Statistical Models for Forecasting
State Space Models, Bayesian Belief Update, Bayesian Dynamic Models, ARIMA Models, GARCH Models, Autoregressive Vector Models (VAR), Impulse Response Functions, Unit Root Processes, Cointegration, Principal Component Analysis, Factor Models, Dynamic Conditional Correlation Models (DCC), Copulas
Basic Information
Workload
60 hours
Requirements
Statistical Modeling
Mandatory:
- Morettin, Pedro Alberto. Financial Econometrics: a course in financial time series. Edgard Blücher, 2008.
- Tsay, Ruey S. Multivariate Time Series Analysis: with R and financial applications. John Wiley & Sons, 2013.
- Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice. OTexts, 2014.
Complementary:
- Kuhn, Max, and Kjell Johnson. Applied predictive modeling. Vol. 810. New York: Springer, 2013.
- Brockwell, Peter J., and Richard A. Davis. Introduction to time series and forecasting. springer, 2016.
- Randal Douc, Eric Moulines, and David Stoffer. Nonlinear time series: theory, methods and applications with R examples. CRC Press, 2014.
- Hamilton, James Douglas. Time series analysis. Vol. 2. Princeton: Princeton university press, 1994.
- Harrison, Jeff, and Mike West. Bayesian forecasting and dynamic models. Springer, 1999.