Quriosity Volume 09 Issue 09

QURIOSITY

VOLUME 09 ISSUE 09

SEPTEMBER 2018 MONTHLY NEWSLETTER OF QUANTINUUM

– The quant & analytics committee @ SIMSR

Editor’s Note Welcome to the latest issue of Quriosity, the monthly newsletter of Quantinuum!

Quantinuum - the Quant and Analytics committee of K.J. Somaiya Institute of Management Studies and Research aims to empower students and professionals alike to organize and understand numbers and in turn, to make good and rational decisions as future managers. The newsletter published monthly consists of articles which will enrich the young minds by informing about the contributions made in the field of quant, analytics, and mathematics. The objective of Quriosity is to publish up-to-date articles on data analytics, alongside relevant and insightful news. This way the magazine aspires to be vibrant, engaging and accessible, and at the same time integrative.

This issue includes cover story on text analytics and sub-article on how market basket analysis is being used for data analysis for marketing and retailing purposes. We have also highlighted the contributions of a quant guru –Prof. Ritabrata Munshi (B-1976). Curiosity updates will inform you about developments in space exploration from around the world. The issue also features other interesting quant fun articles and quant digest. We have also reported the Tableau workshop conducted by Prof. Cyrus Lentin along with an interview providing his insights about analytics.

If you wish to submit articles or news items, either individually or collaboratively, you are welcome to write to us at – quriosity.quantinuum@gmail.com Thank you and Happy Reading!

Quriosity Editorial Team Quantinuum@SIMSR Editorial Team: VVNS Anudeep (+91 9441201685) Khushbu Mehta (+91 9930158610) Tanmay Nikam (+91 9699288587) Himanshu Data (+91 8105936820) Akshay Nandan R (+919176444022) Saumya Joshi (+91 9456684181) Abhishek Bawa (+91 9619995738) Kaustubh Karanje (+91 7738219050) Dhyan Baby K (+91 9809245308) Shubham Thakur (+91 7096045088)

Mentor: Prof. N.S.Nilakantan (+919820680741) Email – nilakantan@somaiya.edu

Team Leaders: Purav Shah (+918511929416) VVNS Anudeep (+919441201685) Yatharth Jaiswal (+919969698361)

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Contents TOPIC

PAGE NO

Cover Story Text analytics – Understanding its basic application

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by Kaustubh Karanje

Sub-article Market Basket Analysis – Analytics in 7

marketing and retailing

by Malika Bansal

Quant Guru – Prof. Ritabrata Munshi (B-1976)

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by Dhyan Baby K

Quant Curiosity Update

by Shubham Thakur

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News Digest

by Shubham Thakur

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Faculty Interview

by Tanmay Nikam

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Mentor’s Corner

by Tanmay Nikam with inputs from mentor

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Event Report

by Himanshu Data

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Quant Fun

by Dhyan Baby K and Tanmay Nikam

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Quant Connect 24 3

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Quant Cover Story Text Analytics - Understanding its basic application

Our typical workday is spent reading and writing e-mails, letters, reports, articles etc. It isn’t enigmatic that 80% of the information in business comes from unstructured forms, prominently Text.

Historically, computational linguistics is a very old subject and computer scientists have targeted the natural language since then. In 90’s Text Analytics started emerging as a subject. It has found applications ranging from pharmaceutical drug discovery, risk management, cyber-crime prevention to customer care service.

Text analytics, with the use of “natural language processing” (NLP), holds the key to unlocking the business value of these big data assets. In the era of big data, the right platform enables businesses to fully utilize their data and take advantage of the latest text analytics and NLP algorithms. How does NLP work?

NLP is a way for computers to analyze and understand human language and derive meaningful conclusions from it. Common word processors treat language like a string of symbols. NLP considers the sequence that alphabets make words, words make phrases, several phrases make sentences and sentences eventually convey the idea.

NLP algorithms are based on machine learning algorithms because the system should automatically learn rules by analyzing examples. NLP algorithms are used to summarize blocks of texts, creating chat bots to interact with the customers, identification of the sentiment of a string of text.

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There are some open source NLP libraries like Apache Open NLP that provides sentence segmentation, part-of-speech tagging. Natural Language Toolkit (NLTK) provides modules for processing text, tagging, parsing and more.

Data scraping, sometimes called web scraping, data extraction, or web harvesting, is simply the process of collecting data from websites and storing it on your local database or spreadsheets. For starters, data scraping may sound one of those scary techno jargons. But it’s more understandable than you think.

Data scraping tools come in handy not only for recruitment purposes, but also in marketing, finance, ecommerce and many other industries.

Among the best scraping tools in the market there is a tool called “Octoparse”. Octoparse allows us to take all the text from the website and thus we can download all the content on the website and then save it from a structured format like Excel, HTML, CSV, or your databases without coding. Only drawback is that it can’t scrape data from PDFs. There is another tool called “ParseHub” which is a visual extraction tool and it can handle interactive maps, calendars etc. It gives you 5 projects and 200 pages per run which is enough for a student.

ParseHub supports operating systems such as Windows, Linux, Mac OS X. ParseHub is more user friendly for programmers with API access. Both Octoparse and ParseHub are free tools to be used for data extraction.

There is a commercial data scraping tool called “Content Grabber”. It can extract data from dynamic websites like AJAX websites. It is more suitable for people with good programming skills because it has editing, scripting and debugging interfaces. It uses many third-party tools which aid in data scraping. Content grabber can integrate with Visual Studio 2013 for script editing and debugging.

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There are some companies that have stable topic domain while others have multiple and shifting topic domains. For shifting topic domains, we would need platforms that excel in speed and flexibility of analysis. For example, some companies might need the platform to integrate with their customer relationship management systems (CRM).

There are some important things a company should consider before choosing any tool for data extraction. Analytical methods chosen should identify the topic accurately and should be flexible enough to accommodate technical terms and local jargons. It should be able to work with large and small data sets with same precision. The platform should have flexible reporting dashboards that help visualize the text and can be customized for formatting and editing. It should be able to analyze and extract data at various levels of details. The last part would be that it should have the ability to export the results in flexible formats.

References: "Unstructured Data and the 80 Percent Rule"- Seth Grimes www.octoparse.com www.linguamatics.com www.expertsystem.com www.datasciencecentral.com www.bain.com www.blog.algorithmia.com

By Kaustubh Karanje PG CORE (2018-20)

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Sub Article Market Basket Analysis - analytics in marketing and retailing

Today we have a large amount of data available with us. Also, we now have the tools required to collect, manage and store this massive amount of data which is being streamed continuously.

Businesses and business analysts are interested in finding out answers to - What could be very effective for them? What could be the business patterns that can help them in marketing or retailing?

So, we have Market Basket Analysis which could be used as a modeling technique effectively for this purpose to make sense of the data. All we need to do is to understand the various terms and methods associated with Market Basket Analysis.

The name Market Basket Analysis was basically derived from the idea that customers usually throw all the purchases in a shopping cart or a market basket during grocery shopping. So, the basic idea behind Market Basket Analysis started from the very act of grocery shopping. This is basically a method which could be used for data analysis for marketing and retailing purpose. It basically determines which products customers are likely to purchase together. This trend is identified by using computer tools for mining and analysis purpose. There is a really interesting story behind this analysis which is known as the beer and diaper story. There was a chain of supermarket in US who analyzed various buying habits of customers for beer and diapers with respect to explanatory variable like weekends and they found a very interesting relationship between the buying patterns. It was found that customers usually bought beer and diapers on weekends together. The reason behind this could be that the fathers with kids are not able to visit pubs very often. Or maybe that they are planning to enjoy their weekend with their kids so they are getting the supplies for their kids as well as for them in advance. When the supermarket found out this correlation they decided to place the diapers and the beer next to each other so that this could result in increased sales.

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Market Basket Analysis problem can have the following applications: • Item affinity – This tells us the probability of two or more items being sold together • Identify driver items – It tells us which items need to be always in stock and what drives customer willingness and temptation which will indirectly increase the footfall in the market • Classify trips – It analyzes the customer preferences like when they buy, on what occasion and what time of the day and classifies the trip to store into categories such as weekend grocery trip, festival buying, etc.

• Store to store comparison - Understanding the number of baskets allows any metric to be divided by the total number of baskets, effectively creating a convenient and easy way to compare the stores with different characteristics (units sold per customer, revenue per transaction, number of items per basket, and so on) • Revenue optimization – Revenue targets can be optimized by analyzing the data on change in price of products and its impact on customer’s shopping basket contents • Marketing strategy - It is about identifying more profitable advertising and promotions, targeting offers more precisely in order to improve ROI, generating better loyalty card promotions with longitudinal analysis, and attracting more traffic to the store.

• Operations optimization: It is about matching the inventory to the requirement by customizing the store and assortment of trade area demographics and optimizing the store layout.

Benefits of Market Basket Analysis: Based on the insights from Market Basket Analysis businesses and retailors can organize their product portfolios and stores to increase their revenues. Analytics can tell us which item go along with each other or which items should be placed near each other which will make the consumer notice them more.

This will guide the way a store should be organized to aim for maximum sales and revenues. With the help of this data you can eliminate the guesswork while determining the optimal store layout. Based on the inputs from Market Basket Analysis we can also predict future purchases of customers over a period of time. Using initial sales data, we can predict which item would probably fall short and maintain stocks in optimal quality. This will help improve the allocations of resources to different items of the inventory.

Market basket analysis can help businesses especially retailers, to analyze buying behavior of their customers and predict when and what is their next purchase going to be. If used effectively this can significantly improve cross-selling and in turn, help increase customer’s lifetime value.

By Malika Bansal PG- RM 2018-20 8

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Quant Guru Prof. Ritabrata Munshi (B-1976) Biography Prof. Ritabrata Munshi was born on September 14th, 1976 in Kolkata. He is an Indian mathematician who specializes in number theory. As a student Ritabrata was never interested in sports and spent hours reading science journals. Soon he found his heart and mind deviating towards mathematics and was already doing number theory by the time he was in Class IX. As an undergraduate, he joined the prestigious B.Stat. program at Indian Statistical Institute (ISI), Kolkata. He even went to Tata Institute of Fundamental Research (TIFR) during long holidays to satiate his hunger for mathematics. He went on to complete his early graduation from ISI but his desire to pursue mathematics full time drove him to join the PhD program at Princeton (Institute of Advanced Studies). He got a chance to work with Andrew Wiles, a British Mathematician specializing in Number theory and even with Henrik Iwaniec, a Polish American mathematician for his Postdoctoral research at Rutgers University. In 2010, he returned to TIFR as a professor and worked there for five years after which he joined his alma mater ISI and started teaching there as an Assistant Professor. He is also a part of the editorial board of Hardy-Ramanujan journal and Journal of the Ramanujan Mathematical Society.

Work and Recognition Prof. Ritabrata is world renowned for his work in the analytical side of number theory, automorphic forms, and arithmetic geometry. His work on the analytic theory of L-functions, especially the sub convexity problem for higher rank L-functions and applying analytic methods in the study of Diophantine problems was widely appreciated. He has received worldwide recognition for his research and contribution to these fields. In 2017, he was awarded the Infosys Prize in Mathematical Sciences for exceptional work in the analytics aspect of number theory. He was also honored by being elected as a Fellow of the Indian Academy of Sciences in 2016. He was awarded the Shanti Swarup Bhatnagar Prize for Science and Technology, the highest science award in India, in mathematical science category for the year 2015. He also received the B.M. Birla Science prize in 2013 and the Swarna-Jayanti fellowship by the Department of Science and Technology, Government of India in 2012. In 2018 he won the prestigious ICTP Ramanujan Prize. Ritabrata is definitely one of the heirs to Ramanujam from whom the mathematics world is expecting really big things.

References: http://www.infosys-science-foundation.com/images/thumbnails/ritabrata-munshi.jpg (image) http://www.infosys-science-foundation.com/prize/laureates/2017/ritabrata-munshi.asp https://www.revolvy.com/page/Ritabrata-Munshi

By Dhyan Baby K PG FS (2018-20)

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Curiosity Update --This updates readers on space exploration around the world including our own ISRO’s efforts.

NASA's Curiosity Mars rover noticed this summer's monster dust storm fairly early on — but not in the way you might expect. The storm was first spotted from above by NASA's Mars Reconnaissance Orbiter on May 30 as a localized event near Perseverance Valley, a landform being explored by the agency's Opportunity rover. The dust storm grew quickly over the following days, as Curiosity's observations showed. Curiosity's home is the 96-mile-wide (154 kilometers) Gale Crater, on the other side of the planet from Perseverance Valley, but it saw signs of the storm on June 5. Those signs were temperature readings, made by sensors on a motor on the car-size rover's deck, mission team members said. That motor powers the lid on a funnel that directs powdered rock samples from Curiosity's drill into its onboard chemistry-lab instrument, which is known as Sample Analysis at Mars (SAM). All the charts showed the dust storm effect on the actuator because it's exposed. All of a sudden, drop in daytime temperature was observed.

The night time temperature stayed abnormally high as well, as it does during big Martian dust storms.

While all that dirt in the air blocks sunlight during the day, it also prevents infrared radiation from escaping to space at night, keeping things warmer than usual after the sun goes down.

The storm continued to grow, eventually encircling the planet by June 20. Its intensity plunged Perseverance Valley into perpetual darkness, blocking so much sunlight that the solar-powered Opportunity couldn't recharge its batteries. The golf-cart-size rover, which has been exploring Mars since January 2004, hasn't made a peep since June 10.

The motor's temperature measurements helped the Curiosity team keep tabs on the storm (which they also did using the rover's onboard weather station). Analysts combined the dust-storm data with historic readings from the motor, to predict when the storm might start clearing up.

That forecast proved accurate. Dust levels in Gale Crater had returned to normal by Sept. 18, according to the motor measurements, NASA officials said. Curiosity was largely unaffected by the storm, because it runs on nuclear rather than solar power.

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Scientists are eager to study all the data they can about the recent Mars dust storm, to get a better handle on these fairly regular, but poorly understood, events. For example, researchers can't accurately predict when a global dust storm will arise on Mars, and they don't know why some small storms balloon into planet-girding monsters, whereas others fade away.

Its been four years since @MARSOrbiter successfully got inserted into Martian orbit on September 24,2014 in its first attempt. #MOM’s mission life was expected to be six months! So far, the Mars color camera has acquired 980+ images. Mars Atlas is also ready.

About news closer to home, India's Mars Orbiter (MoM) Mission, more commonly known as 'Mangalyaan' left the ISRO launchpad on November 5, 2013, it was only designed to be in space for six months. Four years later, it is still spinning. While this marked a huge achievement for India's space capabilities - it also focused attention on what happens next to the orbiter - and was discovered that it could have a long life based on the amount of propellant left aboard the spacecraft after achieving orbit.

Reference: https://www.space.com/41963-mars-dust-storm-2018-curiosity-rover-detection.html

By Shubham Thakur PG - IB (2018-20)

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Quant News Digest Data Science Platforms Help the Buy Side Integrate Alternative Data Asset managers are looking for ways to mine alternative data sets for investment ideas, recognizing that stock pickers cannot rely on traditional research. An explosion in alternative data, ranging from satellite images to mobile geolocation data and unstructured text, has created an arms race among hedge funds and quantitative funds. Many firms have hired data scientists to dive into pools of data and to use machine learning algorithms to extract insights or predictive signals. Traditional buy-side firms are also eyeing big data sets while wrestling with how to incorporate them into the investment process.

Reference: https://flextrade.com/data-science-platforms-help-the-buy-side-integrate-alternative-data/

10 Years Later, Lessons from the Financial Crisis Summary of the 2008 financial crisis from the point of view of US investors and the impact of actions taken by the government during and after the aftermath. Also listed are some of the facts about the crisis and the lessons learnt from it.

Some statistics from the crisis: •

8.8 million jobs lost

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Unemployment spiked to 10% by Oct 2009

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8 million home foreclosures

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$19.2 trillion in household wealth evaporated

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Home price declines of 40% on average – even steeper in some cities

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S&P 500 declined 38.5% in 2008

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$7.4 trillion in stock wealth lost from 2008-09, or $66,200 per household, on average

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Employee sponsored savings or retirement account balances declined 27% in 2008

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Delinquency rates for Adjustable Rate Mortgages climbed to nearly 30% by 2010

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The lessons from the financial crisis were painful and profound. Here is a list of a few of them: 1. Too Big to Fail - The notion that global banks were ‘too big to fail’, was wrong.

2. Reducing Risk on Wall Street -Reduction in banks making careless bets with their own money and sometimes in blatant conflict with those they had made on behalf of their customers.

3. Overzealous lending in an Overheated Housing Market - The housing market has recovered in several major cities and lending has become more stringent, to a degree.

4. Moral Hazard? What Moral Hazard? - Many banks and agencies did appear to clean up their acts.

Reference: 10 Years Later, Lessons from the Financial Crisis | Investopedia https://www.investopedia.com/news/10-yearslater-lessons-financial-crisis/#ixzz5QjQkdyW9

Blockchain Trust Company Paxos Launches NY Regulator-Approved, USDBacked Stablecoin Blockchain Trust Company Paxos has launched a U.S.-dollar backed stablecoin following approval from New York regulators, according to a press release published September 10. The stablecoin is reportedly seeking to be listed on other marketplaces, and will trade under the ticker symbol PAX. Reference: https://cointelegraph.com/news/blockchain-trust-company-paxos-launches-ny-regulator-approved-usd-backedstablecoin

By Shubham Thakhur PG-IB (2018-20)

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Faculty Corner Quantinuum members had the opportunity to host, interact and gain insights about analytics from Prof. Cyrus Lentin who was on K.J. Somaiya Institute of Management campus to conduct a four-day workshop on Tableau. So we thought of highlighting Prof. Cyrus Lentin as faculty of the month.

Prof. Cyrus Lentin is a qualified data scientist with thirty plus years industry experience with extensive domain expertise in Data Management, Messaging & Infrastructure. An Information Technology expert with hands on experience in Product Management, Release / Delivery Management, Software Development, Management Information Systems with a track record of success in platforms covering Java, LAMP (Linux, Apache, MySQL, PHP), .Net & Android; creating robust architectures & infrastructure. He has been a certified lead auditor for ISO-9001 and ISO-27001 and completed training for Certified Ethical Hacker, Blackblot Product Management, Mobile Application Development, Big Data Analyst (covering Hadoop, Java Map Reduce, Pig, Hive, Impala, Hbase & Sqoop), Data Scientist Specialization (covering Exploring Data, Data Visualization, Statistical Inference, Regression Analysis, Machine Learning & ShinyApps using RProgramming). And also completed advanced training for BI Tools QlikView, SAS & Tableau.

Below are the excerpts from the interview of Prof. Cyrus Lentin: Q: How did you get into analytics?

A: Being an Arts (Economics / Statistics) graduate, it was providence (luck?) that I entered the IT field. But even while programming was always interested in "playing" with data. Would bring in some element of analytics in all the projects I have worked on in the past. Moving into data analytics when I branched out on my own, I guess, was just a natural progression.

Q: How does one become successful in the field of analytics and data science?

A: Like any other field the formula for success is simple. Its 90% perspiration and rest all else. No substitute for hard work and practice makes a person perfect.

Q: What advice would you give for MBA students about career and analytics?

A: Analytics is a sunrise industry; we have just started; "miles to go before we sleep". The key to survival would be keeping abreast of new technologies. Every day something new is coming up.

Will you be able to devote say four hours a week for up-skilling? If yes, you will grow. If not, you will languish ...

Q: What according to you is the future of analytics in India?

A: In the near future there would be a convergence of analytics, machine learning, neural networks, artificial intelligence. The line between all these will blur and artificial intelligence-based systems will be common place. However, it is unlikely that there will be large scale replacement of humans by machines. The will be some pain but with re-skilling / up-skilling the humans will be back in control.

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Q: How is AI and machine learning impacting analytics?

A: Let me share some interesting case studies: •

A lot of client facing but mundane support jobs will be taken over by AI. A case in point is EVA, the AI driven chat-bot from HDFC Bank. EVA is able to answer a lot of simple but frequent queries, like "what do I require to open a bank account", "what is the procedure to change address", "how do I add nominee to bank account". This will not necessarily mean unemployment; it would result in trained manpower being required for support of such systems.

Just imagine how efficient govt service would become if similar systems were deployed in ward / other govt office :)

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AI combining with Virtual Reality is going to change our retail experience. The future stores are likely to be virtual stores, you shop in a virtual environment and and your orders will be delivered at home. Sales Assistant like "Conversica" help enhance sales operations processes by identifying and conversing with internet leads.

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ROSS Intelligence makes a legal research platform based on IBM's cognitive computing system Watson, which is being used by a number of the world's biggest law firms, including Dentons, Latham & Watkins. Legal Research involves going through the archives and identifying earlier cases (precedents) most relevant to the current case. It could take days for a team of legal assistants to come up with such precedents. ROSS scans through the entire legal archives of the legal cases to extract most relevant precedents.

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Today, while teaching the focus of instruction is use of tools to create a table or a graph or a model. How to read the story from a report is never the focus of training. It is my belief that, sooner rather than later, AI will take over the responsibility of getting to the story of the report. A company called Narrative Science is pioneering in this.

We have many such case studies in each & every industry and / or vertical. I do not think it will take too long to convert what are currently case studies to mainstream. I guess a decade or two at the most.

By Tanmay Nikam PG FS (2018-20)

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Mentor’s Corner The FOW India International Derivatives Conference report Prof. N.S.Nilakantan was invited to the FOW (Futures & Options World) India International Derivatives Conference. The event that took place at Sofitel BKC, Mumbai on 25th September, 2018 brought experts from India and international markets with the objective of knowledge sharing and debate discussion regarding what new markets have to offer, and which exchanges, banks, brokers and technology firms are leading in the markets. The conference was organised by Global Investor Group (GIG).

The conference began with welcome remarks by Andrew Neil, Editor, GIG. It was followed by a keynote address and a talk on Federal Reserve’s rate policy and how quantitative easing can help spur growth by Erik Norland, Senior Economist, CME Group. It was followed by a panel discussion on the opportunities present in the market today by senior executives of exchanges -Juca Andrade, Chief Product and Client Officer, B3, K Hari, Chief Business Officer, Equities, Derivatives and Currency, NSE and Rishi Nathany, Head- Business Development and Marketing, MCX formed the panel which was moderated by Andrew Neil. The discussion focused on SEBI’s move to allow exchanges to offer universal cross asset trading facilities from October, 2018 which looks set to fundamentally change the competitive landscape across the market as exchanges gear up to launch new products. After a brief coffee break there was a presentation by David Helps, Head of Global Business Development, TMX, after which there was a panel discussion on “International perspective to what’s hot in the global market”. It highlighted the current trends in the global market and what they mean for the evolution of India’s derivatives market. It also focused on cryptocurrencies to futurization and innovation. The moderator for the panel was Anil Batra, Chief Operating Officer, Hertshten Group and panel members were Devendra Raghav, Head of Compliance, QNB Group, Mezhgan Qabool, Derivatives Trading and Clearing Sales and Business Development, Eurex, Martin Frewer, Global Commercial Director, ABN AMRO, David Helps and Chintan Thakkar, Managing Director, OSTC India, Founder - Trading Institute’. The discussion after lunch focused on the shock the global market went through in February, 2018 when Indian exchanges clamped down on offshore derivatives trading through limiting external market data licenses. The moderator for the panel was Sai Dutt, Co-Owner, Livesquawk with panel memebrs - K Hari, Chief Business Officer, Equities, Derivatives and Currency, NSE, Ritesh Ashar, Chief Strategy Officer, KIFS and Rishi Nathany. After the afternoon coffee break there was a discussion which focused on the opportunities that Gift City brings to the global market. Gift City, located near Gandhinagar, Ahmedabad, potentially represents one of the most significant developments in the Indian market in recent times enabling international access to India’s vast liquidity pools. This panel comprising of Ravindranath Thota, RBL, Nagendra Kumar, Chief Business Officer, NSE, Shalaban Rakyan, Vice President, Estee Advisors, Rajib Ranjan Borah, Co-founder - iRageCapital was moderated by Hemal Randerwala, MD, Arjun Global ltd. The discussion was on progress of the initiative to date and what more is to be done to attract international trading flow. The final discussion for the day focused on international participation, global trends in the commodity markets. It focused on moves to open up India’s commodity markets to international participation which would increase volumes, liquidity and create a more holistic market. Also, it dealt with the likely launch of commodity options market in India. The panel was moderated by Abhishek Bansal, Chairman, Abans and panel

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members were Kunal Shah, Head of Commodities Research, Nirmal Bang, Sumesh Parasrampuria, Group CEO, Kunvarji Group, Rohit Srivastava, Head – Technical Research,Sharekhan and Nelson Low, Executive Director, CME Group. The event concluded with a networking session.

The event witnessed active participation from sponsors such as CME Group-the world’s leading and most diverse derivatives marketplace, Aveacom which is focused on providing high performance connectivity and IT infrastructure for global capital markets, Stellar which supplies its clients with cutting edge trading systems and Greeksoft which provides algorithmic trading solutions among others.

Our mentor, Prof. Nilakantan had interactions with many of the dignitaries and participants. He discussed the aspects of derivatives trading with Mr. Erik Norland, senior economist of CME group.

Mr. Norland has spent his formative years in the US and spent a few years in New York during his studies and on the job. He is currently located in London. He is very much interested in India and visits Mumbai frequently. CME group has its Indian office at Bengaluru and Mr. Norland has tentatively agreed to spare sometime during his next visit to Mumbai. We will be pursuing with him to fix a suitable date for his visit to the institute.

By Tanmay Nikam, PG FS (2018-20) Based on inputs from mentor

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Event Report _ Tableau workshop “If you can’t explain it simply, you don’t understand it well enough.” -Albert Einstein There is too much data everywhere and finding and relevant data and information is like finding a needle in a haystack. But we succeeded in finding that needle. Is finding the relevant data enough? No, it’s not enough. Expectation is to find the data, visualize it, and run algorithms in data, modeling of data, prediction and forecasting using that data, machine learning, Artificial Intelligence.

With the same goal, Quantinuum - The Quant and Analytics committee of KJ SIMSR organized a 16hour workshop spread over four days from 7th - 11th September, 2018. Many students were interested and we received about 75 registrations. But due to limited seats, 40 students on first-cum-first-serve basis were taken in.

Business Intelligence and Data visualization workshop was to help students take initial steps in the field of Data Analytics with tool Tableau. Tableau is a Data visualization tool which is used in many organizations like Accenture, Maersk, Barclays, JP Morgan Chase, Amazon, Citibank etc. Mr. Cyrus Lentin, having more than 30 years of experience, was the Guest lecturer for this workshop.

The workshop was a huge success and the approach of Mr. Lentin was quite practical which enhanced students’ skills to work easily on the tool. Students were quite excited and enthralled with the workshop which in a way will help them in their placement process and future endeavors.

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The testimonial of Shivani Sharma from PGDM-IB batch who attended the workshop: “Hi Team Quantinuum, I would like to thank the entire team for taking efforts in organizing Tableau workshop for college students. I would like to share my experience in Accenture Interview and how this particular workshop helped me brag in Data and architect profile. In the 2 technical interviews I had, I was asked questions on data analytical tools and I managed to drive the interview towards the new tool that I had worked on, Tableau. Even the basic knowledge of the tool was enough to talk and convince the panelists. I am really thankful to the entire team. Guys, please make the most of such workshops as they are really helpful and act as differentiating factor in your resume and interviews. All the best for the placement season ahead.”

On the basis of overwhelming responses and feedbacks received, we will try to conduct more such events which will help students climb the ladder of Data Analytics helping them in their career path.

By Himanshu Data PGDM (2018-20)

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Q U R I O S I T Y - V O L U M E - 9, I S S U E – 9

Quant Fun 1) Three thieves need to cross a river. Each thief has certain amount of stolen gold coins kept in his bag.

Thief A has 1000 gold coins Thief B has 700 gold coins Thief C has 300 gold coin To cross the river there is a boat which can carry a maximum of two objects at a time that means either a maximum of two thieves can cross the river or a thief with a bag can cross the river. The problem is that in this process of crossing the river if a thief is left with an amount of coins more than his own then he will run away with that. The same rule applies for two thieves, if they are left with a total of more than their cumulative gold coins then they will run away with that money.

What strategy will ensure that they all cross the river properly?

2) Shubham thought of a two-digit number and divided the number by the sum of the digits of the number.

He found that the remainder is 3. Devesh also thought of a two-digit number and divided the number by the sum of the digits of the number. He also found that the remainder is 3. Find the probability that the two-digit number thought by Shubham and Devesh have the reminder 3?

3) Sudoku puzzle (easy level):

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Q U R I O S I T Y - V O L U M E - 9, I S S U E – 9

4) Sudoku puzzle (hard level):

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Answers: 1. They all will cross the river in following manner: i.

Thief B crosses first with his bag of 700 coins. He will keep the bag there and will return. ii.

Thief A will now cross the river with the bag which has 300 coins. He will keep the bag and return. iii. Now thief B and C cross the river and thief C will return with his bag of 300 coins. iv.

Now thief A goes to the other side with his bag of 1000 coins and thief B will return with his bag of 700 coins. v.

Now thief B and C cross the river together and thief A return empty handed. Thief A takes the bag of 300 coins and cross the river then thief B is sent to collect his bag of 700 coins.

So, finally they all cross the river properly.

2. Let two-digit number that Shubham thought be 'xy', where x and y are single digit number.

Therefore, 10x+y=p(x+y)+3, where p is a natural number p=10x+y−3x+y Also y+x>3 Possible values of x and y for which p is a natural number are: (x=1,y=5),(x=2,y=3),(x=3,y=1,3,5,9), (x=4,y=7),(x=5,y=1,2,9),(x=6,y=Null), (x=7,y=3,5,8,(x=8,y=Null),(x=9,y=4) There are 14 such two digit numbers that give a remainder of 3 when divided by the sum of the digits.

Probability that Devesh thought of the same number as Shubham = 1/14.

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3.

4.

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September 2018 Quantinuum, the Quant and Analytics committee of K.J. Somaiya Institute of Management Studies and Research aims to empower students and professionals alike to organize and understand numbers and, in turn, to make good and rational decisions as future managers. The newsletter published monthly consists of a gamut of articles for readers ranging from beginners to advanced learners so as to further enrich the young minds understand the contributions made to the field of mathematics along with a couple of brain- racking sections of Sudoku to tickle the gray cells.

For any further queries and feedback, please contact the following address: K.J. Somaiya Institute of Management Studies and Research, Vidya Nagar, Vidyavihar, Ghatkopar East, Mumbai -400077 or drop us a mail at quriosity.quantinuum@gmail.com Mentor: Prof. N.S.Nilakantan (+919820680741) Email – nilakantan@somaiya.edu Team Leaders: Purav Shah (+918511929416) VVNS Anudeep (+919441201685) Yatharth Jaiswal (+919969698361)

Editorial Team: VVNS Anudeep (+91 9441201685) Khushbu Mehta (+91 9930158610) Tanmay Nikam (+91 9699288587) Himanshu Data (+91 8105936820) Akshay Nandan R (+919176444022) Saumya Joshi (+91 9456684181) Abhishek Bawa (+91 9619995738) Kaustubh Karanje (+91 7738219050) Dhyan Baby K (+91 9809245308) Shubham Thakur (+91 7096045088)

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