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MASSIMO GUIDOLIN

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Teaching materials

- 20192 - FINANCIAL ECONOMETRICS AND EMPIRICAL FINANCE - MODULE 2
   A.Y. 2011/2012 - Classes: 14, 15, 16
   A.Y. 2012/2013 - Classes: 15, 16, 17
   A.Y. 2013/2014 - Classes: 15, 16, 17
   A.Y. 2014/2015 - Classes: 15, 16, 17
   A.Y. 2015/2016 - Classes: 15, 16, 17
   A.Y. 2016/2017 - Classes: 15, 16, 17
   A.Y. 2017/2018 - Classes: 15, 16, 17
   A.Y. 2018/2019 - Classes: 15, 16, 17

Detailed syllabus (with information concerning exams)

The Summer 2017 Statistics Prep Course remains here.

1. The Econometrics of Financial Returns: an Introduction [3 hours]
GUIDOLIN-PEDIO, chapter 1 and Appendix.
 
2. Essential Concepts in Time Series Analysis: Weak and Strong Stationarity; Sample Autocorrelations and Sample Partial Autocorrelations [5 hours]
*GUIDOLIN-PEDIO, chapter 2.1.
Cornell, B. (2018) "Taking Stationarity Seriously", Journal of Portfolio Management, 44, 1-4.
 
3. Autoregressive Moving Average (ARMA) Models and their Applications; Selection and Estimation of AR, MA and ARMA models; Forecasting ARMA processes [11 hours]
*GUIDOLIN-PEDIO, chapter 2.2-2-4.
Some additional slides about stationarity, memory and moving averages are here.
To play with ACFs and other properties of the ARMA models, click here.
 
4. Multivariate Time Series: Structural vs. Reduced-Form VARs; Estimation; Specification, Hypothesis Testing, and Forecasting; Structural Analysis with VAR Models [11 hours]
*GUIDOLIN-PEDIO, chapter 3.1-3.3.
An example of impulse response function with explicit calculations is here.
 
5. Unit Roots, Cointegration and Error Correction; Spurious Regression Problem [7 hours]
*Lecture Slides (part 1part 2).
*GUIDOLIN-PEDIO, chapter 4.
Campbell, J. Y. and R. Shiller (1987) "Cointegration and Present Value Models", Journal of Political Economy, 95, 1062-1088.
Bhargava, V., and D., Malhotra (2006) "Do Price-Earnings Ratios Drive Stock Values?", Journal of Portfolio Management, 33, 86-92.
One example of cointegration analysis on US real stock prices, dividends, and earnings is here.
 
6. Univariate Volatility Modeling: Introduction to ARCH and GARCH [6 hours]
*GUIDOLIN-PEDIO, chapter 5.1-5.2.
Engle, R. F. (2001) “GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics”, Journal of Economic Perspectives, 15, 157-168.
Schreder, M. (2018) "Volatility Forecasting in Practice: Exploratory Evidence from European Hedge Funds", Journal of Asset Management, 19, 245-258.
One example of estimation of RiskMetric's lmbda parameter is here.
 
7. Advanced Univariate Volatility Modeling: Non-Gaussian Marginal Innovations; Exogenous (Predetermined) Factors; Forecasting; Estimation and Inference [5 hours]
*GUIDOLIN-PEDIO, chapter 5.3-5.6.
Poon, S.-H., C. Granger (2005) “Practical Issues in Forecasting Volatility”, Financial Analysts Journal, Jan./Feb. issue, 61, 45-56.
One example of estimation of asymmetries in threshold GARCH in different asset classes is here.
Supplementary material on Netwon's method to maximize the log-likelihood function is here.
Supplementary material on GARCH option pricing is here.
 
 
Last update 02/05/2019