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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
Roles and responsibilities • 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.
Relevant courses in our MSc Programs Financial Mathematics MATH571 Mathematical Models of Financial Derivatives [Fall, 07] MATH572 Interest Rate Models [Spring, 08] MAFS524 Software Development with C++ for Quantitative Finance [Spring, 08] MAFS525 Computational Methods for Pricing Structured Financial Products [Spring, 08] MAFS523 Advanced Credit Risk Models [Summer, 08]
Statistics courses MAFS513 Quantitative Analysis of Financial Time Series [Fall, 07] MAFS511 Advanced Data Analysis with Statistical Programming [Spring, 08] MAFS522 Quantitative and Statistical Risk Analysis [Summer, 08]
Foundation courses MAFS501 Stochastic Calculus [Fall, 07] MAFS502 Advanced Probability and Statistics [Fall, 07]
MAFS 501Stochastic 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.
MAFS 513 Quantitative Analysis of Financial Time Series [3-0-0:3] Analysis of asset returns: autocorrelation, predictability and prediction. Volatility models: GARCH-type models, long range dependence. High frequency data analysis: transactions data, duration. Markov switching and threshold models. Multivariate time series: cointegration models and vector GARCH models.
MATH 571 Mathematical Models of Financial Derivatives [3-0-0:3] Black-Scholes-Merton framework, dynamic hedging, replicating portfolio. Martingale theory of option pricing, risk neutral measure. Exotic options: barrier options, lookback options and Asian options. Free boundary value pricing models: American options, reset options.
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. • 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.