Portale di Ateneo - En.Unibs.it

Part I: Statistical inference and multiple regression models (Textbook: Stock & Watson, Introduction to Econometrics, Pearson 2012)
1.1 Definition of estimators and hypotheses testing, type I and II errors, pvalue and confidence levels
1.2 Simple and multiple regressione models, ordinary least square estimator, unbiasedness, consistency, and asymptotic distribution
1.3 Estimation of OLS estimators variance matrix in presence of heteroskedasticity
1.4 t and F statistics to test linear constraints on the parameters of the model
Part II: Multiple regression models for time series(Textbook Stock and Watson, Introduction to Econometrics, Pearson 2012)
2.1 Distributed lag models (DL), Autoregressive distributed lag models (ADL), introduction to VAR and cointegration
2.2 Trend and stationarity, unit root and structural breaks tests
2.3 Impact and dynamic multipliers
2.4 Variance matrix in presence of heteroskedasticity and autocorrelation of error terms
2.5 GLS estimation of models with autocorrelated errors (Cochrane – Orcutt)
Part III: Topics of financial markets econometrics (Textbook: MacKinlay, Lo and Campbell, The Econometrics of Financial Markets, Princeton University Press, 1997)
3.1 Tests for portfolio Mean-Variance efficiency
3.2 CAPM empirical analysis, cross sectional and time series approaches
3.3 APT empirical analysis, cross sectional and time series approaches
3.4 Event study
3.5 Performance analysis