The competition between implied volatility and model-based volatility

Abstract

The current study presents a comprehensive research that aims to measure whether model-based forecasted volatility or implied volatility is the best method of determining future volatility. Forecasting horizons of one day, one week and one month will be used. The models that are investigated are the GARCH model, the HAR model and the VIX. The aim of this study is twofold. Firstly, to investigate which of the methods yields the best forecasting results in isolation. Second, to find out whether the different models provide any incremental information on volatility compared to the other models. The results of this study can be divided into two categories. One that compares the absolute performance of the models, and one that compares the relative performance of the models. The results on the absolute comparison between the models show that the HAR model offers the most accurate forecast for the daily and monthly forecast horizon. For the weekly forecasting period, the GARCH model is the best at predicting future volatility. Furthermore, the relative comparison between the models indicate that in almost all the cases, all models have independent information over each other. Only for the daily forecasting horizon, the GARCH model does not have independent information over the other models.