Students take courses in stochastic processes, numerical techniques, Monte Carlo simulation and data modelling. They study financial economics, portfolio theory, derivatives valuation, and financial risk analysis. They also learn to extensively use the advanced features of Excel. And then writing application programs making use of the theories and methods they have learned.

Click here to get the Brochure and detailed Syllabus for the program




Participants learn about stochastic processes, numerical techniques, Monte Carlo simulation and data modelling which are used in Investment Finance by professionals in the field and how to implement them in practice. They study the underlying financial theories like financial economics, portfolio theory, derivatives valuation, and financial risk analysis. They also learn to extensively use the advanced features of Excel as modelling tool. Then they learn to write application programs making use of the theories and methods they have learned for valuations of Vanilla and Exotic Derivatives on equities, currency, interest rates, etc.

This program is intended for students who have a bachelor's degree in engineering or a master's degree in mathematics, statistics, physics and econometrics or an equivalent training, and wish to obtain positions in investment banks, hedge funds, etc., as quantitative analysts.


Dr. Amit Puniyani, Ph.D. (Statistical Physics and Computational Methods) Stanford University, Stanford CA, USA, B. Tech. (Engineering Physics) IIT Bombay. He is currently Associate (AVP), Quantitative Risk with Nomura, where he is responsible for VaR methodologies and works on historical simulation VaR process.
He has extensive experience working in financial industry on valuation and risk management of financial derivatives. He has extensive product knowledge encompassing fixed income, credit and hybrid equity derivatives. He has expertise in stochastic calculus based financial mathematics and experience in working with regression based models in mortgage finance and extensive experience applying statistical data analysis methods to financial data. He has expertise in presenting complex mathematical and statistical ideas to traders and sales people. He has well experienced in mentoring quantitative analysts, desk traders and programmers.
Previously he was Analyst (Manager), Valuation Control, Standard Chartered Bank, New York where he was responsible for Model usage & calibration review of Interest Rate/Foreign Exchange and Equity Derivatives desks.
Prior to that he worked as Associate, Quantitative Risk Analytics, Lehman Brothers, New York. He tested and validated Lehman Brothers Equity derivatives and credit derivatives pricing analytics.
He was Consulting Associate, Fixed Income Strategy research with J P Morgan Chase, New York where he supported clients and JPM trading desks on Futures and Options analytics.
He was a Teaching Associate in the Department of Physics, Stanford University where he taught undergraduate and graduate classes on Quantum Mechanics, classical mechanics and bio-statistics.

Dr. Binay Kumar Ray, Ph.D. (Econometrics) IGIDR, MBA ISB and BE (Mining Eng.) BITS Dhanbad. He is currently AVP Quantitative Risk with DBS Singapore. He is responsible for setting up Quant-based risk analytics.
Previously he was AVP Quantitative Risk team with Nomura Sec. (formerly Lehman Brothers) one of top four Wall Street Investment Banks. A Quant professional with more than half a decade of experience in Modeling, Measurement and Management of Quantitative risk and analytical projects. He is the first person to start the Quant Credit Risk Team in India for the Lehman Brothers for their entire Asia-Pacific trading desk and received an Outstanding Award for setting up the Quant Credit Risk team and exposure estimation. He was responsible for risk exposure estimation for structured Credit Derivatives trades generated from Asia trading desk. Currently he is involved in developing a simulation-based system for commodity derivatives.
Previously he was Independent Consultant with Stadiamarketing (USA), Roulac Global Places where he managed and worked with economics and data analyst team on different Economics projects.
He was Senior Consultant with the Decision and Marketing Science Team of General Electrics Capital International Services where he developed score-card model for retail (credit card, bank account, PLCC, Loan, Mortgage etc) for Acquisition, Attrition, Cross-sell and Customer Segmentation analysis for USA biggest retail chain firm.He was Senior Analyst, Analytics Team with Mckinsey and Company where he worked on and managed the Analytics area projects using various econometric and Time series techniques.
He is a visiting faculty at NITIE and NMIMS where he teaches Financial Econometrics, Time Series Analysis and Derivative Modelling.

Dr. M.P. Rajan, Ph.D. IIT-Madras, Assistant Professor, Mathematics, School of Mathematics, Indian Institute of Science Education & Research. He has extensive experience in industry, research and academics.
He had worked with a tier-I Wall Street Investment Bank, Goldman Sachs as Quant Analyst in the Fixed Income, Currency, Commodity and Strategy Division where he was engaged in research and development activities. He has designed and developed financial applications for interest rate and forex derivatives.
Previously he has been an Associate Professor in Financial Engineering and Mathematics with the Dept. of Mathematics, IIT-Guwahati where he headed the Quantitative Finance Research and Development Group. He also worked as Professor and Head of a Computer Science department, Anna University, Chennai.
He has extensive post doctoral research experience and has authored many research papers published in highly reputed international journals. Visited Stanford University, USA, University of Kaiserslautern, Germany and University of Linz, Austria as part of Post Doctoral research activities. He has been referee for many highly reputed International Journals. He also offers consultancy in financial engineering.

Kalyan Roy, Ph.D. candidate in Statistics from Indiana University, Bloomington, U.S.A., Master of Statistics Indian Statistical Institute, Kolkata, Bachelor of Statistics Indian Statistical Institute, Kolkata. He is a vastly experienced professional. In a career spanning over sixteen years he has held various positions in the industry.
He is currently working as a Quantitative Analyst with Deep Value Technology, an innovative firm specializing in high-performance algorithmic trading strategy vehicles. He is involved in studying stochastic models of equity market microstructure, developing ultra high frequency trading algorithms, statistical modeling, estimation of volatility based on ultra high frequency data, building factor models for the S&P500 stocks, statistical modeling of market and limit order arrival times and cancellation times and ultra high frequency equity price time series.
Previously he had worked as Statistical Consultant with Indiana University, U.S.A. where he was involved in modeling for researchers in physical, biomedical and social sciences. He had worked as Statistical Analyst with CITIBANK, Chicago, U.S.A. where he worked on consumer response modeling. He worked as Statistical Analyst with BANK ONE, Delaware, U.S.A. where he worked on consumer credit risk modeling. He had worked as Statistical Modeler with IMS America, Pennsylvania, U.S.A. He had been a Lead Consultant with Symphony Services, Bangalore, India and Market Research Director with IMRB International, New Delhi.

Sujit Vettam, M.S. (Statistics) Stanford University, USA and B.S. (Mathematics, Computer Science), Utah State University, USA, recipient of Annie-Hunsaker scholarship from the Department of Mathematics and Statistics, Utah State University.
Sujit is currently a Consultant providing clients with cutting edge solutions in Analytics, Predictive Modeling, Data Mining, Large Dataset Analysis and Marketing Optimization.
Previously he had worked as Statistician with Web Research and Analytics, Intuit Inc, Mountain View, California, USA where he was involved in analyzing large datasets of clickstream data and developed data mining models to predict customer usage patterns and behaviors. Prior to that he worked as Research Assistant with the Department of Statistics, Stanford University, California, USA.
He has been a Statistics Consultant with the Institute of Clinical Outcomes Research and Education, Stanford University, California, USA where he analyzed large insurance claims data searching for patterns and trends. He was a Statistics Consultant with Louisiana State University Health Science Center, Louisiana, USA, where he carried out statistical data analysis for a research project in clinical nutrition.
Among his many noteworthy works is an implementation of a new algorithm for web searching using a tree-based composed pages approach which was found to produce search results which were qualitatively better than the Google search results.

Anand Sabale, FRM, M.Tech. IIT Kanpur, BE Shivaji University. He is currently Partner at SPN Risk Solutions LLP, where he is involved in Statistical Arbitrage Trading in India Markets and advising broker’s prop desk for Stat-Arb trading.
He has over six years of experience in risk management consulting, performance analytics and algorithmic trading. He is involved in risk management consulting and performance analytics for hedge funds and fund of hedge funds.
Previously he had worked with Capital Metrics and Risk Solutions where he was involved in developing quantitative trading strategies and performance analytics for hedge funds.

Abhijit Biswas is currently a Director and Head of Product Development at Risk Infotech Solutions, India’s premiere company of Portfolio Risk Management Software Products. With over ten years worth of experience in research and development in the field of Financial Engineering, Risk Modelling, Derivatives and Risk Management Software Systems Development, he is one of the pioneers of Risk Modelling Technologies in India. He is also an expert in Monte-Carlo Simulation theories and systems and advanced simulation technologies applied to finance and general business risks .
As a Quant professional, he has created several breakthroughs in Risk Modelling Technology in India. He has co-developed India’s first and principal Multi-Factor Risk Model for the Equity Market, and India’s first and only one of a kind Multi-Factor Risk Model for the Fixed Income Market. He has also developed India’s first commercial grade large scale Monte Carlo Simulation system for business analytics using Excel spreadsheet models.
He received Venture Capital funding to start up one of India’s first software product companies to research and develop risk management systems in India which caters to major global financial institutions.
He has been a consultant to major global financial institutions in risk management domain. He has conducted training programs on statistics, econometrics, simulations, etc. for the top and mid level executives of the National Stock Exchange. He has conducted training programs for the Bombay Stock Exchange and other institutions.

Vishal Singhi, is the Chief Manager – Treasury in a top private bank, where his responsibilities include structuring of Forex and interest rate derivative products, designing hedging strategies, risk analysis, pricing of path dependent exotic options, etc. He has over five years of experience in industry and also in teaching in business schools. He has done MMS in Finance and Certificate Course in Financial Engineering.

Ujwal Dinesh works with one of the top four Wall Street Investment Banks as Credit Analyst where he is responsible for structuring and recommending exposure for fund-based, non fund-based and derivative facilities. He has experience of statistical modelling of short-term interest rates in India. He has been a visiting faculty at leading business schools. He is an MBA from IIM-Calcutta, BE, FRM, CFA (Level-III candidate).

A Bachelors degree in engineering or a Master's degree or equivalent in Mathematics / Statistics / Physics / Econometrics / Actuarial Science from good instituitions. Candidates must have good exposure of Multi-variate Calculus, Linear Algebra, Probability and Statistics.

Good knowledge of any programming language.

Good knowledge of MS Excel.

Applicants in their final year bachelor's/master's degree course (as applicable) are also eligible to apply.

Career Opportunities

Modern Investment Management has become very much mathematical and statistical in nature, it is now much more of science than arts, specially where investments in complex financial instruments and complex trading/investment strategies are concerned. That is the reason that high-end investment firms that invest in derivatives are opting for people who have strong quantitative skills for structuring or valuation of complex financial instruments and for devicing superior investment strategies.

This has opened up very exciting and rewarding career opportunities in the field of Quantitative Investment Management for candidates who come with academic background in engineering, mathematics, and other numerical specializations. Needless to say, that apart from the stimulating intectual challenges that careers in this field offer to the mathematically talented individuals, the compensations are quite handsome indeed.

The course prepares candidates for careers as quantitative investment managers or quantitative analysts with financial institutions like investment banks, hedge funds, private equity firms, large broking houses, investment research and analytics firms, etc.

Placement

IIQF provides placement assistance to all students who successfully complete the program. We have an active placement program in place to provide job opportunities to our students in relevant areas.

IIQF has been engaged by top Wall Street Investment Banks for recruitment of personnel for their Quant teams. We receive enquiries from investment banks, investment analytics firms, hedge funds, financial software companies and other financial institutions for placement of our students in their Quant teams.

Students from this course will get placement support for positions in investment banks, hedge funds, analytical firms, proprietary tradings desks of large broking houses, etc.

Salaries of quantitative analysts vary depending on their experience and background. Salaries for this profile range from 6 Lacs p.a. for freshers to 25 Lacs p.a. for candidates with a few years of experience.

IIQF is glad to announce that even before the completion of the 1st batch of its "Certificate Program in Applied Mathematical Finance for Engineers" some of the top firms have made pre-placement enquiries from this batch for positions in their Quant teams. Following is an indicative list of such firms:

Course Details

Course duration	4 Months (150 Hours)
Course schedule	Saturdays and Sundays

Course Calendar

Centre	Course Start Date	Admission Test	Seats	Course Fee
Mumbai	March 31, 2012	Feb 25 and Mar 17, 2012	Limited to 20	INR 75,000/- plus taxes

Admission Process

Candidates may apply online for admission to the course. Admission will be based on the candidate’s academic background, professional experience and admission test here .