Forecasting Volatility - A Comparison Study of Model Based Forecasts and Implied Volatility

Sammanfattning: Purpose: The purpose is to investigate which of the selected models that forecasts the out-of-sample data most accurate and whether the model based estimators make better forecasts than the implied volatility. Methodology: Trough in-sample data from a Swedish stock index return series and a exchange rate return series, different forecasting models are evaluated to see which one that predicts the out-of-sample realized volatility most accurate. The data is forecasted under different distribution assumptions and then evaluated against each other and the implied volatility. Results: Trough this thesis, it can be concluded that the asymmetric EGARCH under general error distribution and under normal distribution most accurately describes the stock index return series and the exchange rate return series respectively. It can also be concluded that the implied volatility does not predict the volatility more accurate than the model based forecasts.