HAR(d) to beat? Forecasting volatility: a comparison of the HAR model and actual volatility in the Netherlands

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2019-08-30
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en
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This thesis is testing the forecasting performance of the heterogeneous autoregressive model for realized volatility (HAR-RV), against the generalized autoregressive conditionally heteroskedastic model (GARCH (1, 1)), and the volatility derived from the volatility index in the Netherlands. Using data from the AEX index for the period 2000 to 2018, it has been found that the HAR-RV model was able to better forecast volatility for this period against GARCH (1, 1) and VAEX. The same results were produced when the models were tested in the two periods of crisis, namely 2000 to 2002 and 2007 to 2009. The daily out of sample forecasting performance of the models was based on a 252 days training period. The mean squared error (MSE) and the mean absolute error (MAE) methods have been used to estimate the forecasting performance of the models against the actual realized volatility. The indices of the S&P 500 and Nikkei 225 and their respective volatility indices have been tested for the same periods as a robustness check. The performance of the HAR-RV model was again superior against the GARCH (1, 1) model and the respective volatility indices for all the periods.
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Faculteit der Managementwetenschappen