1 / 35

Master of Science in Financial Mathematics and Stastistics

Master of Science in Financial Mathematics and Stastistics . Orientation Session, Fall 2009. Welcome!. What Make this Program Distinguished?. Derivative modeling Equity Fixed income Credit Inflation Hybrid and structured products Risk Management Financial economics.

valdemar
Download Presentation

Master of Science in Financial Mathematics and Stastistics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Master of Science inFinancial Mathematics and Stastistics Orientation Session, Fall 2009

  2. Welcome!

  3. What Make this Program Distinguished? • Derivative modeling • Equity • Fixed income • Credit • Inflation • Hybrid and structured products • Risk Management • Financial economics

  4. Teaching Staff from UST • Prof. Yue-Kuen Kwok, Financial Mathematics • Prof. Qi-Man Shao, Probaility • Prof. Bin-Yi Jing, Probability • Prof. Kani Chen, Statistics • Prof. Man-Yu Wong, Statistics • Prof. Shi-Qing Ling, Statistics • Prof. Mike So, Statistics • Visiting Prof. Jerome Yan, Finance • Dr. Mei-Choy Chiu • Prof. Lixin Wu, Financial Mathematics

  5. Teaching Staff from Outside • Dr. Chun-De Shum (former senior VP of JP Morgan), Quant Programmer • Prof. Harry Zheng (Imperial College), Financial Mathematics • Prof. M. Dai (NUS), Financial Mathematics • Prof. M. Kijima (Kyoto Univ.), Financial Mathematics and Applied Economics • Dr. S.Y. Leung (Citigroup) • Dr. Bon Ho (Macquaire) • Mr. Y.F. Lam (HSBC) • Mr. G.X. Wu (Essense Security)

  6. Regulations for Course Taking • Full-time students are advised to take no more than four courses per semester • Part-time students should take nor more than two courses, or he/she should change to full-time mode (The change of mode can only be made once).

  7. Degree Requirement: 30 credits and a B or better GPA • Category of courses • 6 credits from the list of foundation courses • 9 credits from the list of courses in financial mathematics • 9 credits from the list of courses in statistics • 6 credits as free electives* • A graduation GPA of B or above. • For other information, please visit Program webpage.

  8. A Complete List of Courses • Courses of the MSc Program • Courses of Mathematics of Fall Semester

  9. Courses for Fall 2009 • MAFS 501 Stochastic Calculus (B.Y. Jing) • MAFS 511 Advanced Data Analysis with Statistical Programming (M. So) • MAFS 524 Software Development with C++ for Quantitative Finance (C.D. Shum) • MAFS 601B Financial Derivatives and Martingale Pricing Theory (M.C. Chiu)

  10. Course of Spring 2010 • MAFS 513 Quantitative Analysis of Financial Time Series (SQ Ling) • MAFS 522 Quantitative and Statistical Risk Analysis (Y.F. Lam, G. Wu and L. Wu) • MAFS 601A Volatility Derivatives and Structured Products (Y.K. Kwok, B. Ho, J. Yen), or • MATH 572 Interest Rate Models (L. Wu) • MATH 685A Mathematical Models of Financial Economics (Y.K. Kwok) • MATH 685B Volatility Smile Modeling (L. Wu)

  11. Courses for the 1st Summer Session of 2010 • MAFS 523 Advanced Credit Risk Models (H. Zheng) • MAFS 525 Computational Methods for Pricing Structured Products (YK Kwok)

  12. Courses for the 2nd Summer Session of 2010 • MAFS 502 Advanced Probability and Statistics (MC Chiu)

  13. An Interdisciplinary Program • Three corner stones Probability Statistics Stoch. Analysis PDE Numer. Anal. C++, Java, VBA, Pearl, R, database management Economics Finance Financial markets Business Financial Economics Mathematics IT skills

  14. Job RelatedIssues

  15. Types of Institutions • Investment banks • Hedge funds • Asset management companies • Securities firms • Insurance companies • Commercial banks

  16. Targeted Professions • Derivatives traders • Quantitative programmers • Sales of financial instruments • Software developers • Quantitative analysts • Quant for trading desks • Quant for middle and back offices • Risk analysts/managers • Statistical analysts

  17. Where Our Students Work? • Citigroup, Merrill Lynch, Societie General, DBS, Nomura, Macquarie, Credit Lyonnais Security Asia, Athbest Financial Groups, Hang Seng Bank, CITIC KA Wah Bank, Clayons • Moody(中国),中银, 安信, 平保, 深国投, 渣打

  18. Job Information • The contacts between the program and the industry • Student Affair Office • Internet job sites • Jobs in Finance • Financial Analysis Jobs • Jobs Finance • 51job • chinahr 招聘网站! • www.zhaopin.com • www.chinabond.com.cn

  19. For Non-local Students • Mainland students can stay in Hong Kong for up to a year after graduation. • Internship for this one-year program is discouraged by both University and Immigration Department.

  20. About Internship • Yet students under student visa can still apply • Such internship is limited to a maximum of 20 hours/week, and the interns have to take course with at least 9 credits

  21. Questions? Thank you for your attentions!

  22. Course Description • MAFS 501 Stochastic Calculus 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.

  23. MAFS 511 Advanced Data Analysis with Statistical Programming Data analysis and implementation of statistical tools in a statistical program, like SAS, R, or Minitab.  Topics: reading and describing data, categorical data and longitudinal data, correlation and regression, nonparametric comparisons, ANOVA, multiple regression, multivariate data analysis.

  24. MAFS 524 Software Development with C++ for Quantitative Finance This course introduces C++ with applications in derivative pricing.  Contents include abstract data types; object creation, initialization, and toolkit for large-scale component programming; reusable components for path-dependent options under the Monte Carlo framework. Background: Prior programming experience

  25. MAFS 601B Financial Derivatives and Martingale Pricing Theory 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.

  26. MAFS 513 Quantitative Analysis of Financial Time Series 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. Background: Entry PG level MATH

  27. MAFS 521 Mathematical Models of Investment Utility theory, stochastic dominance.  Portfolio analysis: mean-variance approach, one-fund and two-fund theorems.  Capital asset pricing models.  Arbitrage pricing theory.  Consumption-investment problems.

  28. MAFS 522 Quantitative and Statistical Risk Analysis Various risk measures such as Value at Risk and Shortfall Risk.  Coherent risk measures.  Stress testing, model risk, spot and forward risk.  Portfolio risks.  Liabilities and reserves management.  Case studies of major financial losses.

  29. MATH 571 Mathematical Models of Financial Derivatives 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.

  30. MATH 572 Interest Rate Models Theory of interest rates, yield curves, short rates, forward rates. Short rate models: Vasicek model and Cox-Ingersoll-Ross models. Term structure models: Hull-White fitting procedure. Heath-Jarrow-Morton pricing framework. LIBOR and swap market models, Brace-Gatarek-Musiela approach. Affine models.

  31. MATH 600 Volatility Smile Modeling The mechanism of volatility smile/skew. Pros and cons of local volatility diffusion model. Dynamics of jump and stochastic volatility. Levy framework. Affine models. Models of stochastic volatility: Heston’s model and SABR model.

  32. Courses for the 1st Summer Session of 2010 • MAFS 523 Advanced Credit Risk Models (H. Zheng) • MAFS 525 Computational Methods for Pricing Structured Products (YK Kwok)

  33. Course Descriptions • MAFS 523 Advanced Credit Risk Models Credit spreads and bond price-based pricing.  Credit spread models.  Recovery modeling.  Intensity based models.  Credit rating models.  Firm value and share price-based models. Industrial codes: KMV and Credit Metrics.  Default correlation: copula functions.

  34. MAFS 525 Computational Methods for Pricing Structured Products Computational methods for pricing structured (equity, fixed-income and hybrid) financial derivatives products.  Lattice tree methods.  Finite difference schemes.  Forward shooting grid techniques.  Monte Carlo simulation.  Structured products analyzed include: Convertible securities; Equity-linked notes; Quanto currency swaps; Differential swaps; Credit derivatives products; Mortgage backed securities; Collateralized debt obligations; Volatility swaps. Background: Entry PG level MATH

  35. Courses for the 2nd Summer Session of 2010 • MAFS 502 Advanced Probability and Statistics (MC Chiu) 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. Background: Entry PG level MATH

More Related