AMATH 546/ECON 589: Financial Econometrics and Quantitative Risk Management
TA: Xuyang Ma (maxuyang at uw dot edu)
This is a course in financial econometrics with an emphasis on the concepts, techniques and tools required for quantitative risk management. The focus will be on the statistical modeling of financial time series (asset prices and returns) with an emphasis on modeling volatility and correlation for quantitative risk management. The learning goals/objectives of the course are to (1) survey the relevant theoretical and practical literature; (2) introduce state-of-the-art techniques for modeling financial time series and managing financial risk; (3) use the open source R statistical software to get hands-on experience with real world data. Topics to be covered include:
Weekly homework assignments and computer lab work using R. Midterm and Final exam.
Grading distribution: Homework, labs weekly discussions (30%); Midterm (30%); Final exam (40%).
Graduate level econometrics or equivalent (econ 580-583). Familiarity with time series methods at the level of econ 584 or stat 519. Some familiarity with statistical programming using matrix languages (GAUSS, MATLAB, R, or S-PLUS).
McNeil, A., Frey, R., and Embrechts, P., Quantitative Risk Management: Concepts, Techniques, and Tools, Princeton University Press, 2005.
Jondeau, E., Poon, S.-H., and Rockinger, M. (2006). Financial Modeling Under Non-Gaussian Distributions, Springer-Verlag ebook. Available online from UW libraries.
Danielsson, J., Financial Risk Forecasting, Wiley Finance, 2011.
Ruppert, D. (2010). Statistics and Data Analysis for Financial Engineering, Springer-Verlag. Book website.
Tsay, R. (2010). Analysis of Financial Time Series, Third Edition. Wiley.
Supplemental reading from journal articles and non-required textbooks (available on course webpage)
The course will utilize R data analysis and statistical modeling.