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How does this Program equip students for a successful career in financial engineering?

How does this Program equip students for a successful career in financial engineering?. technically skilled and financially streetwise (development of an intuitive mind) Assessing risk – portfolio level or individual structured products; statistical analysis, stress testing

leah-morrison
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How does this Program equip students for a successful career in financial engineering?

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  1. How does this Program equip students for a successful career in financial engineering? • technically skilled and financially streetwise(development of an intuitive mind) • Assessing risk – portfolio level or individual structured products; statistical analysis, stress testing • Empirical methods and statistical tools in financial analysis • Developing structured products from the ground up – nature of risks, hedging strategy, pricing vehicles (implementation of model calculations and interpretation of results)

  2. Technical skills trained • Understanding the complexity in structured products: Analytics of pricing models and their numerical implementation • Fundamental concepts in financial economics • Analytic statistical and stochastic tools: Stochastic Calculus, Financial Time Series, • Use of statistical packages • Mastery of a high level programming language (C++)

  3. Courses in the MSc Program MAFS501 Stochastic Calculus [Fall, 08] Instructor: Professor B.Y. Jing of Mathematics Department Meeting hours and Venue: Thurs 19:30pm - 20:50pm;  Sat:  9:00am - 10:20am;   Room 4502 Foundation courses • Brownian motions. Diffusion processes. • Ito’s calculus.

  4. MAFS502 Advanced Probability and Statistics [Summer, 08] For those full-time students who have missed MAFS502 in the summer session, you are advised to take either MATH541 Advanced Probability and Statistics I (Prof B.Y. Jing) or MATH531 Advanced Numerical Methods or MATH551 Mathematical Methods in Science and Engineering I

  5. Financial Mathematics MATH571 Mathematical Models of Financial Derivatives [Fall, 08] Instructor: Prof Y.K. Kwok of Mathematics Department Meeting hours and Venue: Tues and Thurs 11:00am - 12:20pm;  Room 4502 • Black-Scholes-Merton pricing framework • Dynamic hedging, replicating portfolio • Martingale theory of option pricing • Risk neutral measure

  6. MAFS524 Software Development with C++ for Quantitative Finance [Fall, 08] Instructor: Dr C.D. Shum Meeting hours and Venue: Sat 11:00am - 12:20pm; Sat:  13:30pm - 14:50pm;   Room 2612A • Abstract data types • Object creation; Initialization • Toolkit for large scale component programming

  7. MAFS601 Special Topics in Financial Mathematics[Fall, 08] “Fixed Income Derivatives and Structured Hybrid Products” Instructors: "quants" in industry Meeting hours: Saturday 15:30pm - 18:20pm This topic course discusses the product nature, hedging, pricing and risk management methodologies of the commonly traded fixed income derivatives and structured hybrid products in the financial markets. Products include exotic swaps, equity-linked  products, structured credit derivatives, and others. Illustrative case studies of real financial products will be provided.

  8. MATH572 Interest Rate Models[Spring, 09] MAFS521 Mathematical Models of Investment[Spring, 09] MAFS523 Advanced Credit Risk Models[Spring, 09] MAFS525 Computational Methods for Pricing Structured Financial Products[Summer, 09]

  9. Statistics courses MAFS511 Advanced Data Analysis with Statistical Programming[Fall, 08] Instructor: Professor Mike So of ISMT Dept Meeting hours and Venue: Tues 19:30pm - 22:20pm;  Room 4502 • Reading and describing data • Categorical data and longitudinal data • Correlation and regression • Nonparametric comparisons Implementation of statistical tools in SAS

  10. MAFS522 Quantitative and Statistical Risk Analysis[Spring, 09] MAFS512 Applied Multivariate Analysis[Spring, 09] MAFS513 Quantitative Analysis of Financial Time Series[Spring, 09]

  11. 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.

  12. 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 elective* or independent project (MAFS 699) • Free elective can be any mathematics course at 300-level or above, • or any course outside the department at 500-level course or above. • Maintain a graduation grade point average of B grade or above.

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