entering and exiting. For example, if you’re a long-term trend follower, then exiting with profits, or using stops, fights with the underlying strategy. In order to have profits from trend following you need to capture the “fat tail,” those very big profits that offset all the small losses. If you add profit-taking or stops to your trend system and exit while the trend is still intact, then you risk missing the really big profit and your system will eventually fail. So that these extra rules must be combined with a way of re-entering the trend trade so that you don’t miss that rare big profit. I try to give the reader an understanding of the problem, the exceptions, and some examples of how to solve the problem. I think it’s an important addition.

MVG - The Adaptive Market Hypothesis9 affirms that markets are not always efficient, nor are they always irrational: they are adaptive. The behaviour that may seem irrational is, instead, behaviour that has not yet had sufficient time to adapt to modern contexts. Therefore, fixed investment rules that ignore changing environments will almost always have unintended consequences, and pattern recognition, in any form, may yield important competitive advantages. These axioms seem to be almost a paraphrase of what you wrote when describing the search for the robustness of a trading system: your rule number two being that the characteristics of a system with the best forecasting ability is that it must adapt to changing market conditions. In addition, I also found very useful the chapter about price shocks, which can be considered a very important part in the construction of a trading system to avoid catastrophic losses. Can you tell us in an Occam’ Razor style (“One should not increase, beyond what is necessary, the number of entities required to explain anything”), your view about this topic?

Perry Kaufman - The market itself evolves. In the 1990s, Toby Crabel published his book on intraday breakouts where he used fixed points to define the breakout. For example, if T-Notes opened at 110 and rallied 4/32nds, then we buy. But 4/32nds doesn’t work if the market has a different volatility. You entered either too soon or too late. And then we all know that price movement, even across different markets, has become more correlated. In the subprime collapse of 2008 all the markets moved together, not because of fundamentals, but because money moves the market. From that, we have evolved a much better way of managing risk.

Another part of this question is “How long will a system work?” I can’t answer that. Some continue to work, such as trend following, but other pattern recognition systems only work for a short time. I can say that you must monitor the performance and be able to recognize

14 • Summer 2013 • The Swiss Technical Analysis Journal

when a system is no longer doing what it should, before you lose all your money. A system developer might want to read Dietrich Dörner’s book, The Logic of Failure, because it explains the importance of monitoring your work.

As for price shocks, yes, they are rare but important events that can cause you to fail. You can’t ignore them, so I give various ways you can deal with them and still survive.

MVG - Martin Pring defined technical analysis as an art. Antti Ilmanen, fund manager and researcher, wrote that investment activity is both art and science: however, a good scientific background can enhance the artist. What’s your opinion?

Perry Kaufman - Of course I believe that a scientific background is a great advantage, but common sense and discipline will work also. You don’t need to be a rocket scientist, but you do need to be systemactic, that is you should have clear rules that you follow. If you are skilled at using development software, such as TradeStation and MetaStock, then you must test your work correctly and accept bad results. While discretionary traders may make huge profits from time to time, my own approach is to create a system that grinds out profits, with a certain level of risk, over time. And, I think that approach has become more popular among both traders and investors.

MVG - The book is written very clearly, but it is also very challenging with its 1,212 pages. What kind of advice would you give to the first-time reader, or the trader who is just starting?

Perry Kaufman - I try to give an overview of the topics at the beginning of each chapter, so I would start simply by reading the first page or two of each chapter. Then go back to the chapters that seem most interesting to you. The chapters each progress from simple to more complex, so you can stop any place and pick it up later. Or, if you have an idea of a method that interests you, you can always look it up in the index and start there.

MVG - You dedicated your book to your wife Barbara, and in the preface you thank Barbara for her everlasting support that is only enhanced by rolling her eyes whenever you say that “this is my last book, ever.” Did you make this promise again?

Footnotes 1 A. Lo and J. Hasanhodzic – The Heretics of Finance – Bloomberg Press – 2009 2 See A.Lo and J Hasanhodzic – The Evolution of Technical Analysis – Bloomberg Press – 2012 - Chapter 7, 8 and C. D. Kirkpatrick & J. R. Dahlquist – Technical Analysis – 2 ed. - Chapter 4 – Pearson Education – 2011; 3 The term “Black Swan” was created by Nassim Taleb, Distinguished Professor of Risk Engineering at New York University’s Polytechnic Institute, to indicate an isolated event that does not fall within the normal expectations, because nothing in the past may indicate its existence; 4 “The New Normal,” is a term that Bill (William H.) Gross coined in March, 2009, to define the economic landscape for years, or decades, to come. “When the U.S. and global economy reset after the crisis, [the global economy] will look different,” says (Mohamed) El-Erian of PIMCO. “This has implications for investment strategies, how you run a business and what you offer your clients.”

5 Murphy, John J.: Technical Analysis of the Financial Markets, New York Institute of Finance, New York, NY, 1999; 6 Pring, Martin J.: Technical Analysis Explained, 4th (or current) Edition, McGraw Hill Book Company, New York, NY, 2001; 7 Edwards, Robert D. and Magee, John, Technical Analysis of Stock Trends, 9th (or current) Edition (2001-­2008), John Magee Inc., Chicago Illinois 2001; 8 Smith, Faugère & Wang – 2013 Head and Shoulders Above the Rest? The Performance of Institutional Portfolio Managers Who Use Technical Analysis - http://papers.ssrn.com/sol3/papers. cfm?abstract_id=2202060 9 Lo – The Evolution… - Chapter 8 – Adaptive markets and Technical Analysis

Perry Kaufman - I always promise and it’s always not true.

MVG - This reminds me an aphorism attributed to Winston Churchill: “There are three great things in the world: the oceans, the mountains, and an engaged person.” Thank you, Perry.

Mario Valentino Guffanti, CFTe is a Financial Advisor, Certified Financial Technician and Researcher. He is the Assistant Vice President of the Swiss Italian Chapter of the Swiss Association of Market Technicians (SAMT) and also a Lecturer in Technical Analysis at the Centro di Studi Bancari in Vezia (CH)

The Swiss Technical Analysis Journal • Summer 2013 • 15

l

Genève

Geneva Chapter

22 April Event Guest speaker: Bruno Estier, MFTA, MSTA, Bruno Estier Strategic Technicals, Geneva.

The event was held at Credit Suisse.

events 22 April, 30 May & 13 June 2013

30 May Event Guest speaker: Michael Reisner, Head of Equities Technical Analysis at UBS Investment Bank, Zürich.

The event was held at Bloomberg.

13 June Event Guest speaker: Andrew Pancholi (center), Leading Cycle Specialist, London.

The event was held at Credit Suisse.

16 • Summer 2013 • The Swiss Technical Analysis Journal

Cusp Catastrophe Theory: A Model for Technical Analysis Hank Pruden, Ph.D.

Technical analysts suffer from too much data, not too little. The superabundancy of data probably leads them to employ too many statistical indicators, many of which are redundant, conflicting, or downright confusing.

As a result, technicians sub-optimize: they have too many opportunities (excuses) for making buy and sell decisions. These leave technicians prey to fear and hope emanating from within themselves and to social pressure closing in on them from without. No wonder there exist that stigmatic indictment of the chartist fraternity: when advisors hold a consensus opinion which is extremely bullish or bearish, they are almost invariably wrong.(1) That the technicians have a spotty record is not surprising if one examines the theoretical frameworks or models which these chartists use to guide the construction, interrelation and interpretation of their indicators. In fact, theoretical frameworks are conspicuous by their absence. Little exists beyond simple verbal anchorings to “supply and demand,” “mass psychology,” “fear and greed,” “inertia,” and similar global notions. Technicians skills and interests seem to lie outside of model building. Typically, technicians love to create indicators with which to predict the behavior of stocks or averages. Give them a few positive correlations and they hatch anew system for beating the market.

Models are the weak link in the market (technical) decisions support system (see Figure 1.) The technicians’ role is to answer money managers’ questions on when optimal peaks and troughs are reached by conducting (largely statistical) analysis of data according to models of the market. Models are ideas of how the world works and are therefore guides to seeking out and evaluating what is interesting and worthwhile in the data.

What is lacking in the arena of market timing is a comprehensive, unifying, theoretical model. Indeed, the paucity of sound, unifying frameworks plagues the social sciences in general, and stock market analysis in particular. Until recently, a major, new general model was simply unavailable.

But now the promise of a vast and powerful paradigm has become available with the discovery of Catastrophe Theory.

Catastrophe Theory “Catastrophe theory is a new mathematical method for describing the evolution of forms in nature. It was created by Rene Thom who wrote a revolutionary book “Structural Stability and Morphogenesis” in 1972, expanding the philosophy behind the ideas.(3) It is particularly applicable where gradually changing forces produce sudden effects. We often call such effects catastrophes, because our intuition about the underlying continuity of the forces makes the very discontinuity of the effects so unexpected, and this has given rise to the name.

The theory depends upon some new and deep theorems in the geometry of many dimensions, which classify the way that discontinuities can occur in terms of a few archetypal forms; Thom calls these forms the elementary catastrophes.

The remarkable thing about the results is that, although the proofs are sophisticated, the elementary catastrophes themselves are both surprising and relatively easy to understand, and can be profitably used by scientists who are not expert mathematicians.”(4)

Figure 1 A manager uses a market decision support system (MDSS) to learn about the business environment and take action with respect to it.(2)

In a pioneering effort, Zeeman attempted to show how the elementary catastrophe, the CUSP CATASTROPHE model, could explain the unstable behavior of stock exchanges.(6) He believed a similar model could be applied to currencies, property markets, or any market that admits speculators. In essence, Zeeman held that all the pertinent mathematical features of a stock exchange could be synthesized into a single concept, the Cusp Catastrophe.

The Swiss Technical Analysis Journal • Summer 2013 • 17

Equilibrium Surface The model posits two parallel surfaces.

The upper behavior or equilibrium surface is represented by a price index such as the Dow-Jones Industrial Average. This behavior surface is further sub-divided into a top sheet representing bearish behavior. Each point on the behavior surface is an equilibrium juncture between supply and demand, even though incremental and transitory.

Near the center of the behavior surface lies the catastrophe model’s most interesting feature a fold curve or cusp. What this suggests is that there are no equilibrium (turning points) available until the top sheet is reached after a buying stampede or the bottom sheet is reached after a selling panic. Notice that the abstract model shows the behavior surface curving over to a threshold point, after which comes the panic sell-off. One can visualize top reversal patterns, bottom reversal patterns and breakouts at the thresholds. Obviously, the thresholds are points at which to sell or buy, which is precisely how current technical theory and practice instructs us to act.

Control Surface Since the behavior surface is the dependent variable, there must exist some independent variable(s) which account for the index or to which the index may be attributed. In Exhibit 2, the independent variables are fear and greed.

The model featured in this article (Exhibit 2) presents fear and greed as two normal but opposing factors lying on either side of the cusp. The placement of fear and greed as conflicting variables is an interpretation by this author. The approach given here to the control variables differs sharply from Zeeman’s original model. Zeeman hypothesized that there are two types of investors, fundamentalists and chartists, or investors and speculators. To him it was the excessive, speculative behavior at the top which set up selling panics. However, his version did not envision buying stampedes.

Fear and greed are not viewed as single state variables in Exhibit 2; rather they vary along spectrums from lesser to greater degrees. Fear, for example, may be viewed as ranging from euphoria to confidence to hope to concern to worry to panic; in other words, fearlessness to fear or optimism to pessimism. Greed may be defined as ranging from low to high levels of greediness, such as when greedlessness or parsimony leads to overselling and

undervaluation, and covetous drives lead to overbuying and overvaluation. A different perspective is to view fear as activating selling or supply and greed as activating buying or demand.

Why don’t fear and greed simply cancel each other out, leaving a stable, neutral market index? The reason is because fear and greed are oppositional variables held together in dynamic tension – they are reflected in the struggle between. the bears and the bulls.

According to the Cusp Catastrophe Model, the conflict between fear and greed is the motor force which drives the market. The price index at any one point reflects the relative strength of these bullish and bearish forces.

Cusp Model in Operation Now let us imagine Exhibit 2 in operation.

The flow of the market index takes place over a smooth surface composed of equilibrium points. Changes in the control variables, fear and greed, have unique responses on the behavior surface. The dynamic process of the model causes the index to seek out local points of stable, albeit temporary, equilibrium.

Starting at a bear market low, where the market index is on the lower at-tractor sheet, the level of greed (demand) is suppressed by the level of fear (supply). Mounting greed gradually overcomes fear until the edge of the sheet is reached, at which point the market breaks out of an upside reversal pattern via a catastrophe jump to the top sheet. The index Exhibit 2 A CUSP CATASTROPHE MODEL OF A STOCK EXCHANGE

(Exhibit 2 shows a diagramatic rendition of a Cusp Catastrophe.)

18 • Summer 2013 • The Swiss Technical Analysis Journal

then flows along a rising channel on the top sheet until the bullish potential is exhausted.

At that point, both greed and fear are high.

Finally, as fear overcomes greed the market index reaches a threshold on the top sheet, then plunges to the bottom sheet via a bearish catastrophe jump.

What is dramatically different about this dynamic flow is that when both fear and greed are high and in opposition, the behavior surface solution is bimodal: within the fold curve zone a slight divergence in a control parameter can trigger either a bull catastrophe or a bear catastrophe.

Predicting which way the index will jump out of a bimodal or horizontal equilibrium trading range becomes less uncertain when the antecedent levels of fear and greed are known. Intuitively we can imagine the probable course of security prices if we frighten a group of greedy investors after there has been a substantial rise in the market index.

Salient Properties What are the salient properties of the Catastrophe Theory model, and what are their stock market counterparts?

middle sheet representing least likely behavior has been omitted for clarity. Finally, the Cusp Catastrophe implies the possibility of divergent behavior.”(5)

1. Biomodality, 2. Catastrophic jump, 3. Hysteresis, 4. Inaccessible zone, and 5.

Divergence are squared up with their stock market equivalents in the accompanying table. (See Exhibit 3)

Applications The Cusp Catastrophe model shines a spot–light upon the importance of price formations immediately before the mark up or mark down “ jump “ phase. The key chart patterns are triple descending price peaks during side ways top formations and triple ascending price peaks during side ways bottom formations. A prime example of this phenomenon is the right-angle triangle price formation. In a forthcoming article in the SAMT Journal, I shall illustrate another application of Cusp Catastrophe Theory which at the same time adds a new schematic to the Wyckoff Method of technical analysis.

“Five properties characterize phenomena that can be described by the Cusp Catastrophe. The behavior is always bimodal in some part of its range, and sudden jumps are observed between one mode of behavior and the other. The jump from the top sheet of the behavior surface to the bottom sheet does not take place at the same position as the jump from the bottom sheet to the top one, an, effect called hysteresis.

Between the top and bottom sheets, there is an inaccessible zone on the behavior axis; the

Henry (Hank) Pruden, Ph.D.

Exhibit 3 Salient Properties of Cusp Catastrophe Theory

The Swiss Technical Analysis Journal • Summer 2013 • 19

Dr. Pruden is a private investor, a lecturer at Golden Gate University and a member of the Board of Directors of the Technical Securities Analysts Association of San Francisco. http://www.hankpruden.com/

Lugano l

Lugano Chapter and the Centro di Studi Bancari event 27 May 2013

The 27 May event, organized by Nicola Donadio of Centro di Studio Bancari di Vezia and Mario Valentino Guffanti, Assistant Vice President of the SAMT Lugano Chapter, saw the participation of three speakers: Alessandro Angeli, MFTA, Alberto Vivanti, Vice President of Lugano Chapter, and Ron William, CMT, MSTA, Vice President of Geneva chapter.

From L-R: Ron, Nicola, Mario, Alberto, and Alessandro.

20 • Summer 2013 • The Swiss Technical Analysis Journal

SmartView Model Alessandro Angeli, CFTe, MFTA

An Introduction to the SmartView Model I have been always amazed by the capacity of a closing moving average to provide, during trending markets, support and resistance areas and profitable buy & sell signals.

Aware of the limits of moving averages, I have tried to develop something, without departing too much from the averages’ basic idea, which was able to work not worse during trending markets but much better during other kinds of movements.

After reading many technical analysts’ reports and specific technical analysis books, the first thing I have noticed is that generally closing moving averages are plotted on barcharts or candle-charts and not on close-only charts. The second thing I have observed is that analysts usually ask the closing moving averages to provide, during bullish trends, support areas near the lows of the price-bars and, during bearish trends, resistance areas near the highs. Furthermore, it’s generally accepted that a buy signal is generated when the price closes above the closing moving average and that a sell signal is generated when the price closes under the closing moving average.

In my opinion these interpretations are not wrong, but they contain something that doesn’t persuade me completely. Why should I use an algorithm (the moving average) based on the closing price hoping it will provide support areas near the lows of the price-bars and resistance areas near the highs? Closing prices are usually above the lows and under the highs; and in any case they are different.

Rather than focus on closing prices, I believe that support and resistance should be determined using high and lows prices, since high and low prices are specifically geared to ideas of support and resistance. So rather than examine moving averages of closing prices for support or resistance, it might be better to use moving averages of lows and highs to determine support and resistance respectively.

And something else could be observed also about the classical definitions, explained above, of the buy & sell signals. Surely they are correct because everything is based on the closing price. But if we try to imagine a buy signal when the price closes above the highmoving average and a sell signal when the price closes under the low-moving average, the signals can be considered much stronger.

What You Should and Shouldn’t Ask of Moving Averages

Moving averages are generally considered trend-following indicators because their signals are profitable during trendingmarkets and they often become wrong when the market moves sideways.

So the first thing you shouldn’t expect from a closing moving average is that it works well during trading-ranges. But an other thing you shouldn’t expect is that a particular closing moving average (for example the 15-periods one) works well in all the trends which are developing on the chart. First of all note that I define a trend as bullish if it’s possible to identify on the chart rising highs and lows and that I define a trend as bearish if it’s possible to identify falling highs and lows. As said before, a closing moving average tends to be a support in an uptrend and to become

a resistance in a downtrend. However, in order to get good results, trends have to be enough extended in temporal terms. In fact, if it doesn’t happen, a closing moving average (for example the 15-periods one), which is able to support an uptrend for a long-time, couldn’t have the time to become an efficient resistance in a short-term movement in the opposite direction, even if the new trend has the same slope. This happens because the change of direction of the closing moving average is generally quite slow and so, if the new trend is not enough extended, the average could be unable to represent it before its end.

Furthermore, in order to obtain profitable buy & sell signals, uptrends and downtrends should have more or less the same slope. In fact if the trends have consistently different slopes it’s very difficult that a particular closing moving average (for example the 15periods one) is able to provide good signals with all of them.

Figure 1 shows the weekly chart of the Eur/ USD with the 15-periods closing EMA. It’s easy to notice that its signals are profitable during long-term or middle-term trends with more or less the same slope (B and D) and that they become wrong in short-term trends

Figure 1: Eur/USD (weekly data) and the 15-periods closing EMA. The Swiss Technical Analysis Journal • Summer 2013 • 21

(A and C) and during sideways movements as well (E).

Figure 2 shows the same Eur/USD chart of figure 1, except the MAC is plotted.

Some Solutions to Improve the Moving Averages’ Signals

Although the MAC is not easy to use because the two lines tend sometimes to make a mess in the chart, it’s possible to notice that, very often, the two averages provide efficient support and resistance areas.

Aware of the limits of the moving average in relation to the closing price, many technical analysts have conducted intensive research in order to develop a moving average which would be able to work well in almost all market conditions. The most of them concentrated the research on two of the three parameters that need and input by the analyst: the number of time periods (the length) and the calculation method. The two people who obtained the best results in this way are Tushar Chande and Perry Kaufman. They respectively developed the Variable Index Dynamic Average (VIDYA) and the Kaufman’s Adaptive Moving Average (KAMA).

Another person who also worked with moving averages is Jake Bernestein who concentrated instead on the third parameter, the price field, developing in this way the Moving Average Channel (MAC).

Bernstein’s MAC

Jake Bernstein tried to improve moving averages’ signals in relation to the price working with the price field. In one of his first books he explains that, inspired by concepts originally introduced in the 1950s by Richard Donchian, he departed from the traditional use of the moving average having conducted intensive research on moving average channels (MACs) which consist of a moving average of high prices and a moving average of low prices. Rather than focus on closing prices, he felt that support and resistance should be determined using high and low prices because usually resistance tends to be found near previous highs and support tends to be found near previous lows. His technique uses a moving average of high prices and a moving average of low prices in conjunction which form a Moving Average Channel that is used for determining support and resistance. More precisely when the trend of prices is up, the Moving Average of Lows (MAL) tends to act as support and when the trend of the prices is down the Moving Average of Highs (MAH) tends to act as resistance.

Jake Bernstein provides in his book a lot of examples but almost all of them are about intraday markets. Further on he suggests many different interpretations in order to use the MAC during trending or sideways markets and by aggressive or conservative traders.

The SmartView Model Explained The SmartView model is my contribution to the research in technical analysis with the ambitious purpose to improve moving averages’ signals in relation to the price.

It could also be intended as an attempt to complete Bernstein’s MAC in order to simplify its use and to identify more easily the real key levels of support and resistance it provides.

Two is Better Than One

I believe that the use of two moving averages, a moving average of the high prices and a moving average of the low prices could really lead analysts to a better interpretation of what is happening in the price-chart than the one they would have been brought just using a closing moving average in relation to the closing price itself.

I have this idea for two reasons. The first one is that this argument is logical and rational.

In fact, as said before, usually resistance tends to be found near previous highs and support tends to be found near previous lows.

So, it’s surely reasonable that rather than examine moving averages of closing prices for support or resistance, it might be better to use moving averages of lows and highs to determine support and resistance respectively.

Furthermore, if we consider the buy signal when the price closes above the high-moving

average and the sell signal when the price closes under the low-moving average, these signals can be considered much stronger in relation to the classical moving averages’ buy & sell signals.

The second reason is that in my experience this idea really works very well. I’ve tested it on stocks, currencies, indexes, commodities and bonds of different market places and in multiple time frames (from 5-minutes data to quarterly data) and I’ve very often obtained interesting results.

But unfortunately the use of the MAC is not so easy as it could appear. In fact when the MAC is plotted on the chart an accurate and careful analysis is needed to exploit all its potentialities. For example during an uptrend analysts could pay attention only to the MAL (which tends to act as support) and they could forget that also the MAH could be very useful. In the same way, during a downtrend, analysts could pay attention only to the MAH (which tends to act as resistance) and they could forget that also the MAL could be very powerful. But it’s also true that there are often a lot of times in which one of the two averages is completely useless and its presence on the chart makes only a confusion. Further on it’s not easy at all to appreciate the MAC during high-volatility sideways movements because the two averages are continuously penetrated.

In conclusion we could say that it is easier to work with a closing moving average rather than with the MAC, although its signals are probably less indicative.

But there is a last point I would like to talk about before going on. Sometimes it’s not easy to present technical analysis models in

Figure 2: Eur/USD (weekly data) and the MAC or the 10-periods exponential moving average of the high prices (MAH) and the 8-periods exponential moving average of the low prices (MAL).

22 • Summer 2013 • The Swiss Technical Analysis Journal

banks, funds or in other financial institutes because unfortunately money managers, financial advisors, bankers and customers have still a few knowledge of this subject. So it’s necessary, in order to create also a stronger interest towards technical analysis, to show and produce systems of which benefits could be rapidly understood. Figure 2 is complex for people who do not have studied technical analysis in depth.

The real key of my research consists therefore in an appropriate elaboration of the MAC based on programming, opportunely a technical analysis software in order that it shows the moving average of the low prices (MAL), the moving average of the high prices (MAH) or both of them exclusively when I really need them. The output of this programming is the SmartView model which I like to define as a new way of looking at price-charts.

An Easy Programming

The SmartView model is based on the relationship between the MAC, the closing price and the opening price in each trading period.

The Position of the Closing Price

The closing price has surely the major weight comparing to the other three prices (open, high and low) which form a price-bar. I don’t need to explain why. In fact this idea is generally accepted by the most part of technical analysts.

As a consequence, I think it’s very important to consider the closing price in relation to the MAC in each trading period.

The MAH, for its construction, can always be defined as a resistance moving average.

Then, if the closing price is above the MAH, we can presume that the resistance has been broken. If it happens, I think there is no need to see the MAH on the chart because prices are expected to rise and it’s useless to see a resistance under prices. To resume, I want to see the MAH on the chart only if the closing price is under the MAH. In the same way the MAL, for its construction, can always be defined as a support moving average. Then, if the closing price is under the MAL, we can presume that the support has been broken. If it happens I think there is no need to see the MAL on the chart because prices are expected to fall down and it’s useless to see a support above prices. That means I want to see the MAL on the chart only if the closing price is above the MAL. These are the two first conditions of the SmartView model and they are stronger than

the second ones which will be treated in the next section.

The Position of the Opening Price

Even if the opening price has probably the minor weight comparing to the other three prices (high, low and close) which form a price-bar, I think that it is in any case very important to take it into account in relation to the MAC. For example, if the opening price of a trading period is above the MAH, it means that it’s not working as well as resistance. Later, if the closing price of the same trading period will place above the MAL, it will be useless to show the MAH on the chart because it represents a resistance which hasn’t done its job well from the first price. Instead, if the closing price will place under the MAL, the MAH should be plotted on the chart because we can presume that in the next trading period the market will fall (a support has been broken) and it will be useful to have in advance a reference resistance value. In the same way, if the opening price of a trading period is under the MAL, it means it’s not working very well as support. Later, if the price of the same trading period will close under the MAH, it will be useless to show the MAL on the chart because it represents a support which hasn’t done its job well from the first price. Instead, if the closing price will place above the MAH, the MAL should be plotted on the chart because we can presume that in the next trading period the market will rise (a resistance has been broken) and it will be useful to have in advance a reference support value.

The SmartView Model

The SmartView model can be defined as a new way of looking at price-charts with moving averages. Its first aim is to help analysts to follow as well and easy as possible financial markets movements. The SmartView model appears on the price chart combining each trading period with alternatively: a green dot placed under the price-bar (the MAL value), a red dot placed above the price-bar (the MAH value) or two dots of two colours.

Besides providing information about the market direction and the real existence of a trend, the SmartView model furnishes also support and resistance levels which could be identified observing the exact position of each dot on the chart. As a consequence, the model is able to provide in every period, paying attention to the number and to the colour of the last dots, both stop loss and long & short entry levels. A buy signal occurs at the first trading period when the model plots only a green dot; a sell signal occurs at the first trading period when the model plots only a red dot.

Before going on, it is very important to notice that price levels provided by the SmartView model when the market is still open, should be broken with the closing price in order that the signal could be considered valid. For this reason, it’s useful to consider the model only at the end of each trading period and not during its construction. Obviously this condition must be fulfilled in all the technical indicators which are based on the closing price. However in the SmartView model this aspect has a lower weight. In fact the resistance and the support levels depend exclusively on the highs and on the lows and they are not based on the closing price. Therefore in some cases, if the market is trading sufficiently away from the highs or from the lows, it’s possible to have an effective resistance or support reference value before the end of each period.

Before plotting the SmartView model, it is possible to choose the moving averages’ calculation method (simple, weighted, exponential, triangular, Chande’s Vidya and Kaufman’s AMA) and their length. My default settings are: 10-periods exponential MAH and 8-periods exponential MAL. The Exponential Moving Average (EMA)-SmartView model can be written as an indicator in Omega code as:

Briefly, the model signals the probable presence of: • a bullish trend, when the SmartView model shows just green dots; • a bearish trend, when the SmartView model shows just red dots; • a trading range when the SmartView model shows dots of both the two colours.

The Swiss Technical Analysis Journal • Summer 2013 • 23

if (O<Xaverage(H,PeriodH)) then

look at the rectangles in the second part of the 2000 and in the 2003. The EMA-SmartView furnishes correct resistance and support levels absolutely sooner than the 15-periods closing EMA. Further on, during bullish (bearish) trends the EMA-SmartView provides interesting resistance (support) areas which, if broken, confirm the original trend. Consider the ovals in figure 4; this information is not given at all by the 15-periods closing EMA.

plot2(Xaverage(H,PeriodH),”Resistance”);

During Major Reversal Patterns

If (C<Xaverage(L,PeriodL)) then

During major reversal patterns (double bottoms, H&S, broadening formation, etc.) prices very often move sideways for a while even if the volatility remains in general quite high. For this reason a closing moving average usually provides wrong buy & sell signals.

EMA-SmartView : SmartView of Exponential Moving Averages.

Provided by Alessandro Alberto Angeli (c) Copyright 2004. All rights reserved.

Inputs: PeriodH(10), PeriodL(8); If (C>Xaverage(H,PeriodH)) then plot1(Xaverage(L,PeriodL),”Support”) else

plot3(Xaverage(H,PeriodH),”Resistance”) else if (O>Xaverage(L,PeriodL)) then plot4(Xaverage(L,PeriodL),”Support”)

Figure 5 shows the 60-minutes chart of the S&P500 Future (04-Sep), the EMASmartView and the 15-periods closing EMA. In the middle of the chart it’s possible to identify a double bottom pattern.

The buy & sell signals that the two indicators provide during this reversal formation, are very similar. However, in the rectangle, which underlines when prices move sideways, the EMA-SmartView gives interesting and correct support and resistance levels, especially in the oval, providing precious information which the 15-periods closing EMA is not able to furnish at all.

During Trading-Range Movements

Figure 6 shows the weekly chart of the DJIA, the EMA-SmartView and the 15-periods

Figure 3 shows the same Eur/USD chart of figures 1 and 2, except the EMA-SmartView is plotted. The model shows the support and the resistance levels exactly when I want and need them.

Advantages of Using the SmartView Model I believe that the use of the SmartView model leads analysts to a better interpretation of what is happening on the price-chart than the one they would have been brought just using a closing moving average in relation to the closing price itself. If the logical and reasoned arguments presented in chapter 1 and 2 haven’t yet persuaded the reader, I’ll try now to prove my purposes presenting some real examples in multiple time frames taken from different international marketplaces.

During Trending Markets

Figure 3: Eur/USD (weekly data) and the EMA-SmartView (default settings).

Figure 4 shows the monthly chart of the German DAX Index, the EMA-SmartView and the 15-periods closing EMA. The 15periods length has been chosen because, during trending movements, this average tends to be very similar to the EMA-SmartView with default settings and in this way it’s possible to do a comparison. Carefully observing the chart it’s possible to notice that, when the market is trending, the EMA-SmartView provides buy & sell signals very similar to the closing EMA ones even if, in my opinion, the EMASmartView works slightly better. However, from this point of view, we could say that the use of the EMA-SmartView instead of the closing EMA is not a handicap.

Considering now the function of support and resistance the two indicators provide, I think that the EMA-SmartView works better. Have a

Figure 4: Dax Index (monthly data), the EMA-SmartView (default settings) and the 15-periods closing EMA.

24 • Summer 2013 • The Swiss Technical Analysis Journal

closing EMA. When the market moves sideways the closing EMA tends to flatten and to place itself in the middle of the tradingrange, becoming completely unable to provide efficient support and resistance areas. Further on it gives a lot of wrong buy & sell signals, in particular when the volatility is quite low, as it’s possible to see in the rectangles drawn on figure 6. On the other hand the EMASmartView provides splendid resistance and support areas which really helps analysts to identify the trading-range bands. When the volatility increases but the market continues to move sideways (in the ovals) the two indicators provide more or less the same buy & sell signals.

Conclusion The SmartView model is first of all a trendfollowing indicator which seems to work very well, or at least not worse than a closing moving average. Furthermore it provides powerful information during low-volatility trading ranges; in these situations it is very useful, much more than a closing moving average. But unfortunately it’s not perfect. In fact it suffers high-waves movements and highvolatility trading-ranges. Anyway I do not ask it to work always. I’ve developed it to help me in my job (analyst and portfolio manager) in order to make good investment choices, especially about underweight and overweight

decisions, and in this way I’m fully satisfied.

On the other hand, the SmartView model could also be used as a trading system or as a trading method, but it is absolutely necessary to be aware of the limits that the SmartView model meets in high-waves movements and during high-volatility trading-ranges because in those periods wrong signals will be given. A solution could be combining the signals given by the SmartView model with other technical indicators. Personally, I use the model with the stochastic oscillator. It helps me to identify possible reversals and to understand if the market is in a positive or in a negative cycle.

References • Bernstein, J., 1995, The Compleat Day Trader, McGraw-Hill, USA. • Chande, T.S.,1994, The New Technical Trader, Wiley, USA. • Kaufman, P., 1995, Smarter Trading, McGraw-Hill, USA.

Figure 5: S&P500 Future 04-Sep (60-minutes data), the EMA-SmartView and the 15-periods closing EMA.

Figure 6: DJIA (weekly data), the EMA-SmartView (default settings) and the 15-periods closing EMA.

The Swiss Technical Analysis Journal • Summer 2013 • 25

Bibliography Achelis, S., 2001, Technical Analysis from A to Z, McGraw-Hill, USA.

Murphy, J.J., 2000, Analisi tecnica intermarket, Il Sole 24 Ore, Ita.

Bernstein, J., 1993, Short-Term Futures Trading, Probus, USA.

Nison, S., 1991, Japanese Candlestick Charting Techniques, NY Istitute of Finance, USA.

Bernstein, J., 1995, The Compleat Day Trader, McGraw-Hill, USA.

Nison, S., 1994, Beyond Candlesticks, Wiley, USA.

Bernstein, J., 1997, The Compleat Day Trader II, McGraw-Hill, USA.

Plummer, T., 2003, Forecasting Financials Markets, Kogan Page, UK.

Bernstein, J., 2000, Strategies for the Electronic Futures Trader, McGraw-Hill, USA.

Pring, M.J., 2003, Analisi tecnica dei mercati finanziari, McGraw-Hill, USA.

Castagnoli, E., 1991, Introduzione alla selezione di portafoglio, Coop. L. Milano, Italia.

Schwager, J.D., 1990, Market Wizards, Harper Business, USA.

Chande, T.S.,1994, The New Technical Trader, Wiley.

Chande, T.S.,1997, Beyond Technical Analysis, Wiley, USA.

Schwager, J.D., 1992, The New Market Wizards, Harper Business, USA. Schwager, J.D., 1996, Schwager on Futures, Wiley, USA.

Coliva, E., Galati, L.,1992, Analisi tecnica finanziaria, Utet, Italia.

Wagner, G.S. and B.L. Matheny, 1994, Trading Applications of Japanese Candlesticks, Wiley, USA.

DeMark, T.R., 1994, The New Science of Technical Analysis, Wiley, USA.

Wilder, W., 1978, New Concepts in Technical Trading Systems, HPC, USA.

Edwards, R., and J. Magee, 1966, Technical Analysis of Stock Trends, Amazon, USA. Eng, W.F., 1993, The Day Trader’s Manual, Wiley, USA. Fornasini, A., 1996, Mercati finanziari: scelta e gestione di operazioni speculative, Etas, Ita. Fuller, R., and J. Farrel, 1993, Analisi degli investimenti finanziari, McGraw-Hill, Italia.

Gabbi, G., 1999, La previsione nei mercati finanziari, Bancaria Editrice, Italia.

Hull, J.C., 1997, Opzioni Futures e altri derivati, Il Sole 24 Ore, Italia.

Kaufman, P., 1998, Trading Systems and Methods, Wiley, USA. Kaufman, P., 1995, Smarter Trading, McGraw-Hill, USA. Meyers, T., 1994, The Technical Analysis Course, Probus, USA.

Alessandro Angeli, CFTe, MFTA Alessandro currently covers the position of Chief Operating Officer at T&F Asset Management SA in Lugano, a company providing asset management services to private individuals and institutionals.

He is also adjunct professor of Financial Technical Analysis at Parma University and lecturer in the CFTe courses at Centro di Studi Bancari in Vezia. From 2001 until 2005 Alessandro worked as Strategist at RCF SA, a company providing innovative research in the field of quantitative and technical financial analysis.

Morris, G.L., 1992, Candlestick Charting Explained, Irwin, USA. Murphy, J.J., 1986, Technical Analysis of the Financial Markets, NY Institute of Finance, USA.

26 • Summer 2013 • The Swiss Technical Analysis Journal

The Volatility-Based Envelopes (VBE): a dynamic adaptation to fixed width moving average envelopes Mohamed El Saiid, MFTA

Abstract This paper discusses the limitations of fixed-width envelopes and introduces a new method that addresses these limitations. The new method utilizes the concepts of standard deviation and correlation in order to produce a dynamic adaptation to the fixed-width envelopes.

The paper also offers an example of a useful technique and some guidelines for applying the new method on price charts. The method will be referred to henceforth as the volatility-based envelopes (VBE).

Introduction Fixed-Width Envelopes Fixed-width envelopes (FWE) are two boundaries. Each boundary is placed at a fixed percentage above and below a simple moving average (SMA) of the exact same duration. The primary aim of using the FWE is to contain the price action fluctuations and hence, imply when prices have gotten over-extended in either direction. FWE are characterized by the same effects of lag and smoothness associated with their corresponding SMA.1 Unfortunately, due to the inherent lag effect caused by the FWE, prices would quite often move and remain outside the envelopes’ boundaries for a notable period of time. Despite some featured techniques adapted for the FWE that would accommodate and sometimes even depend on these occurrences2, the initial purpose as to contain the price action is not satisfied.

Bryan J. Millard suggested that in order to represent the trend properly and highlight active and dominant cycles using SMAs and FWE respectively, the statistically-correct plot would be to shift it back from the most recent data point by half the span of the SMA duration. This technique is referred to as centering the moving average. The rationale behind this argument is that since the FWE are properly plotted (centered), the price action fluctuations will be contained within the envelope boundaries.3 To its credit, the centered FWE manages to contain a larger amount of price action. However, it still produces a couple of challenges. As a result of the centering procedure, the envelopes values will terminate n-days prior to the most recent closing price, where n = (the SMA span – 1)/2. Moreover, the centered FWE are non-adaptive to the continuous volatility changes of the price action. Depending on the price volatility, this will still cause the price fluctuations to move and remain out of the envelope boundaries quite frequently (during high volatility phases), or not react with the envelopes at all (during low volatility phases).

Another attempt to address the FWE’s lack of adaptability to price volatility was made in the 1980s by John Bollinger. Adopting the statistical concept of standard deviation into the field of technical analysis, Mr. Bollinger introduced the Bollinger Bands (B-Bands). The B-Bands are two bands set at two standard deviations above and below a SMA calculated off the price action. In principle, the B-Bands aim at utilizing the standard deviation concept in order to identify rare and unsustainable price excursions and coin them as overbought (OB) and oversold (OS) conditions.4 The B-Bands manages to contain more price action within its boundaries, especially during trendless phases in price action where identifying OB and OS conditions using the B-Bands becomes quite valuable. However, there are certain price conditions on the near to short term horizon as explained by Bollinger, in which prices tend to breakout and remain outside either one of the 2-standard deviation bands for some considerable time. At other times, even if the price excursion was relatively brief, the price gain (or loss) would be quite considerable. These conditions will generally occur during trending phases and following periods of low volatility in price action and are dubbed by John Bollinger as volatility breakouts. The technique proposed by Bollinger relies on these volatility breakouts in order to initiate a position in the direction (favor) of the price breakout.5 Though very successful when properly identified in the price action, these volatility breakouts seem to argue against the general notion that price excursions occurring beyond two standard deviations are deemed rare and unsustainable.

Sustainable price breakouts from the B-Bands are primarily attributed to the difference in tendency and behavior of price action during trending vs. non-trending phases. During non-trending phases, price action visually exhibits a characteristic of oscillatory/mean reversion motion. During these events, price excursions are rare and unsustainable. While during trending phases, this feature becomes less dominant and further diminishes on the near to short term horizon as the trending phase grows stronger. This is attributed to the lagging effect of the SMA which visually appears clearer during trending phases. As you would recall from the B-bands calculation, the 2-standard deviations calculated are added to and subtracted from that lagging SMA to construct the upper and lower bands respectively.

Hence, the B-Bands do not fully resolve the lag effect of the SMA. Although the B-Bands succeed to achieve adaptability, the upper and lower bands do not inherit the smoothness of their corresponding SMA as they are relatively more erratic in motion than the latter. This does not allow them to be as suitable as centered FWE when attempting to highlight active and dominant cycles in the price action.

The Swiss Technical Analysis Journal • Summer 2013 • 27

Introducing the Adaptive Volatility-Based Envelopes (VBE) Using Volatility to Achieve Adaptability To address the drawback associated with the lack of adaptability of the FWE, we use the measure of standard deviation. Unlike B-Bands’ calculation, we use the historical percent changes of price returns of a security instead of the historical price action of that security.

Therefore, we can expect that approximately 95.4% of the daily percent change movements to be maintained within the percentage range of:

Since practitioners in the field of statistics and financial engineering have consistently hypothesized over the past decades that the percent changes in a stock price (or security) are normally distributed on the short term.6 Hence, we use this hypothesis as the basis for the VBE calculation methodology; once the standard deviation calculations were complete, the outcome was added to and subtracted from a SMA of the percent changes of price returns. Then, the outcome was added to/and subtracted from today’s (the most recent) closing value on a percentage basis and not over a lagged SMA of the price action. As a result, a dynamic adaptation to the envelopes’ boundaries can be achieved, while avoiding the inherent lag effect of the MA of prices.

The following steps will explain the VBE’s calculation methodology:

In order to translate those values into a price range for most recent closing value of the index, or in other words; the raw VBE, then:

Step 1: Calculate the standard deviation (σ) of the percent changes (or logarithm) of the daily historical price returns (σ).

The standard deviation is calculated over duration of 21 daily percent change values.

case of the index movement. Thus, a need to smooth out these boundaries is required.

Step 3: Smooth the raw VBE using weighted moving averages.

0.07% – (1.00% * 2) = – 1.93% (at 2 standard deviation).

In order to smooth out the raw VBE, we will use two centered weighted moving averages (CWMA) for both envelopes of the raw VBE. Using CWMAs instead of CSMAs mathematically results in a reduction of lagtime by approximately 40%. This means that instead of lagging the most recent price by (span-1)/2 as with the case of the SMA, the lag is reduced to be approximately equivalent (span-1)/3.34. 7

0.07% + (1.00% * 2) = + 2.07% (at 2 standard deviation).

2,190 * (1-1.93%) = 2,147.7 (lower raw envelope at 2 standard deviation).

2,190 * (1+2.07%) = 2,235.3 (upper raw envelope at 2 standard deviation).

In real life observations and mainly due to the non-linear nature of price action, the lag tends to be reduced down to equate (span-1)/4 instead of (span-1)/3.34. This means that – in real life price action – the lag of the 21-period WMA tends to approximate to 5-periods (and in some cases, 4-periods), but not 6-periods.

Plotting the raw VBE over the price chart Using the same calculation method presented above, we can regress and calculate a daily range for all previous historical closing values of the S&P 500 Index and then plot the outcome as shown in Figure 1.

Figure 1 depicts the S&P 500 Index line chart with daily closing values and the raw upper and lower boundaries of the calculated raw VBE. As observed, there exists a strong (almost identical) similarity between the closing values (line chart) of the S&P500 Index and both; the upper (red) and lower (blue) boundaries of the calculated raw VBE. Having said that, both boundaries are choppy (raw), as with the

Table 1 features CWMAs of different spans and the amount of lag attained by each

CWMA

Lag

span

periods

21.00

5.00

17.00

4.00

13.00

3.00

9.00

2.00

5.00

1.00

2.00

0.25

Step 2: Calculate the values of the raw Volatility-Based Envelopes (raw VBE).

The lower VBE = Centered (WMA (Close*(1 + (μ - (σ*2 Standard Deviation))), WMAPeriod), N)

Upper boundary of the volatility range at 2 standard deviations

The upper VBE = Centered (WMA (Close*(1+ (μ + (σ*2 Standard Deviation))), WMA-Period), N) S&P 500 closing values

Example: Assuming the following data: The last given price (S) of the NASDAQ Index is: 2,190.

Lower boundary of the volatility range at 2 standard deviations

The simple average (μ) of the percent change is: 0.07%.

The (σ) of the daily percent change is: 1.00%.

Figure 1 – S&P 500 Index – Line chart – Daily closing values – Normal scale

28 • Summer 2013 • The Swiss Technical Analysis Journal

The Smoothed Volatility-Based Envelopes (VBE) Now let us make a visual comparison between the smoothed VBE vs. both the centered FWE and the B-Bands. This comparison is shown in Figure 2.

Figure 2 visually depicts the advantages of the VBE over the centered FWE and the B-Bands.

The centered FWE failed to mechanically adapt to volatility changes during the movements of the S&P 500 Index, while the VBE was able to contract and expand in accordance to the decrease and increase in volatility of the S&P 500 Index movements. Meanwhile, unlike the B-Bands, the VBE maintains its boundary smoothness, relative to the corresponding moving average of the price action. And finally, the VBE managed to contain more price action than the B-Bands. The VBE is constructed with the primary advantage of its ability to identify overbought (OB) and oversold (OS) conditions in the price chart regardless of the trend status.

Using (ρ) to Forecast the Missing Data Points of the 21-Day CWMA As previously explained, the 21-CWMA has 5 missing data points, while the 17-CWMA has only 4. This means that we can use the last given value of the 17-CWMA and the (ρ) value of both variables from table (2) to forecast the 1st missing value of the 21CWMA as follows: Example: Referring to the data used in calculation, the last calculated percent change of the 17CWMA was 0.80%.

The last calculated value of the 21-CWMA was 1,122.30.

1,122.40 * [1 + (0.80% * 0.88%)] = 1,130.38

This value would be placed shifted back from the most recent closing value of the index by 4-days (since the 17-CWMA has only 4 missing data points).

Moving onwards, the following table (Table 3) shows the last calculated percent changes of the 13, 9, 5 and 2 CWMAs as well as the forecast of the 2nd, 3rd, 4th and 5th (i.e. last) missing values of the 21-CWMA. Using that same concept, we can now forecast the five missing data points of the smoothed VBE.

The calculated (ρ) value was 0.88 or 88% (from Table 2).

Step 4: Forecast the VBE’s missing data points using correlation.

To be able to forecast the missing data points of the VBE, we will use both the CWMA feature previously presented in Table 1, as well as the statistical concept of correlation (ρ). The aim is to use the correlation between the values of other CWMAs of lesser span (independent variables) with the 21-period CWMA or smoothed VBE (dependant variable) to forecast the missing data points of that smoothed VBE. It’s worth mentioning that all CWMAs of lesser span are selected with reference to the amount of their missing data points.

Then, the forecast of the 1st missing value of the 21-CWMA would be:

VBE are more receptive to any volaility changes in price action

Price excursions from the VBE are less than that of the B-Bands CMA Envelopes are not sensitive to the volatility changes in prices

The upper and lower B-Bands are more volatile in action than their corresonding MA

Example: Using the daily values of the S&P 500 Index, we calculate (ρ) matrix of the daily percentage change of a 21-day CWMA vs. the daily percentage change of a 17-day, 13-day, 9-day, 5-day and a 2-day CWMA over the most recent 63-actual data points as shown in table 2.

Figure 2 – S&P 500 Index – Candlestick chart – Daily closing values – Normal scale

Table 2 S&P 500 Index – correlation coefficients (ρ) of 21, 17, 13, 9, 5 and 2-day % change of CWMAs

21-CWMA

21-CWMA

17-CWMA

13-CWMA

9-CWMA

5-CWMA

2-CWMA

1

0.88

0.76

0.67

0.56

0.31

Table 3

13-CWMA

9-CWMA

5-CWMA

2-CWMA

0.86% 1,137.80

1.07% 1,145.99

0.93% 1,151.90

0.80% 1,154.77

The Swiss Technical Analysis Journal • Summer 2013 • 29

Figure 3 visually depicts the smoothed VBE (at 2-standard deviation) with a forecast of its missing five data points using the correlation methodology previously presented.

Using the VBE to identify over-extended price action on the price charts

Actual VBE values

The VBEs forecasted interval

Now that the VBE has been constructed, we will demonstrate a useful trading technique when applying it on price charts. Below are some essential guidelines to be followed when using the VBE. • Spot the most recent turning phase of the VBE (crest or trough) while it is occurring.

The turning phase must be associated with a price excursion. The VBE will guarantee to a high degree that any price excursions are unsustainable regardless of the trend.

• If a price excursion occurred at a low, wait for the price to return back inside the VBE range, and then initiate a long position (or buy-back an old short position) until the next VBE turn (in the opposite direction) takes place.

• If a price excursion occurred at a high, wait for the price to return back inside the VBE range, and then short, sell or reduce your position until the next VBE turn (in the opposite direction) takes place.

VBE estimates

Figure 3 – S&P 500 Index – Candlestick chart – Daily closing values – Normal scale

Needless to say, the appropriate trading strategy applied will depend on the direction of the overriding trend direction.

Figures 6 and 7 illustrate how to initiate buy and sell trades using the VBE. A buy signal is generated when prices break out of the lower envelope, and then reverted back inside

Figure 4 – EGX 30 Index – Candlestick chart – Daily closing values – Semi-log scale

A sell signal is generated when prices break outside the boundary of the VBE and resume back inside

Figure 5 – EGX 30 Index – Candlestick chart – Daily closing values – Semi-log scale

30 • Summer 2013 • The Swiss Technical Analysis Journal

Conclusion The VBE introduced in this paper manages to dynamically adapt to the volatility changes of the price action and thus, successfully contains the price action within a predefined standard deviation range. Accordingly, the VBE is consistently able to identify over-extended price action regardless of the trend status.

This is achieved without compromising the smoothness of its boundaries.

Nevertheless, the VBE is still left with a few challenges. Most importantly, is the fact that the most recent data points on the smoothed VBE are missing and were required a forecast. In this paper, we used the concept of correlation and applied it to moving averages of different durations in order to achieve a reliable forecast for the missing data points.

Still, the correlation figures tend to lose their significance as they approach zero, since a value of zero implies no correlation between the variables. Thus, the significance of the VBE estimated values will vary depending on the significance of the correlation figures

which tend to change more often than not.

Thus, one should always check the (μ) matrix values for statistical significance (i.e. at least above 0.5 and/or below -0.5).

References 1 Murphy, John J., Technical Analysis of the Financial Markets, New York institute of Finance, 1999.

2 Pring, Martin J., Technical Analysis Explained: The Successful Investor’s Guide to Spotting Investment Trends and Turning Points, McGraw-Hill, 2002.

3, 7 Millard, Brian J., Channels and Cycles: A Tribute to J. M. Hurst, Traders Press, 1999.

4, 5 Bollinger, John A., Bollinger on Bollinger Bands, McGraw-Hill, 2001.

6 Hull, John C., Options, Futures, and Other Derivatives, Prentice Hall, 2000.

Bibliography • Hull, John C., Options, Futures, and Other Derivatives, Prentice Hall, 2000.

• Mason, Robert D., Marchal, William G., Lind, Douglas A., Statistical Techniques in Business & Economics, McGraw-Hill/Irwin, 2002.

• Millard, Brian J., Channels and Cycles: A Tribute to J. M. Hurst, Traders Press, 1999.

• Bollinger, John A., Bollinger on Bollinger Bands, McGraw-Hill, 2001.

• Murphy, John J., Technical Analysis of the Financial Markets, New York Institute of Finance, 1999.

• Pring, Martin J., Technical Analysis Explained: The Successful Investor’s Guide to Spotting Investment Trends and Turning Points, McGraw-Hill, 2002.

• VIX White Paper, Chicago Board Options Exchange (CBOE), 2009.

• Data courtesy of Bloomberg and Reuters.

• Charting software courtesy of Equis International MetaStock v.9.1.

Mohamed El Saiid, MFTA, CFTe Stop-Loss

Buy here

Figure 6 – NASDAQ Index – Candlestick chart – Daily closing values – Semi-log scale Reduce here

Mohamed El Saiid is currently an Executive Director and Head of the Technical Analysis department for HC Brokerage (HCB), Cairo, Egypt. He started his career working for Momentum Wavers, Ltd., a Middle East Technical Analysis firm (2001-2004). He joined HCB as an associate/lead technical analyst (20042006). Later, he joined Unifund, a Geneva-based global private fund (20062007) as a Chief Technical Strategist/Co-Fund Manager to the Middle East investments.

Mohamed holds an MBA in Finance and is currently a Board Member, Technical Analysis instructor in the Egyptian Society for Technical Analysts (ESTA), as well as an Education sub-committee Member and a Board Nominating committee Member in IFTA. Mohamed authored several TA-related articles and developed several indicators including the Volatility-Based Envelopes (VBE) and the Implied Volatility Projection Range (IVPR).

This article was originally published in the 2012 IFTA Journal.

Figure 7 – NASDAQ Index – Candlestick chart – Daily closing values – Semi-log. scale

The Swiss Technical Analysis Journal • Summer 2013 • 31

l

Zürich

Zurich Chapter event 25 june 2013

Technical Analysis Trading - Algorithmic or Discretionary Presenter, Henrik Mikkelsen

32 • Summer 2013 • The Swiss Technical Analysis Journal

Markets made easy Jean-François Owczarczak, CFTe Increase Technical Analysis Penetration Ninety five% of the people that have access to technical analysis don’t use it. Why so ?

simple, visual and didactic way, using a preparametered standardised methodology over all asset classes and frequencies of observation.

Despite the fact that technical analysis platforms are becoming more powerful every day, most products remain quite sophisticated and in general are still reserved to the seasoned and professional elite. There seems to be a scarcity of value-added tools targeted at the newcomers, private investors or the time and technology constrained.

Define Your Investment Horizons: No financial decision can be taken without an investment horizon. Hence, there are no universal bear or bull indications. Each market participant must chose or adapt to a specific time frame which fits his investment style, return objectives, disponibility, transaction costs or simply character. FinGraphs displays frequencies ranging from historical Weekly and Daily charts to Live Streaming Intrahour (up to an automatic update every 5 seconds). In order to lead users to view time frames which are adapted to their profile, it has categorized these into different styles, each corresponding to a combination of three frequencies:

Since 1969, Management Joint Trust SA (MJT) has been advising institutional investors using its proprietary Technical Analysis methodology focused on Trends, Targets and Timing.* It is well aware of the on-boarding and communication constraints inherent to technical analysis (with each new user, the methodology needs to be taught, coached and regularly supported through face to face contact). This tailor made model is adapted to institutional business.

Now, What if You Were Targeting the Masses?

In order to increase penetration of and facilitates access to technical analysis, MJT launched its new FinGraphs platform in 2012. Simple, didactic and visual, FinGraphs is aimed at a large audience of market participants and delivers a powerful yet simple decision making, market monitoring and tutoring tool. It is a simplification of MJT’s institutional methodology with a large portion of the value added having been retained.

l Investor’s

View (historical Weekly, Daily,

Hourly), l

Trader’s View (historical 60 min, 15 min, 4 min),

l

Scalper’s View (live streaming 4 min, 60 seconds, 15 seconds),

l

Super Scalper’s View (live streaming 60 seconds, 15 seconds, 5 seconds).

Most users will focus on the Investor’s View where the investment horizon is measured in quarters down to weeks. More active participants will choose the Trader’s View for Intra-week, Inter-day market positioning.

Finally, if your style keeps you in front of your trading screens during the day, you’ll probably end up using the Scalper’s and Super Scalper’s views for true decision-making content up to an update every 5 seconds.

Visual Presentation Over Three Frequencies: Within each investment horizon (Investor’s, Trader’s or Scalper’s), FinGraphs presents an analysis over three frequencies of observation.

The purpose of this multi frequency presentation is to teach and encourage users to coordinate their analysis over different time frames by putting them into perspective. Hence, the upper half of each FinGraphs chart pictures a summary chart of price history upon which three rectangle time windows have been superimposed (labelled 1: Long term, 2: Medium term, 3: Short term).

The bottom half of each FinGraphs chart then presents these three rectangles (still labelled 1,2,3 and called “Time Boxes”) in a standardised format presentation for a quick

* (3T methodology as referenced in the Market Technician, No 70, June 2011, available on our website www.fingraphs.com in Home / About Us / Press Releases) Focus on the Essentials The platform pushes simple concepts that will help end-users focus on the essential elements of their financial decision making process: l

Define your investment horizon: are you an Investor, a Trader, a Scalper?

l

Within your investment horizon, view three time frequencies put into perspective (“Fractal made easy”)

l Use

simple instruments (bull/bear trend indications, visual price targets, oversold/ overbought risk oscillator, support/resistance levels using market stress)

l

Standardised methodology over all investment horizons and asset classes

l Entertaining

Coaching section using the “Driving a car / road signs” analogy

i.e. put all elements needed for financial decisions onto a single chart, presented in a

Copyright ©2012 - Management Joint Trust SA - www.FinGraphs.com

The Swiss Technical Analysis Journal • Summer 2013 • 33

“at a glance” analysis differentiated over three different time frames. Although, the different time frames are not related by fixed multiple factors, it is like a “fractal view” made easy with the same methodology being applied to all three frequencies.

Our coaching section compares this presentation to a roadmap: for example on the investor’s view the long term (weekly) is similar to a smooth ride on the highway, the medium term (daily) is compared to a main road with two way traffic and more halts and road signs. finally, the short term (hourly) is like driving on secondary roads, it implies shorter distances, multiple stops and many signs.

This visual multi frequency presentation combined with FinGraphs’ simple indicators allows for a quick “at a glance” analysis of any instrument. To say the least, it is very efficient way to quickly get a first impression / opinion on any instrument, on any time frame.

Simple Trend Indications

Visual Targets

To evaluate how well established and how far out trends are in their development, the Bull and Bear trend analysis is completed with colourful price targets beams, green for uptrend or red for downtrend. These end with an ellipse representing the probable price target zone (measured in terms of potential price range as well as time horizon period).

The price targets element is calculated based on MJT’s traditional measure of historic volatility, i.e. the width of its larger dark yellow standard deviation envelope (or “delta”). The calculation involves factoring this volatility by specific pre-set factors and then adding the result to a significant Top or Bottom to obtain potential price targets for the current price move. Setting these prices targets is a progressive process.

Every price move starts as being a correction.

Its rebound potential is usually 0.5 to 0.8 times “delta” from the last turning point. Once a price move makes it above the 0.8 times “delta” mark, it turns impulsive and has a strong chance of achieving its impulsive targets (1.3 to 1.7 times “delta” from the last important turning point).

In rare occasion, for very strong moves super impulsive price targets are calculated (2.3 to 2.7 times “delta”).

Time projections of these targets are drawn from a standardised measure of how long corrective or impulsive price moves should normally last.

These measures, which have been part of the MJT toolkit for years, are then adapted to fit each time horizon.

Visually, these price beams give a great sense of direction (red or green) and of how much potential is left in a price move (measured both in price and time potential). Combined with the Bull and Bear indications, they provided a precise and rapid assessment of the trend status over the three frequencies presented.

Risk Indicator and Market Stress Bull/Bear indications combined with target zones offer a great trend following monitoring tools.

Many FinGraphs users will probably stop here in their analysis. FinGraphs, however, presents two other indicators measuring exaggerations (the risk indicator) and market stress (stress points between the larger and smaller envelopes).

FinGraphs’ risk indicator is a bounded oscillator which moves from overbought to oversold.

Traditionally, MJT uses six oscillators per graph calculated over different time frames. For FinGraphs, it has retained only the longer term one to obtain less frequent but more robust exaggeration signals.

Market stress is measured when the shorter term white envelope contacts with the boundaries of the longer term dark yellow envelope. These contact points indicate that the short term trend has gone too quickly versus the longer term trend. A consolidation or a correction is imminent.

Taken separately, these two indications offer tentative top or bottom fishing opportunities

MJT’s Risk Indicator

Trend indications are represented by Bull and Bear figurines on each FinGraphs time box.

These are labelled with subtle “Think Positive” / “Think Safety” mottos as trends are a function of current and prior direction, not a hard recommendation of future price evolution.

FinGraphs “Bull” and “Bear” indications are calculated based on the direction of FinGraphs standard deviation envelopes and to a large extend on the direction of the larger one of them (the big yellow envelope). Its direction, which has been used for more than 30 years in many of MJT’s algorithms, shows strong inertia, i.e. it is a very stable trend indicator.

MJT’s Market Stress

Using these figurines, the user can get a first impression of trends in seconds (Long /Medium/ Short term: Bull/Bull/Bear or Bear/Bull/Bull, …) and hence better understand how major, secondary, minor trends interplay.

Copyright ©2012 - Management Joint Trust SA - www.FinGraphs.com

34 • Summer 2013 • The Swiss Technical Analysis Journal

against the prevailing trend. However, when used together, in an attempt to synchronise risk exaggerations and market stress, the resulting turning points are very robust, often preceding trend following instruments in signalling the emergence of a new trend. Combining these two instruments with price target exhaustion offers even stronger probabilities of reversal.

As described on the facing page, the FinGraphs methodology is simple and visual.

It helps you position yourself very rapidly on each frequency by identifying trends and evaluate their potential in terms of rewards and risks. Add the fact that you are constantly working with three frequencies and you have a true financial GPS.

Global Coverage for “All Investors and Traders”: FinGraphs market coverage is extensive with more than 5’000 instruments worldwide over all asset classes (single stocks, market and sector indexes, futures, trackers, Forex, swap rates, benchmark bond yields and commodities).

This basic coverage is presented in delayed format except for FX which is displayed in realtime. For newcomers, it is a unique platform to discover the world of investments and decision making in a simple and didactic format. For experts, it is a great screening and monitoring tool, at retail cost, to scan the world for ideas, correlations and relative opportunities.

have no limitations in terms of market delays.

Hence, they allow FinGraphs to create its shortterm Scalper’s and Super Scalper’s views as well as high frequencies market mosaics.

Private day-traders as well as professionals will find great value for money in these short term decision making live streaming charts. Graphs running Dukascopy prices (a Geneva-based FX broker) are already available through the platform covering 60 FX pairs as well as gold and silver. Several other providers are currently being integrated. They will bring additional coverage on CFDs (equity indexes, bond and commodity futures) as well as on major Blue Chips worldwide.

FinGraphs also integrates feeds from various brokers and OTC exchanges. These usually

Additional Market Monitoring Features FinGraphs also displays market components in a mosaic format. These mosaics can be set to include 4-16 instruments per page on a specific frequency (weekly to 5 secs). They are derived either from index constituents, pre-set lists by asset classes or the users’ own favourites selections.

On longer frequencies (e.g. weekly, daily), Mosaics are ideal tools to monitor market breadth, identify correlations or search for outliers/opportunities. The short term mosaics based on Intrahour frequencies are great monitoring tools for intraday price moves (live streaming).

Finally, for users with benchmarking needs, FinGraphs also proposes relative charts for most stocks against their reference market and sector indexes.

Copyright ©2012 - Management Joint Trust SA - www.FinGraphs.com

Copyright ©2012 - Management Joint Trust SA - www.FinGraphs.com The Swiss Technical Analysis Journal • Summer 2013 • 35

Education for Traders In the online trading world, there is an increasing demand from brokers for educational material and simple trading methodologies. The intention is to help clients trade more successfully in order to increase their life time in the markets and retain them as clients over a longer period. With its simple and didactic approach, FinGraphs offers an integrated answer which is both scalable and adaptable.

Simple Concept – Flexible Technology FinGraphs’ standard offering is available through the www.fingraphs.com website. More generally, the FinGraphs concept can easily be adapted to any markets or trading offering (e.g. trading platforms, paper media, blogs or financial websites). Our team is at your disposal to answer any questions and evaluate feasibility (support@fingraphs.com).

Front Office Solution for Bankers – Communication FinGraphs is also the ideal instrument to create a dialog between a banker and his clients.

FinGraphs offers Front Office Bankers and Advisory desks packages of multiple accesses which can be distributed to team members or clients using simple and confidential administrative functions. Using its simple methodology, bankers and clients will be able to discuss on common ground. In addition, these packages also include a Client Relationship Management tool (CRM): it allows an “account master” (banker) to view all queries done by his affiliated users (clients) on the platform.

This information is structured into a client profile, accessible on-line and pint-pointed to understand a client’s centres of interest in a matter of seconds, a powerful advisory tool to deliver more targeted advice.

Jean-François Owczarczak, CFTe In 2003, after 5 years in investment banking at Paribas and Deutsche Bank in London, Jean-François joined Management Joint Trust SA, Geneva. Today, he acts as Chief Investment Officer and Head of Business Development for the company.

He holds a Master in Business from the University of St Gallen (lic. Oec. HSG 1997) as well as the Certified Financial Technician certification (CFTe) and is a Bronwen Wood Prize Winner.

He is also a member of the Swiss and UK societies of technical analysts.

FinGraphs is a financial graphics platform conceived to make markets easy for all Investors and Traders (private and institutional).

The market coverage is global: 5'000 financial instruments worldwide including 4'000 single stocks, country, regional and sector indexes, Forex, Interest Rates, Commodities and Trackers “ Easy to use ” decisional tool with: 3 Time Dimension Graphs – Trends Identification – Targets Estimates – Risk Indicators – Price Exaggeration Real Time Live Streaming on Forex – Gold – Silver Subscription Terms from CHF 60. - per month

www.fingraphs.com

Management Joint Trust SA Rue de Hesse 1 – PO Box 5337 1211 Genève 11 – Switzerland T + 41 22 328 93 33 F + 41 22 320 07 04 www.mjt.ch www.fingraphs.com

3 Time Dimension Graphs

Trends Identification

Targets Estimates

Risk Indicator

36 • Summer 2013 • The Swiss Technical Analysis Journal

Price Exaggeration

SAMT Achievers

Gregoire Genolet, CFTe

I discovered technical analysis during my trainee program in asset management.

I understood quickly the benefit of this art that is unfortunately not taught at university.

Technical analysis helps me to understand the market, and I think, if you can manage it with fundamentals, you’ll reduce the risk of mistake.

What value does the CFTe qualification provide within your career?

The CFTe diploma allowed me to expand my knowledge and the course helped me to structure my analysis.

Jeremie Girod, CFTe

Markus Ilg, CFTe

After a master in Economics obtained in Paris (1995), a military service as a lieutenant in France (1996) and a first professional experience in the tourism industry in Chile during 1997-1998, I started my career in finance in 1999. I first managed the back office and the risk management department of a derivative-trading firm based in Ireland.

I then moved to Switzerland in 2001 to work on the SMI market as an option market maker.

I enjoyed market making a lot but at the same time I became more and more attracted with real commercial activities and decided to move into commodity. I trade and merchandise grain and oilseeds since 2005, and I am enjoying it a lot!

1998-2006 Buy-side analyst and fund manager at WestLB Mellon, Düsseldorf

How do you feel about achieving your CFTe diploma?

Really accomplished now with the last education I needed to complete my numerous set of skills and experience.

How useful was our SAMT Geneva CFTe Immersion Course in helping prepare for the exam...?

Very useful. It help me to focus my attention and effort in the right direction which is key given the wide range of theories and tools developed in technical analysis.

What value does the CFTe qualification provide within your career?

An important and key knowledge which has been achieved thanks to the high objectives set by the exam. And finally an official recognition within the industry.

2006-present Head of Portfolio Management at Union Bancaire Privée, Zürich How you feel about achieving your CFTe diploma?

I feel great. I am very happy that I made both exams in the first trial.

How did you develop a successful strategy in preparing for the exam...?

I started to prepare a long time ago. In 2010 I read the Murphy. And I thought about taking the exam.

It was the year of the soccer world championship. So, I gave up my plans to take the exam (soccer is very popular in Europe).

Time goes by...

In 2012 I thought again about the CFTe. It was the year of the European soccer championship...so, that time I decided to prepare for the exam after the championship.

My advice: it’s important to include key events in your exam preparation planning ;-) What value does the CFTe qualification provide within your career?

Accreditation of professional knowledge is becoming more and more important. It is not enough anymore that you believe you have the necessary knowledge in technical analysis. It’s important that you can prove it. I hope that more and more technical analysts realise that. It’s surprising that there are professional technical analysts that don’t have any professional accreditation.

The Swiss Technical Analysis Journal • Summer 2013 • 37

SAMT Achievers

NEXT CFTe Course 7-8 September See page 40 for details.

Bertrand Clavien, CFTe

Jean-Francois Owczarczak, CFTe

Bertrand Clavien started his carrier at Darier Hentsch & Cie in 1997, after which he joined Bordier & Cie’s private banking department followed by the Hedge Fund & business development team before heading to Monaco to chair the investment committee as well as create and manage the internal Equity and Alternative Funds. He is currently back in Geneva as senior portfolio manager.

In 2003, after 5 years in investment banking at Paribas and Deutsche Bank in London, JeanFrançois joined Management Joint Trust SA, Geneva, as Chief Investment Officer and Head of Business Development.

Bertrand Clavien graduated from the University of Geneva with a Certificate of Advanced Studies in Quantitative Portfolio Management and also holds a CFTe. How you feel about achieving the CFTe diploma?

se

Cour rsion e m II Im 2013 CFTe June

Happy, it is an accomplishment that pushes me to delve deeper into the field of technical analysis.

How useful was our SAMT Geneva CFTe Immersion Course in helping prepare for the exam...?

It was enriching as we shared differing point of views and approaches, pushing me out of my comfort zone in using technical analysis while also understanding the exam methodology.

Ron and Bruno truly dedicated themselves to giving their best to this course.

What value does the CFTe qualification provide within your career?

CFTe

II Imm ersion Cours March e 2013

An extra string to my bow. Technical analysis allows me to enhance my knowledge in market analyses, which is a considerable advantage in the current competitive environment. It also brings me closer to my clients as they generally feel more at ease with an explanation based on technical analysis as opposed to fundamental analysis.

He holds a Master in Business from the University of St Gallen (lic. Oec. HSG 1997) as well as the Certified Financial Technician certification (CFTe) and is a Bronwen Wood Prize Winner. He is also a member of the Swiss and UK societies of technical analysts.

How you feel about being awarded the Bronwen Wood prize?

“A bit surprised and very honored. It is also great news for the family as I represent the third generation of technical analysts in our family.”

How did you develop a successful strategy in preparing for the CFTe exam...?

“Read the books, summarized them, did all the previous exams. On the day of the exam, think like an advisor as most questions are taken out of real life examples and often relate to current dilemmas in the market. In this respect, reading up on current market publications also helps.”

What value does the CFTe qualification and the Bronwen Award provide within your career?

“We run our own market advisory firm in Geneva using our own approach to TA. The Bronwen Wood Award is an outstanding recognition for us. Personally, I’ve been advising clients day-in day-out for 10 years; CFTe was essential to broaden my TA knowledge (anyways, more a pleasure than a duty). It’s also great to be part of the CFTe holders here in Switzerland with the SAMT currently showing great “momentum”.”

38 • Summer 2013 • The Swiss Technical Analysis Journal

SAMT Board of Directors Daniel Stillhart President daniel.stillhart@frankfurter-bankgesellschaft.ch

& Officers

Patrick Pfister, CFTe Vice President and Head of Zürich Chapter trading_patrick@yahoo.com

Ron William, CMT, MSTA Vice President and Head of Geneva Chapter ronwilliamPR@gmail.com

Alberto Vivanti Vice President and Head of Lugano Chapter vivanalysis@bluewin.ch

Mario Valentino Guffanti, CFTe Assistant Vice President of Lugano Chapter mario@guffanti.net

Louis Grosjean Head of Treasury louis@grosjean.ch

Tim Straiton, FGA Head of Website Development info@stoploss.ch

The Swiss Association of Market Technicians

The Swiss Association of Market Technicians (SAMT) is a non-profit organisation Founded 1987 (Civil Code Art 60ff) of market analysis professionals in Switzerland, founded in 1987. SAMT is a member of the International Federation of Technical Analysts (IFTA).

Technical analysis is the study of prices and markets. It examines price behavior on an emprirical and statistical basis.

It extends to the study of all published information on price trends, volatility, momentum, cycles and the interrelationship of prices, volume, breadth, sentiment and liquidity. A comprehensive understanding of technical analysis requires a knowledge of statistics and pattern recognition, a familiarity with financial history and cycles.

SAMT encourages the development of technical analysis and the education of the financial community in the uses and applications of technical research and its value in the formulation of investment and trading decisions. SAMT has a wide range of activities including: n

Organising meetings on a broad range of technical subjects encouraging the exchange of information and knowledge of technical analysis for the purpose of adding to the knowledge of its members.

n

Preparing its members to sit for the Certified Financial Technician (CFTe) exams and the Masters level degree Master of Financial Technical Analysis (MFTA) in Switzerland. These exams are controlled by IFTA.

n

Developing CFTe preparatory courses.

Marco Zahner Auditor ma_zahner@bluewin.ch

The Swiss Technical Analysis Journal • Summer 2013 • 39

THE Swiss We would especially like to see contributions that draw from areas not previously examined, and/or topics tangential to technical analysis.

technical analysis journal The Swiss Technical Analysis Journal is a quarterly publication established

by The Swiss Association of Market Technicians (SAMT). It is compiled by a committee of SAMT colleagues.

The Swiss Technical Analysis Journal is essential reading for academics, students and practitioners of technical analysis in all arenas. It is an excellent reference source for anyone interested in technical analysis, containing a wealth of resource material.

Credibility And Recognition The Swiss Technical Analysis Journal has original contributions from its members covering developments in technical analysis in global markets.

The Journal’s aim is to reach leading practitioners and students of technical analysis throughout the world.

The Swiss Technical Analysis Journal is a professional resource. Its online publication on the SAMT website will make its work available as a future resource to the community of technical analysts.

Topics SAMT is seeking papers that cover developments impacting, either directly or indirectly, on the field of technical analysis; they may be drawn from such areas as: • Basic market analysis techniques • Indicators—sentiment, volume analysis, momentum, etc.

• Global and intra-global technical analysis • Styles of technical analysis • Data • The changing role of technical analysis in the investment community.

The above list is just a guide and should in no way be considered restrictive. We wish to make the Journal open to new and innovative ideas from all areas of technical analysis and those that connect with it.

Submitting Contributions Submission of contributions to ronwilliamPR@gmail.com

Material deadline for the Autumn 2013 issue

Language Contributions must be submitted in English with British grammar required.

Writing Style Papers should be written in a thesis style.

References All texts referred to in the paper must be appropriately referenced with a bibliography and endnotes (footnotes will not be accepted.)

Responsibility for the accuracy of references and quotations is the author’s. We expect the authors to check thoroughly before submission.

All references are to be included as endnotes. No separate list of references or bibliography should be provided.

Figures, Charts and Tables Illustrations and charts must be referred to by Figure Number and source (when applicable). Tables must be referred to

by Table Number and source.

Length of Contribution Papers should be approximately 1,200 to 3,000 words, with supporting graphs and charts.

Format We ask for submission in MS Word or other text format. PDF format will not be accepted. Charts and graphs may be in gif or jpeg, but we ask that authors also keep a tif format in case it is required.

30 September 2013

Advertising The Swiss Technical Analysis Journal is published three times a year and is published in A4 size, in pdf format only.

SAMT will accept advertisements in this publication if the advertising does not interfere with its objectives.

The appearance of advertising in SAMT publications is neither a guarantee nor an endorsement by SAMT. Advertising Policy Advertising is subject to approval by SAMT. All advertisements must be non-discriminatory and comply with all applicable laws and regulations. SAMT reserves the right to decline, withdraw and/or copy edit at their discretion.

Every care is taken to avoid mistakes, but responsibility cannot be accepted for clerical error.

Advertising Rates Rate

Size

Inside covers

750 CHF

21.0 x 29.7 cm

Full page

500 CHF

19.3 x 26.9 cm

1/2 page

350 CHF

19.3 x 13.4 cm

Payment Pre-payment by wire transfer is required for all ads. Bank details will be provided upon request.

40 • Summer 2013 • The Swiss Technical Analysis Journal

The Cost of Membership n Initial one time registration fee of CHF 50.

SAMT Membership

Samt encourages the development of technical analysis and the education of the financial community in the uses and applications of the technical research and its value in the formulation of investment and trading decisions.

SAMT offers the following benefits: n

The organisation of meetings on a broad range of technical subjects encouraging the exchange of information and knowledge of technical analysis for the purpose of adding to the knowledge of the members.

n

The organisation of presentations from guest speakers from around the world.

n

The possibility to sit for the Certified Financial Technician(CFTe) exams at a discounted rate. These exams are controlled by IFTA.

n

The “IFTA Update” - a quarterly newsletter from the International Federation of Technical Analysts.

n

Access to the SAMT database covering trading strategies, chart pattern recognition, technical indicators and a glossary of terms.

n

A generous discount on the annual IFTA Conference admission fee.

n

Annual membership fee of CHF 150. (The total cost for the first year is CHF 200.)

n

Only fully paid-up members have access to the member area.

n

The subscription cost for each subsequent year is CHF 150.

n

Subscription expiry results in blocked access to the member area. A standing annual payment order is therefore recommended.

Subscription Payments Please use the Register Here link below for executing your payment and don’t forget to make sure your name is mentioned in the payment (especially for members whose subscription is paid by/through their employers).

Also please note that by registering as a member of SAMT you declare that you have read, fully understand and agree to the content of the SAMTDisclaimer statement which appears below.

Payments are made to: Swiss Association of Market Technicians S.A.M.T. Swiss Postal account Nr. 80-52569-5 IBAN: CH77 0900 0000 8005 2569 5

Register Here

SAMT Disclaimer The Swiss Association of Market Technicians (SAMT) is a not-for-profit organization that does not hold a Swiss Financial Services License. It is the aim of the SAMT to promote the theory and practice of technical analysis, and to assist members in becoming more knowledgeable and competent technical analysts, through meetings and encouraging the interchange of materials, ideas and information. In furthering its aims the SAMT offers general material and information through its website and publications therein.

The information provided on the SAMT website has been compiled for your convenience and made available for general personal use only.

SAMT makes no warranties implied or expressly, as to the accuracy or completeness of any information contained on the SAMT web site. The SAMT directors, affiliates, officers, employees, agents, contractors, successors and assigns, will not accept any liability for any loss, damage or other injury resulting from its use.

SAMT does not accept any liability for any investment decisions made on the basis of this information, nor any errors or omissions on the SAMT website.

This web site does not constitute financial advice and should not be taken as such. SAMT urges you to obtain professional advice before proceeding with any investment.

The material may include views and statements of third parties, which do not necessarily reflect the views of the SAMT. Information on this website is maintained by the people and organization to which it relates. The SAMT believes that the material contained on this website is based on the information from sources that are considered reliable. Although all care has been taken to ensure the material contained on this website is based on sources considered reliable we take no responsibility for the relevance and accuracy of this information.

Before relying or acting on the material, users should independently verify its accuracy, currency, completeness and relevance for their purposes. Before making any financial decision it is recommended that you seek appropriate professional advice. The SAMT website may contain links to other websites, these are inserted merely as a convenience and the presence of these links does not constitute an endorsement of the material at those sites, or any associated organizations, products or services.

Journal Media Sponsor

eNewsletter: Awards: Training: Books:

http://www.technicalanalyst.co.uk/eNewsletter/index.htm http://www.technicalanalyst.co.uk/conferences/Awards13.htm http://www.technicalanalyst.co.uk/training/index.htm http://www.technicalanalyst.co.uk/books/index.htm

The Swiss Technical Analysis Journal • Summer 2013 • 41

Technical Securities Analysts Association San Francisco (TSAA-SF) Webinars

SAMT Education

2-Day Immersion Course for the CFTe Level II Exam - Zürich When: Saturday, 07 September & Sunday, 08 September 2013 Where: Zürich Hours: 9:00 until 18:00 each day 15 hours of Immersion Training Class Size: 5 minimum; 10 maximum Cost: SAMT Members: CHF 1150 Non Members: CHF 1350 Early Bird Cost: SAMT: CHF 1050 Non Members: CHF 1250 Registration Deadline: Friday, 16 August Early Bird Deadline: Friday, 9 August Contact: ronwilliamPR@gmail.com The course will be presented in English. n This immersion course is also designed to prepare candidates for the upcoming CFTe Levels I and II exams which culminate in the award of an international professional qualification in technical analysis. The exam tests technical skills knowledge and understanding of ethics and the markets. n The course will be limited to 5-10 candidates so that each person will receive the same individual level of information and instruction. n The CFTe Level II exam incorporates a number of questions requiring essay-based analysis and answers. The candidate will demonstrate a depth of knowledge and experience in applying various methods of technical analysis. n The exam also contains a number of different charts covering one specific market (often an equity) to be analysed, as though for a fund manager or trader.

Who Will Teach the Course? n The course will be taught by Bruno Estier, CFTe, MFTA; and Ron William, CMT, MSTA who are members of the Geneva chapter of SAMT. n Collectively, the instructors have 45 years of experience, have technical analysis professional designations, and use technical analysis in their daily work (see profiles).

For updated details and to register, please click on this link http://events.constantcontact.com/register/event?llr= a6yl96lab&oeidk=a07e7plfv0pa6fb70bf

Each month the TSAA-SF presents webinars that are often free or require a prepayment of a small fee. The webinars are offered as various times during the day - some early in the morning (Pacific Time), some at noon or in the evening.

Because of the time difference between San Francisco and Switzerland (9 hours), SAMT members could view some of the webinars during CEST evening hours.

The next webinar is on Saturday, 13 April on Integrating Signals from the Credit Market into Equity Trading Strategies by Dave Klein, partner and co-founder of Capital Context LLC. This webinar will be from 10:00-11:30 AM PDT (19:00-20:30 CEST). The fee for this webinar is $US 10 (the member fee).

Click to see the schedule of webinars available.

TSAA-SF is the oldest society in the U.S. devoted to the study and development of technical analysis of stocks and commodities.

TSAA-SF is an IFTA Member Society.

Technical Analysis Applied Course- Lugano Professional use of technical analysis for investment decisions and trading (Certified Financial Technician® - CFTe) Technical analysis, today recognised as a complementary discipline and not necessarily an alternative to fundamental analysis, is essential for those who work in asset management and trading, and also useful for client advisors and financial trustees. In recent years, there has also been a growing interest in the topic by “non-experts”, people from different professions united by the passion for the markets. To meet these diverse needs, the course provides a thorough overview of the technical and practical skills for the purposes of reporting and trading.

The course will cover both the practical aspects of the subject and coverage of the syllabus set by the International Federation of Technical Analysts (IFTA).

The participants will have lectures with practical exercises, group work, simulations and support from technical analysis software.

The course, organized by Centro Studi Bancari in collaboration with SAMT (Swiss Association of Market Technicians), is for people working in private and retail banking advisory, asset and portfolio management, trading, treasury, trading rooms, trustee financial consultants in insurance and finance, insurance brokers, financial intermediaries and persons interested in the subject who want preparation for the Certified Financial Technician examination.

Educational material will be provided during the course by Centro Studi Bancari When: 19 November 2013 until

18 February 2014 Where: Centro Studi Bancari

di Vezia Hours: 48 hours

Class Size: 5 min; 20 max Cost: ABT, SAMT, SFOA Members: CHF 2.990 Non-Members: CHF 3.490 Registration Deadline: Friday, 31 October 2013 The course will be presented in Italian.

Click for a detailed program from the CSB.

IFTA Certified Financial Technician (CFTe) Program The IFTA Certificate (Certified Financial Technician) consists of CFTe I and CFTe II, which together constitute a complete professional program.

The two examinations culminate in the award of this internationally recognised professional qualifi cation in Technical Analysis.

Examinations The exams test not only technical skills, but also international market knowledge.

CFTe I This multiple-choice exam covers a wide range of technical knowledge and understanding of the principals of Technical Analysis, usually not involving actual experience.

The CFTe I exam is offered in English, French, Italian, German, Spanish, and Arabic, and is available, year-round, at testing centers throughout the world, from IFTA’s computerbased testing provider, Pearson VUE.

CFTe II This exam incorporates a number of questions requiring an essay based analysis and answers.

For this, the candidate should demonstrate a depth of knowledge and experience in applying various methods of technical analysis. The exam provides a number of current charts covering one specifi c market (often an equity), to be analysed, as though for a Fund Manager.

The CFTe is offered in English, French, Italian, German, Spanish and Arabic bi-annually, typically in April and October.

Curriculum The program is designed for self-study. Local societies may offer preparatory courses to assist potential candidates. Syllabus and Study Guides are available on the IFTA website.

To Register Please visit the website for registration details.

Cost IFTA Member Colleagues CFTe I $500 US CFTe II $800* US

Non-Members CFTe I $700 US CFTe II $1,000* US *Additional Fees (CFTe II only): $250 US translation fee applies to non-English exams $100 US applies for non-IFTA proctored exam locations

42 • Summer 2013 • The Swiss Technical Analysis Journal

SAMT Partner Societies

International Federation of Technical Analysts (IFTA) IFTA is a non-profit federation of 26 individual country societies who individually and jointly dedicate themselves to n

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Research, education, camaraderie and dissemination of technical analysis of world markets. The IFTA societies support sharing technical analytical methodology that at its highest level is a valid, and often-indispensable element in the formulation of a reasonable basis for investment decisions.

Promotion of the highest standards of professional conduct, international cooperation and scholarship between all its Member and Developing Societies within all arenas of technical analysis.

Providing centralized international exchange for information and data of various financial centers while respecting individual country and Society business practices, legal structures and customs.

Encouraging the standardization of education and testing of its constituent members in technical analysis, making sure that each individual country’s security analyst licensing, legal and language /communication priorities continue to be individually accepted.

Fostering the establishment of individual societies of technical analysts without bias in regard to race, creed or religion.

It supports the need for maintaining a free and open worldwide markets under normal, and in particular crisis periods.

Centro di Studi Bancari Founded by the Ticino’s Banking Association in 1990, Centro di Studi Bancari (CSB) is an institution that promotes and provides education, training and continuous update for banking, fiduciary, insurance and legalfinancial professionals in the financial markets. CSB provides courses, training courses for various certifications and hosts conferences. The training programs are recognized at local, national and international levels, as well as by many private associations, such as SwissBanking. CSB can also organise tailor-made training, leveraging on its inter-disciplinary competences in the field of banking, finance, compliance, management and taxation.

Swiss Futures and Options Association The Swiss Futures and Options Association (SFOA), previously the Swiss Commodities, Futures and Options Association, was founded in 1979 as a non-profit professional association for the purpose of promoting derivative financial instruments, particularly standard futures and options contracts on financial instruments and commodities, to the widest possible audience, and to serve the interests of its members. SFOA serves users of commodity and financial derivatives, as well as professionals, their institutions and the exchanges. www.sfoa.org

www.csbancari.ch

Groupement Suisse des Conseils en Gestion Independats (GSCGI) CSCGI is a group of economic interests formed by specialized independent financial intermediaries who are confirmed professionals in the financial services industry. The group is open to contacts with any person interested in the business of wealth management seeking to promote dialogue with the banking partners and authorities at all levels. Their goals are to: • Promote contacts between professionals motivated by the same desire for independence, wishing to maintain and develop relationships with counterparts.

• Find common ground for exchanging experiences and ideas, a field where diversity and novelty are prevailing.

As a growing bridge of communication worldwide, IFTA remains open to methods of technical analysis, while encouraging the consideration and support of membership for both developing and established societies.

• The enrichment of the links that can be forged on a friendly and professional level within a well defined and recognized framework to favour professional consultation and close dialogues.

www.ifta.org

www.gscgi.ch

Swiss CFA Society The Swiss CFA Society boasts over 2,400 members in Switzerland, against barely 100 in 1996 at inception. It is the largest CFA Institute society in continental Europe. With more than 2,000 candidates taking the rigorous Chartered Financial Analyst® (CFA®) exam in Switzerland each year, the society’s impact on the Swiss investment community is self-evident.

It was the first society of CFA charterholders in the EMEA region to be directly affiliated with the prestigious CFA Institute, which includes more than 110,000 members in 139 countries.

The vision of the Swiss CFA Society is to be a leader in fostering the highest level of knowledge, professionalism, and integrity in the investment business. www.cfasociety.org/switzerland

The Swiss Technical Analysis Journal • Summer 2013 • 43

The Swiss Association of Market Technicians GenÈvE • Lugano • ZÜrich 44 • Summer 2013 • The Swiss Technical Analysis Journal