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金融计量——2012年春季学期双学位课程介绍

发布日期：2012-02-14 01:01    来源：北京大学国家发展研究院

Financial Econometrics : Time Series Models        Spring 2012

CCER, Peking University

Course Requirements:

A midterm (30%), three homework (30%) and a term paper (40%).

Useful textbook- Brook, Chris (2008): Introductory Econometrics for Finance. Cambridge University Press.

Software knowledge: STATA

 

Course Outline

PART 0 Review:

Principle of Maximum likelihood.

1.       Likelihood function

2.       Large sample theory of MLE

3.       Some examples.

 

PART I: Modeling the Mean Equation

A.     Basic time series models-ARIMA

1.       White noise and Autocorrelations

2.       AR(p), MA(q) and ARMA(p,q).

3.       Integrated Time series and Unit root tests

B.  Time Series Regression

1 Conditional mean and OLS

2 OLS, t and F statistics

3 Diagnostics: Serial correlation and DW statsitcs

4 Spurious Regression

5 Parameter shift

6 Useful linear model: ADL regression

References:

§Poterba, J. and L. Summers (1988): “Mean Reversion in Stock Prices: Evidence and Implications,” Journal of Financial Economics 22, 27-50.
§Hasbrouck, J. and T. Ho (1987): “Order Arrival, Quote Behavior and the Return-Generating Process,” The Journal of Finance 42, 1035-1048.

§Balvers,R., T. Cosimano and B. McDonald (1990): “Predicting Stock Returns in an Efficient Market”, Journal of Finance XLV, 1109-1127.

§Fama, E and K. French (1989): “Business Conditions and Expected Returns on Stock and Bonds”, Journal of Financial Economics 25, 23-49.

§Breen,W., L.Glosten and R. Jagannathan(1989): “Economic Significance of Predictable Variations in Stock Index Returns,” Journal of Finance XLIV, 1177-1189.

 

PART II  Volatility-GARCH Models

1 Autoregressive Conditional Heteroskedasticity/ARCH

2 Generalized ARCH/GARCH

3 Integrated GARCH and Break

4 Extensions: Asymmetric GARCH, EGARCH

References:

§Akgiray,V. (1989): “Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts,” The Journal of Business 62, 55-80.

§Berkowitz, J. and J. O'Brien(2002): “ How Accurate Are Value-at-Risk Models at Commercial Banks?” The Journal of Finance 57, 1093-1111.

§Whitelaw, R.(1994): “Time Variations and Covariations in the Expectation and Volatility of Stock Market Returns,” Journal of Finance XLIX, 515-541.

§Christopher G. Lamoureux and William D. Lastrapes (1990): “Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects,” Journal of Finance 45, 221-229.

 

PART III Event Studies

A Models for Measuring Normal Performance

1 Constant-Mean-Return Model

2 Market Model

B Measuring and Analyzing Abnormal Returns

1 Statistical Properties of Abnormal Returns

2 Aggregation of Abnormal Returns

3 CAR test

 

PART IV Multivariate Models

A  Multivariate Regression: Seemingly Unrelated Regression /SUR

1 Reduced form

2 SUR Estimation/SURE

B  Multivariate Time Series: Vector Autoregression

1 Stationarity condition

2 Estimation

3 Causality

4 Cointegration and ECM.

References:

Sundaram Janakiramanan, Asjeet S. Lamba(1998): “An empirical examination of linkages between Pacific-Basin stock markets,” Journal of International Financial Markets,

Institutions and Money 8, 155–173.

Gong-meng Chen, Michael Firth and Oliver Meng Rui (2002): “Stock market linkages: Evidence from Latin America,” Journal of Banking & Finance 26, 1113–1141.


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