Time Series Analysis with Applications to Finance

Professor: Alain Pirotte, Panthéon-Assas University.

Objective: This course focuses on the main econometric methods used in financial econometrics. Particular emphasis is first placed on all fundamental concepts of time series econometrics and more specifically on stationary and non-stationary random processes (identification, estimation, diagnostic tests, forecasting). Next, the course studies the univariate and multivariate non-linear modeling of the volatility of financial phenomena. Empirical applications are presented and concerned especially stock market and asset returns.

Outline:

• Assess risks - VAR (Value-at-Risk) ;
• Main characteristics of the financial series ;
• The particularities of econometric models and methods.

I - Stationary and non-stationary random processes

II - Volatility modelling - univariate models

III - Volatility modelling - multivariate models

Grading: Final exam at the end of the semester.

Bibliography:

• Brooks, C., 2014, Introductory Econometrics for Finance, third edition, Cambridge University Press, Cambridge ;
• Campbell, J.Y., A. Lo et A.C. MacKinlay, 1997, The Econometrics of Financial Markets, Princeton University Press, Princeton ;
• Franses, P.H. et D. van Djik, 2000, Non-Linear Time Series Models in Empirical Finance, Cambridge University Press, Cambridge ;
• Hamilton, J.D., 1994, Time Series Analysis, Princeton University Press, Princeton ;
• Jorion, P., 2007, Value-at-Risk, Third edition, McGraw-Hill, New York ;
• Wang, P., 2003, Financial Econometrics: Methods and Models, Routledge, London.