Prof. Giuseppe Cavaliere

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Argomenti del programma: 1. Introduction to the course. Conditional expectations and their features 2. Multiple linear regression analysis: Ordinary Least Squares (OLS) estimator 3. Finite Sample properties of OLS estimator 4. Finite Sample inference 5. OLS asymptotics and large sample inference 6. Specification tests and model selection 7. Incorporating non-linearities in multiple linear regression models

Argomenti del programma: Part I: Stylized facts of financial time series and conditional volatility models: estimation, inference and applications Stylized facts of financial data and time series Univariate GARCH processes: properties, estimation, diagnostics and inference. Applications to Value at Risk. Extension to multivariate models of conditional variance.

Argomenti del programma: Introduction to multivariate time series . Stationarity, ergodicity. Moments. Linear processes. Martingales. Law of Large Numbers and Central Limit Theorems. Vector Autoregressive (VAR) models for stationary data . Specification and assumptions. Alternative representations of the model. Estimation (OLS, GLS, SUR, MM, ML) and inference. Stationarity conditions. Moving average (MA) representation.