Center of Excellence in Quantitative Finance and Financial EngineeringINDIAN INSTITUTE OF QUANTITATIVE FINANCE

CERTIFICATE PROGRAM IN APPLIED MATHEMATICAL FINANCE

FOR ENGINEERS

n, has emerged as a veryound like those coming fromhe best of the global financial strong quantitative skills forsuch people as there is ampleings, be it like devicing newinding methods to value them.inds in the market and have tory challenging work, and this

n of theories from financialthods and tools of engineeringent Finance.

the theories and techniques oftations is C++ along with toolscome popular. Excel has also built and tested quickly andhe ease of its use and its lesshich is required when building

practitioners from top global that these institutions expectbs. The program covers the

financial institutions.

ABOUT THE COURSE

Mathematical Finance, or Quantitative Finance as it is alternately knowprospective career prospect for people with strong mathematical backgrengineering, mathematics, statistics, physics or econometrics background. Tinstitutions like Investment Banks, Hedge Funds, etc. hire people having“Quant” jobs. This is also a very rewarding and exciting career option for scope for applying their numerical and creative skills to design new thinvestment strategies or be it structuring new financial instruments or be it fThey are continuously competing with their peers and some of the best of mout-perform them to generate superior returns, which is intellectually a vemakes it all the more thrilling. Mathematical Finance is a multidisciplinary field involving the applicatioeconomics, mathematics, statistics, physics and econometrics using the meand the practice of computer programming to solve the problems of Investm Modern Investment Finance is hugely dependent on the implementations of mathematical finance. Generally the language of choice for Quant implemenlike Matlab, Mathematica, Strata, etc. and of late R language has also become to be used as a Modelling tool for the fact that the models can bechanged very easily. Alongside VBA has also gained following because of tsteep learning curve and it being the back-end language of Excel macros wmodels in Excel. This is a short-term course, designed in consultation with the Quant investment banks and financial institutions and keeping in view the skill-setsand demand from the candidates who want to take up these Quant jotheoretical and implementational aspects of Investment Finance used in top

COURSE OBJECTIVE This being a -on” program with a lent blend of th orld l applicationsfrom the indu aims to equip the pa ts with both sou theo ackground aswell as pract lementational skills. ignments are d ilar problems thatthe participan ncounter in their job

The course directors are practising Qu Placement assistance in Quant teams Exposure to real-world models actually The pedagogy followed involves hands

COURSE HIG S

Participants learn about stochastic procmodelling which are used in Investment in practice. They study the underlyinderivatives valuation, and financial risk aof Excel as modelling tool. Then they leamethods they have learned for valuationrates, etc.

LEARNING OUTCOME

WHO SHOULD ATTEND

This program is intended for students whmathematics, statistics, physics and econinvestment banks, hedge funds, etc., as

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mathematical and statistical in nature, it is nownts in complex financial instruments and complexreason that high-end investment firms that investuantitative skills for structuring or valuation of

nvestment strategies.

reer opportunities in the field of Quantitative with academic background in engineering,dless to say, that apart from the stimulating

o the mathematically talented individuals, the

ve investment managers or quantitative analystsunds, private equity firms, large broking houses,

PEDAGOGY The basic approach is to learn by doing. The trainiextensive use of real world models. Course delivery w Live Models Whiteboard

Lecture handouts and spreadsheets models will be m

CAREER OPPORTUNITIES Modern Investment Management has become very mmuch more of science than arts, specially where invetrading/investment strategies are concerned. That isin derivatives are opting for people who have strocomplex financial instruments and for devicing super This has opened up very exciting and rewardinInvestment Management for candidates who cmathematics, and other numerical specializations.intectual challenges that careers in this field offcompensations are quite handsome indeed. The course prepares candidates for careers as quanwith financial institutions like investment banks, hedinvestment research and analytics firms, etc.

teractiv

PLACEMENT IIQF pr ent assistance to all studen successfully complete the pr We have anactive p gram in place to provide job ities to our students in releva s. IIQF ha ged by a top Wall Street bank ruitment of personnel for the t team. Wereceive m investment banks, invest alytics firms and other financial institutions forplaceme dents in their Quant teams. Student course will get placement support for positions in investment banks, hedge funds,analytic rietary tradings desks of large broking houses, etc.

Course Start Date Course Fee (Incl. Taxes)

i 22nd January, 2011 INR 66,180 5th February, 2011 INR 66,180

COURSE

COURSE Course Course

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CALENDAR

DETAILS

duration 3 Months (112 Hours)

Schedule Saturdays and Sundays

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Module 101B – Fundamentals of Investment Finance (24 Hours)

Introduction to Finance

1. Capital structure of companies 2. Financial Statements 3. Types of Financial Markets

a. Capital Market b. Debt Market c. Money Market d. Derivatives Market

4. Primary Market and Secondary Market 5. Financial Market Operations – Stock and other

Exchanges, OTC markets, Intermediaries,Clearing House mechanisms / Clearing Corporation

6. Forms of financial returns 7. Relative and Absolute returns, Continuous and Discreet

returns 8. Corporate actions and their effects on return calculations 9. Speculation, Hedging and Arbitrage

Introduction to Financial Derivatives

Introduction to Fixed Income Instr

1. Time Value of Money 2. Present and Future Values 3. Interest Rates – Discret and Continuous

Compounding 4. Risk-free Rate of Interest 5. Zero Coupon (Discount) Bon upon Bonds 6. Bond Characteristics 7. Bond Types – Fixed Rate, Fl e, Inverse Floater Rate, etc. 8. Fixed Income & Money Ma s – Coupon Rate, Current

Yield, Yield-To-Maturity, Dis d, Money Market Yield, Par Yield, Bond-equivalent Yield, Call/Yield-To-Put

9. YTM and Spot Rates 10. Term Structure of Interest Ra Curve

a. YTMC b. ZCYC / Spot Curve c. Par Yield Curve

11. Bond Pricing – using ZCYC with discrete compounding or continuous compounding

12. Price Yield Relationship d Credit Risk Premium

s

Rates by ping Inverse ction

ethods olation Interpoladified Dur

COURSE SYLLABUS

uments

e Comp

ds and Co

oating Ratrket returncount Yiel Yield-To-

tes / Yield

and YTMC

Spreads –

Bootstrap

Floaters

tion ation, Ma

ounding

caulay’s Duration

1. Equity and Equity Index Derivatives - Forward, Futures and Options

2. Fixed-Income and Interest Rate Derivatives – IRS, FRA 3. Currency / Foreign Exchange (FOREX) Derivatives -

Swaps, Forwards, Futures and Options 4. Commodity derivatives, cost of carry, lease rate,

convenience yield

13. Corporate Bonds an Fixed Income Mathematic

1. Forward Rates 2. Estimating Forward3. Forward Rate Curve4. Pricing Floaters and5. Yield Curve Constru

a. Bootstrap mb. Linear Interpc. Cubic Spline

6. Dollar Duration, Mo7. Convexity 8. PVBP

Stochastic Processes

1. The random behaviour of asset prices 2. Continuous-time Stochastic Processes

a. Markov Process, Markov Chains b. Weiner Process / Brownian Motion c. Geometric Brownian Motion (GBM) d. Generalized Weiner Process e. Ito Process f. Ornstein–Uhlenbeck Process

Stochastic Differential Equations and Solutions

1. Stochastic Differential Equations 2. Ito’s Lemma 3. Feynman-Kac Formula 4. Fokker-Planck Equation / Kolmogorov Forward Equations 5. Kolmogorov Backward Equations 6. Levy’s Theorem 7. Martingales and Measures 8. Girsanov’s Theorem 9. Brownian Bridge 10. Affine Stochastic Processes

Module 105B – Stochastic Calculus for Financial Engineering (32 Hours)

Simulation Techn ques

1. Introductio to Numerical Simulations 2. Monte Car Simulations 3. Generation of random numbers of different distributions –

Transform tion of Uniform Distribution 4. Correlated random numbers generation – Cholesky

Decompos ion 5. Quasi Mon e Carlo Simulation 6. Application of Monte Carlo Simulation to Price Options 7. Solving st chastic integrals using Monte Carlo integration

techniques8. Variance R duction Techniques 9. Historical Simulation

Monte Carlo Sim lation in Excel

1. Generating2. Simulation

Monte Carlo Sim

1. Generatingtransform

2. Single stoc3. Generating4. Portfolio o

Module 106 – Monte Carlo Simulations fo Financial Engineering (16 Hours)

i

nlo

a itt

o e

u

r

different distributions in Excel of stock prices in Excel

lation using VBA / C++

Normal random numbers using Box-Muller

price simulation correlated random numbers stocks simulation

u

k

f

Derivatives Products and Strategies

1. Hedging Strategies Using Futures 2. Arbitrage 3. Trading Strategies with Derivatives 4. Exotic Options

a. Asian Options b. Bermudan Options c. Forward Start Options d. Barrier Options e. Shout Options f. Chooser Options g. Lookback Options h. Exchange Options i. Binary / Digital Options j. Rainbow Options k. Basket Options l. Spread Options m. Compound Options

Options Pricing Fundamentals

1. Replicating Portfolios 2. Risk Neutral Valuation 3. Analytical Models – Black-Scholes-Merton 4. Numerical Methods – Cox-Rubinstein Binomial Tree, Boyle

Trinomial Tree, Monte-Carlo Simulation 5. Option Greeks 6. Implied Volatility 7. Volatility Skews, Volatility Smiles/Frowns, Volatility Term

Structures, Volatility Surface

Equity / Equity tions Pricing in VBA / C++

1. Valuation ean Options using: a. B odel b. B choles (BS) Model c. C Black-Scholes Greeks

2. Valuation can Options using: a. V ith numerical methods

mial Tree omial Tree te Difference Method

b. A olutions l-Geske-Whalley one-Adesi-Whalley

3. Valuation Options using Monte Carlo Simulation 4. Valuation r Options using Monte Carlo Simulation

Currency Deriv

1. Single-cu2. Cross-cu

Module 107B – Derivatives Valuation (40 Hours)

Index Op

of Europinomial Mlack and Somputing of Amerialuation w

i. Binoii. Triniii. Fini

nalytical si. Rolii. Bar

of Asian of Barrie

atives Pricing in VBA

rrency Options rrency Options

/ C++

s and e-Backed Securities

derwr ages paym ls ks in and mortgage-backed securities luation age-backed securities b-prim e design rtgag uritization, sub-prime CDOs

rivati g in VBA / C++

dit R curitization dit D ps (CDS) dit Sp ions (CSO)

llatera t Obligations (CDO)

of Sw

rest Rrrency

3. Equity Sriance

d. Black-Derman-Toy Model

Mortgag

iting mortgent modemortgages of mortge mortgag

es and sec

ves Pricin

isk and Seefault Swaread Optlized Deb

aps in VBA / C++

ate Swap Swap

Module 107B – Derivatives Valuation (contd.)Mortgage

1. Un2. Pre3. Ris4. Va5. Su6. Mo

Credit De

1. Cre2. Cre3. Cre4. Co

Valuation

1. Inte2. Cu

Interest Rate Derivatives Pricing in VBA / C++

1. Interest Rate Term Structure Models d. Stochastic Spot Rate Models e. Black-Rendleman-Barter Model f. Vasicek Model g. Cox-Ingersoll-Ross (CIR) Model h. Ho-Lee Model i. Heath-Jarrow-Morton(HJM) Model j. Hull-White Model k. Black-Derman-Toy (BDT) Model l. Black and Karasinski Model m. Sandmann and Sondermann Model n. Kalotay-Williams-Fabozzi Model o. Brace-Gatarek-Musiela(BGM) Model and Jamshidian Model

2. Interest Rate Options valuation a. Black Model b. Vasicek Model c. Cox-Ingersoll-Ross Model

wap / Total Return Swap Swap

4. Va3. Valuation of Caps

d. Caplet e. Floorlet

4. Valuation of Swaption a. Payer Swaption b. Receiver Swaption

COURSE DIRECTORS

Dr. Binay Ray is AVP Quantitative Risk with one of the top four Wall Street Investment B is a quant professionalwith more than five years of experience in Modeling, Measurement and Management o ative risk and analyticalprojects. He is the first person to start the Quant Credit Risk Team in India for the first W t Investment Bank to setup its quant analytics team in India for their Asia-Pacific trading desk and received an Out Award for setting up theQuant Credit Risk team and exposure estimation. He is a visiting faculty at NITIE and NMIMS where he teaches Financial Econome e Series Analysis andDerivative Modelling. He is a Ph.D. (Econometrics), Executive MBA ISB and BE.

Kalyan Roy, is a vastly experienced professional. In a career spanning over sixteen yearthe industry. He is currently working as a Quantitative Analyst with Deep Value Technologin high-performance algorithmic trading strategy vehicles. He is involved in studying stomicrostructure, developing ultra high frequency trading algorithms, statistical modeling,ultra high frequency data, building factor models for the S&P500 stocks, statistical moarrival 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. whereresearchers in physical, biomedical and social sciences. He had worked as Statistical AU.S.A. where he worked on consumer response modeling. He worked as Statistical AnaU.S.A. where he worked on consumer credit risk modeling. He had worked as StatisPennsylvania, U.S.A. He had been a Lead Consultant with Symphony Services, BangaDirector with IMRB International, New Delhi. He is a Ph.D. candidate in Statistics from Indiana University, Bloomington, U.S.A. HStatistics from the Indian Statistical Institute, Kolkata and a Master’s degree in StatInstitute, Kolkata.

Vishal Singhi, is the Chief Manager – Treasury in a top private bank, where his responsiband interest rate derivative products, designing hedging strategies, risk analysis, pricing etc. He has over five years of experience in industry and also in teaching in businessFinance and Certificate Course in Financial Engineering.

anks. Hef Quantitall Streestanding

trics, Tim

s he has y, an innchastic m

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he was nalyst wlyst with

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e holds istics fro

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held various positions inovative firm specializingodels of equity market

n of volatility based onf market and limit order

involved in modeling forith CITIBANK, Chicago, BANK ONE, Delaware,eler with IMS America,a and Market Research

a Bachelor’s degree inm the Indian Statistical

lude structuring of Forexependent exotic options,. He has done MMS in

ative (IIQF) is established as a center of learning in the field ofinanc eering. IIQF is founded by leading finance professionals ande glob ience and expertise in specialized Quantitative Finance and Riskeduca ackground from the best of global institutions. It is the first

that e y focuses on this extremely specialized field.

ourse fields of Quantitative Finance, Financial Risk Management andhnique courses aim to equip professionals for careers that requires in q ve analysis, financial research, risk management, quantitativeancial ves structuring. There are specialized courses tailored to theprofessionals, engineers, mathematics/statistics graduates, management

tants, and others.

E O ANTITATIVE FINANCE

COURSE DIRECTORS Directo ad of Product Development at Risk Infotech So ndia’s premierenagem are Products. With over ten years worth of exp n research and

Finan eering, Risk Modelling, Derivatives and Risk ment Software one o eers of Risk Modelling Technologies in India. so an expert in ries an and advanced simulation technologies applied ce and general

has cr eral breakthroughs in Risk Modelling Technolo ia. He has co-rincipal tor Risk Model for the Equity Market, and India d only one of al for th ncome Market. He has also developed India’s first commercial gradelation r business analytics using Excel spreadsheet models.

l fundi t up one of India’s first software product companies to research andstems ich caters to major global financial institutions. major g ncial institutions in risk management domain. He has conducted trainingometri tions, etc. for the top and mid level executives of the National Stock trainin s for the Bombay Stock Exchange and other institutions.

Indian Institute of QuantitQuantitative Finance and Fentrepreneurs with extensivManagement domains and institute of its kind in India IIQF conducts specialized cAdvanced Quantitative Tecsophisticated technical skillasset management and finspecific needs of finance graduates, qualified accoun

INDIAN INSTITUT

Abhijit Biswas is currently a company of Portfolio Risk Madevelopment in the field ofSystems Development, he isMonte-Carlo Simulation theobusiness risks . As a Quant professional, hedeveloped India’s first and pkind Multi-Factor Risk Modelarge scale Monte Carlo SimuHe received Venture Capitadevelop risk management syHe has been a consultant to programs on statistics, econExchange. He has conducted

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NCE PVT. LTD."

the payment.

CONTACT DET ILS Mumbai: Indian Insti ute of Quantitative Finance, Module No. 24, Mastermind IV, Royal Palms IT Park, Goregaon (E), Mumbai - 4 0065 Contact Per on : Nitish Mukherjee Phone: +91 22-28797660 +91 9769860151

ADMISSION PROCESS Candidates may apply online for admission tacademic background, professional experience

ELIGIBILITY REQUIREMENTS Bachelor’s degree in engineering or a Mas

Physics or Econometrics from good instituLinear Algebra, Probability and Statistics.

Good knowledge of any programming langua Good knowledge of MS Excel.

REGISTRATION PROCESS Online Registration : http://www.iiqf.org/registration.html Modes of Payment : Mode 1 - Cheque/Demand Draft Payments are accepted in the form of Cheque/DD In favour of "INDIAN INSTITUTE OF QUANTITATIVE FINAPayable at Mumbai or Delhi. Please mention your name, email and telephone number along withPlease mail your payment to our Mumbai or Delhi office.

Mode 2 - Wire Tranfer (NEFT/RTGS) Payments can also be made through internet banking. Please contact us for details. Mode 3 – Credit Card Payments can also be made through credit cards. Please contact us for details. Offline Registration : Visit our offices at Mumbai or Delhi

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