Indian Institute of Quantitative Finance
Indian Institute of Quantitative Finance
Center of Finance Excellence - Quantitative Finance and Risk Management
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Certificate Program in
Applied Mathematical Finance for Engineers

Previous Batch - Mumbai.
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MoreInformation Mathematical Finance
Mathematical Finance, or Quantitative Finance as it is alternately known, is a multidisciplinary field involving the application of theories from financial economics, physics, mathematics, probability, statistics, operations research and econometrics using the methods and tools of engineering and the practice of computer programming to solve the problems of Investment Finance.

MoreInformation Applied Mathematical Finance
Modern Investment Finance is hugely dependent on the implementations of the theories and techniques of mathematical finance. Generally the language of choice for Quant implementations is C++ along with tools like Matlab, Mathematica, Stata, etc. and of late R language has also become popular. Excel has also come to be used as a Modelling tool for the fact that the models can be built and tested quickly and changed very easily. Alongside VBA has also gained following because of the ease of its use and its less steep learning curve and it being the back-end language of Excel macros which is required when building models in Excel.

Mathematical Finance has emerged as a very prospective career prospect for people with strong mathematical background like those coming from engineering, mathematics, statistics, physics or econometrics background. The best of the global financial institutions like Investment Banks, Hedge Funds, etc. hire people having strong quantitative skills for “Quant” jobs. This is also a very rewarding and exciting career option for such people as there is ample scope for applying their numerical and creative skills to design new things, be it like devicing new investment strategies or be it structuring new financial instruments or be it finding methods to value them. They are continuously competing with their peers and some of the best of minds in the market and have to out-perform them to generate superior returns, which is intellectually a very challenging work, and this makes it all the more thrilling.

MoreInformation Course Overview
The Certificate Program in Applied Mathematical Finance for Engineers (AMFE) prepares students for technically sophisticated jobs with financial institutions, financial service providers, financial consulting services and financial software companies. The program is intended for students seeking comprehensive technical knowledge of vanilla and exotic derivatives pricing, hedging, trading and investment strategies and portfolio management in equity, currency, interest rates, credit and mortgages.

This is a short-term course that requires six months of study, which makes it attractive to students with strong quantitative skills who are willing to make a quick head start in the investment finance industry. The applied nature of the program implies the fact that there is great emphasis in it to impart the practical implementation skills and techniques that are actually used by practitioners in top financial institutions in the industry, so much so that almost sixty percent of the course time is devoted to teaching implementation skills along with rigorous theoretical discourse.

As an applied discipline, financial institutions look for the following skill sets in the candidates for positions in their Quant teams :
  • Strong quantitative background
  • Sound knowledge of the underlying financial theories
  • Very good programming skills in C++ / VBA
  • Along with these they also demand knowledge and skills of using advanced features of Excel and expertise in using Excel as a tool for modeling.

    This course is designed specifically to meet these exact needs. This is a course on modelling and applications of mathematics, statistics and econometrics in investment finance. The program covers the all the technical and quantitative aspects of investment finance used in top financial institutions.

    The combination of skills imparted through this program viz. understanding of complex financial theories, rigorous exposure to the underlying mathematical and statistical theories, practical financial modeling ability and computer implementation proficiency, is in high demand in the industry, and which the employers do not generally find in graduates of standard MBA or engineering programs.

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

    MoreInformation Course Highlight - Top Rated Faculty
    The AMFE course is conducted by a world-class faculty team. You are taught by the best faculty in this field unmatched by any university or institution anywhere in India. Some of the good educational institutions have good academicians, some of them world-class; the global best educational institutions have world-class academicians as well as practitioners; we have both.

    The faculty is comprised of :
  • Distinguished academicians who have been educated from best universities in US, UK and India, they have taught Quantitative Finance at the best universities in US and UK and they have conducted a considerable amount of pre-eminent research work in Quantitative Finance and allied fields and the AMFE curriculum is enriched by their research work.

  • Top Quant practitioners who have been educated from best universities in US, UK and India and have worked at the highest level in Quantitative Finance at some of the topmost Wall Street investment banks and financial institutions and have done some significant research work during their practise.

    MoreInformation Course Highlight - Specialized Curriculum
    The AMFE program curriculum has been designed in consultation with Quant practitioners from top Wall Street Investment Banks and financial institutions keeping in view their exact job requirements in terms of the skill-sets that these institutions expect and demand from the candidates who want to take up these Quant jobs. The curriculum is at par with global best in the field. The curriculum is sought to be kept up-to-date and presently relevant by regularly updating it with the latest theoretical developments in the academic domain and the latest practical implementation and technological developments in the industry in this field. You will learn how to combine theory and computational methods with the practical knowledge of the real-world application areas of these skills.

    MoreInformation Course Highlight - Outstanding Classmates
    Students who are admitted to the AMFE program have some things in common – high intellectual caliber, strong analytical skills and strong interest in finance. In order to ensure that the students admitted to the program have the ability to succeed in the program, the admissions committee considers all aspects of a student's application including the admission test scores, academic grades, work experience and any research work. Due to the specific eligibility requirements in terms of degrees, students will have advanced backgrounds in quantitative disciplines such as mathematics, statistics, engineering, physical sciences, operations research, computer science, or econometrics. You will find graduates, post-graduates and Ph.D.s from IITs and IIMs amongst your classmates. This enables a high level of intellectual discourse during the course of the program. It is also expected that most students will have work or research experience in which they have applied quantitative skills. This allows exchange of lot of practical work ideas amongst the peer group.

  • MoreInformation What You Study
    Participants learn Stochastic Calculus, Numerical Techniques, Monte Carlo Simulation, Derivative Valuations and Derivatives Trading Strategies 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 pricing models. They also learn to extensively use the advanced features of Excel VBA as modelling tool. Then they learn to write financial 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.

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

    MoreInformation Who Should Attend
    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 quantitative analysts positions in investment banks, hedge funds, broking houses, financial analytics firms, risk management consultancy firms, etc.

    MoreInformation Faculty

    Dr. Amit Ram, Ph.D. (Statistical Physics and Computational Methods) Stanford University, Stanford CA, USA, B. Tech. (Engineering Physics) IIT Bombay. He is currently Vice President, 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 where 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.
    Prior to that 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, is currently Assistant Professor, Mathematics, School of Mathematics, Indian Institute of Science Education & Research.
    He has the rare combination of having 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.

    Dr. Rituparna Sen, Ph.D. (Statistics) University of Chicago, Graduate student in Statistics, Stanford University, Master of Statistics, Indian Statistical Institute, Bachelor of Statistics Indian Statistical Institute. She is Assistant Professor, Indian Statistical Institute, Chennai.
    She has vast teaching experience. She was previously Assistant Professor, University of California at Davis, Davis, CA, USA, where she taught courses on Applied Statistics, Mathematical Statistics, Mathematical Finance and allied disciplines. Prior to that she was Teaching Assistant at Stanford University.
    Her research interests include Application of Statistics in Finance, in areas like Convergence of stochastic processes, Inference for diffusions, Bayesian filtering, asymptotic inference, likelihood estimation, functional data analysis, hidden Markov models, extreme values, multivariate time series, high-dimensional data, discontinuous asset price, stochastic volatility, optimal derivative pricing and hedging in incomplete market, covolatility for asynchronous data, volatility in the presence of microstructure noise, online auctions, exchange rates, interest rates, energy markets, risk analysis, contagion.
    She has numerous research publications to his credit in top international journals. She has won numerous awards and fellowships and has presented papers at major global conferences.

    Abhijit Biswas is the founding Director and Head of Product Development at Risk Infotech Solutions, India’s pioneering company in Portfolio Risk Management Software Products. He is currently consultant to HPC Links which is involved in the development of Quantitative Finance solutions and services using High Performance Parallel Computing technologies in Algorithmic Trading, Risk Analytics, etc. He is also consultant to financial institutions for Volatility Trading systems. He is also the founding Director of IIQF.
    As a Quant professional, he has created numerous 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 also 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. He regularly conducts training programs for FRM aspirants across India.

    Amrendra Kumar, M.Sc. (Economics) IGIDR and Statistics for Financial Engineers from University of California, Berkely (Haas School of Business) is Senior Trader and Strategist for International Markets (Fixed Income, Commodities and Energy) at Centaurus Financial Services India where he is responsible for developing quantitative strategies for Trading & Risk Management and mentoring/managing new Traders.
    As a Fixed Income Trader his experience is in Trading Bond/Treasury futures, STIR futures, Eurodollars, Swaps, Commodities and Energy products in the International Markets across exchanges (CME, CBOT, LIFFE, EUREX, ICE, EURONEXT).
    Previously he had worked with Bank of Baroda in the Economic Analysis Wing where he worked on the issue of Benchmark Prime Lending Rates (BPLR), the Interest rates pass through mechanism in India and the financial stability of the banking system. He has authored paper on Effectiveness of the Black-Scholes model in Pricing options on S&P CNX Nifty and presented in The Indian Econometric Society (TIES) Conference.

    Anand Sabale, FRM, M.Tech. IIT Kanpur, BE Shivaji University. He is 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.

    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 the Head of Quantitative Analytics at Capital Metrics & Risk Solutions.
    He is a vastly experienced professional. In a career spanning over sixteen years he has held various positions in the industry. Previuosly he worked as a Quantitative Analyst with Deep Value Technology, an innovative firm specializing in high-performance algorithmic trading strategy vehicles where he was 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.
    Prior to that 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.

    Vishal Singhi, MMS (Finance), Certificate in Financial Engineering, is currently working with a top private sector bank heading the derivatives trading desk.
    Previuosly he was the Chief Manager of Treasury at Kotak Mahindra Bank, where his responsibilities included structuring of Forex and interest rate derivative products, designing hedging strategies, risk analysis, pricing of path dependent exotic options, etc. He has over seven years of experience in industry and also in teaching in business schools.

    MoreInformation Eligibility Requirements
  • 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.

    MoreInformation 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.

    Candidates having a strong numerical background have a very bright chance of making a very rewarding career in this field with the largest of investment banks and other financial institutions. Salaries of quantitative analysts vary depending on their experience and background. In India presently, salaries for this profile may range from 6 Lacs p.a. for freshers to 30 Lacs p.a. for candidates with a few years of experience.

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

    IIQF has been engaged by a top Wall Street bank for recruitment of personnel for their Quant team. We receive enquiries from investment banks, investment analytics firms 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.

    MoreInformation Course Details
    Course duration6 Months (240 Hours)
    Course scheduleSaturdays and Sundays

    MoreInformation Course Calendar
    Centre Course Start Date Admission Test Seats Course Fee
    Mumbai April 12, 2014 March 30, 2014 Limited to 20 INR 125,000/- plus taxes

    MoreInformation 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 .

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