Time Series (2 º Sem 2019/2020)

- Introduction to time series analysis. Fundamental concepts
- Models for stationary time series. Autoregressive Moving Average (ARMA) models
- Box-Jenkins methodology: model identification, estimation and diagnostic checking
- Models for nonstationary time series. Autoregressive Integrated Moving Average (ARIMA) models and unit root testing
- Forecasting using ARIMA models
- Seasonality and Seasonal ARIMA (SARIMA) models
- Conditional Heteroskedasticity time series models. ARCH/GARCH models
- Forecasting with exponential smoothing methods
- Multivariate Time Series Models