Introduction to Modern Time Series Analysis

This book contains the most important approaches to analyze time series which may be stationary or nonstationary. It starts with modeling and forecasting univariate time series and then presents Granger causality tests and vector autoregressive models for multiple stationary time series. It also covers modeling volatilities of financial time series with autoregressive conditional heteroskedastic models.

Contenu
and Basics.- Univariate Stationary Processes.- Granger Causality.- Vector Autoregressive Processes.- Nonstationary Processes.- Cointegration.- Autoregressive Conditional Heteroskedasticity.