COURSE CODE NO: 1190

COURSE NAME: Financial Econometrics

COURSE LEVEL: PhD Course

NUMBER OF CREDITS: 3

LECTURE TIME: 13:20 – 16:10, every Monday

CLASSROOM: 4207

APPROVED BY: School of Finance

SEMESTER FOR WHICH THE COURSE DESCRIPTION APPLIES: Fall 2011

FILLED IN BY: ZHU Jie

LECTURER: ZHU Jie

NUMBER OF HOURS PER WEEK: 3hours per week for 17 weeks, total of 51 hours

COMPLEMENTARY COURSES: Investments, Asset Pricing, Econometrics.

RESTRICTIONS ON ADMISSION: None

COURSE DESCRIPTION:

The course is concerned with the theory and practice of financial economics, which is a highly empirical discipline. The objective of the course is to provide methods to obtain inference for financial economics by introducing econometrical and statistical tools useful for conducting analysis on various topics in this field. The topics start with the measurement of returns (which is random in general), followed with market efficiency, event studies, equity valuation, fixed-income securities analysis, derivative pricing, financial risk management, and others. Since most financial data are in time series, the econometrical models dealing with time series analysis are also introduced in the course. The analysis considers basic AR, MA and ARMA models, extending to nonlinear models, high-frequency analysis and market microstructure, and others. Some advanced treatments in this field are also covered, which include the MCMC method and Kalman Filter analysis. Finally, several time slots are assigned on programming skills.

LEARNING OBJECTIVES:

After following the course, students should be able to

·         Explain different methods for predicting stock returns from their own history.

·         Know how the microstructure of stock markets affects the short-run behavior of returns.

·         Know how to derive CAPM and test its validity.

·         Know how to determine multiple factors affecting stock returns via the statistical and fundamental analysis approach.

·         Formulate and implement parametric option pricing models.

·         Pricing path-dependent derivatives via Monte Carlo simulation.

·         Know the term-structure models of interest rate and how to pricing fixed-income securities.

·         Know the AR, MA, and ARMA models in time series.

·         Apply GARCH and other nonlinearity models in finance.

·         Implement the econometrical analysis in computer software (SAS, OxMetrics, etc.)

TEACHING METHOD: Lectures and discussion of cases

FORM OF ASSESSMENT: Home work and final exam, TBA.

EXAMINATION AIDS ALLOWED: All

TEACHING LANGUAGE: Chinese and English

LITERATURE:

The Econometrics of Financial Markets, 1997, by John Y. Campbell, Andrew W. Lo, and A. Craig MacKinlay, Princeton University Press.

Analysis of Financial Time Series, 2005, by Ruey S. Tsay, John Wiley & Sons, Inc.