AMATH 546/ECON 589:  Financial Econometrics and Quantitative Risk Management

R Hints

Course Description

Eric Zivot
348 Savery Hall
email: ezivot at u dot washington dot edu
Office Hours: Monday 1-2

TA: Xuyang Ma (maxuyang at uw dot edu)

Spring 2013

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:


  • Overview of risk concepts

  • Risk measures

  • Empirical properties and stylized facts of asset returns

  • Probability distributions and statistical models for asset returns

  • Volatility and correlation modeling

  • Estimation of risk measures

  • Factor risk models for asset returns

  • Systemic risk 


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).

Required Textbooks

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.

Optional Textbooks

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.