A comparative study of volatility forecasting models

2014

Masteroppgave i økonomi og administrasjon – Universitetet i Agder 2014 The purpose of this thesis is to investigate which of the selected models that forecasts the out-of-sample volatility most accurate and to see if the regression based models can outperform the historical volatility models. Using the data from the S&P500, NASDAQ Composite, DJIA, CBOE Interest Rate, LBMA Gold and USD/GBP return series. The data is forecasted under different distribution assumptions and then evaluated against each other. Trough this thesis, it can be con-cluded that the asymmetric GJR-GARCH under Student-t distribution most accurately describes the S&P500 and DJIA while GJR-GARCH under the normal distributi…