Why attending this Program Sharpening the quantitative skills in   Pricing, hedging and risk measurement of derivative securities   Implementing risk measurement and valuation models in software Developing the abilities in   Identifying and monitoring risk in valuation models   Assessment of the appropriateness of quantitative models and their limitations

Roles and responsibilities as a quantitative analyst  Develop mathematical models for pricing, hedging and risk management of derivative securities.  Support of trading activities by explaining model behavior, identifying risk sources in portfolios, carrying out scenario analysis.  Design efficient numerical algorithms and implement high performance computing solutions – delivery to systems and applications.

How to prepare yourself for a Quants job in the financial market?   Strong knowledge of option pricing theory (quantitative models for pricing and hedging)   Strong software design and development skills using C++   Mastery of advanced mathematics and numerical analysis arising in financial modeling (probability theory, stochastic processes, numerical analysis) General skills: Analytic, quantitative and problem solving skills; strong communication skills

Courses in MSc Program Financial Mathematics MATH571Mathematical Models of Financial Derivatives [Fall, 08] MAFS526Fixed Income Derivatives[Fall, 08] MAFS513Mathematical Models of Investment[Summer, 08] [Summer, 09] MATH572Interest Rate Models[Spring, 09] MAFS523Advanced Credit Risk Models[Summer, 09] MAFS524Software Development with C++ for Quantitative Finance[Spring, 09] MAFS525Computational Methods for Pricing Structured Financial Products[Spring, 08] MAFS527 Computational Tools and Technologies for Building Financial Applications [Fall, 08]

Statistics courses MAFS513Quantitative Analysis of Financial Time Series [Spring, 09] MAFS511Advanced Data Analysis with Statistical Programming[Fall, 08] MAFS512 Applied Multivariate Analysis [Spring, 09] MAFS522Quantitative and Statistical Risk Analysis [Summer, 09]

Foundation courses MAFS501Stochastic Calculus [Fall, 08] MAFS502Advanced Probability and Statistics [Fall, 08]

MATH 571 Mathematical Models of Financial Derivatives[3-0-0:3] Fundamental Theorem of Asset Pricing. Risk neutral valuation approach. Black-Scholes-Merton framework, dynamic hedging, replicating portfolio. Martingale theory of option pricing, risk neutral measure. Stochastic volatility models.

MATH 572 Interest Rate Models [3-0-0:3] Yield curves. Sort rates and forward rates. Short rate models: Vasicek and CIR models. Term structure models: Hull-white fitting procedure. Heath-Jarrow-Morton pricing framework. LIBOR and swap market models. Affine models.

MAFS 521 Mathematical Models of Investment[3-0-0:3] Utility theory, stochastic dominance. Portfolio analysis: mean-variance approach, Two- Fund Theorem. Capital asset pricing models. Arbitrage pricing theory. Consumption-investment models.

MAFS 523 Advanced Credit Risk Models [3-0-0:3] Credit spreads and bond price- based models. Credit spread models. Intensity based models. Credit rating models. Firm value models. Industrial codes: KMV, CreditMetrics and CreditRisk+. Default correlation. Pricing of correlation products.

MAFS 525Computational Methods for Pricing Structured Products[3-0-0:3] Lattice tree methods, finite difference methods, Monte Carlo simulation. Structured products analyzed include: Convertible bonds, equity-linked notes, quanto currency swaps, collateralized debt obligations, mortgage backed securities, volatility swaps.

MAFS 501 Stochastic Calculus[3-0-0:3] Random walk models. Filtration. Martingales. Brownian motions. Diffusion processes. Forward and backward Kolmogorov equations. Ito’s calculus. Stochastic differential equations. Stochastic optimal control problems in finance.

MAFS 502 Advanced Probability and Statistics [3-0-0:3] Probability spaces, measurable functions and distributions, conditional probability, conditional expectations, asymptotic theorems, stopping times, martingales, Markov chains, Brownian motion, sampling distributions, sufficiency, statistical decision theory, statistical inference, unbiased estimation, method of maximum likelihood.

Upon completion of the program, students are expected to achieve the following intellectual abilities: A broad knowledge and understanding of the financial products commonly traded in the markets and various practical aspects of risk management. A broad knowledge and understanding of the financial products commonly traded in the markets and various practical aspects of risk management. Use of mathematical and statistical tools to construct quantitative models in derivative pricing, quantitative trading strategies, risk management, and scenario simulation, including appropriate solution methods and interpretation of results. Use of mathematical and statistical tools to construct quantitative models in derivative pricing, quantitative trading strategies, risk management, and scenario simulation, including appropriate solution methods and interpretation of results.

To graduate from the MSc program, each student is required to complete 30 credits of which  6 credits from the list of foundation courses  9 credits from the list of courses in statistics  9 credits from the list of courses in financial mathematics  6 credits as free electives* Needs to maintain a graduation grade point average of B grade or above.