Università Roma Tre

The multiple linear regression model. Panel data: fixed and random effects models.
Introduction to stochastic processes. Stationarity. The autocovariance function. The autocorrelation and partial autocorrelation functions. Autoregressive (AR), Moving Average (MA) and Autoregressive Moving Average (ARMA) models. Nonstationary processes: Random Walk and Autoregressive Integrated Moving Average (ARIMA) processes. Seasonal models. The Box and Jenkins procedure: preliminary analysis, model identification, parameter estimation, model validation. Forecasting using ARIMA models. Trend stationary and difference stationary process. Unit roots tests. Volatility. Conditional heteroschedastic models: ARCH and GARCH models. Asymmetric effects: TGARCH e EGARCH.

Carter Hill, R., Griffiths, W.E., e Lim, G.C., “Principles of econometrics”, 2012, Wiley.
Tsay, R.S., “An introduction to analysis of financial data with R“, 2013, Wiley.