Forecasting index volatility: sampling interval and non-trading effects

David Walsh and Glenn Yu-Gen Tsou

Applied Financial Economics, 1998, vol. 8, issue 5, 477-485

Abstract: A detailed comparison is made of volatility forecasting techniques on Australian value-weighted indices. The techniques compared are the naive approach (historical volatility), an improved extreme-value method (IEV), the ARCH/GARCH class of models and an exponentially weighted moving average (EWMA) of volatility. The study suggests that the EWMA technique appears to be the best volatility forecasting technique, closely followed by the appropriate GARCH specification. Both the IEV and historical volatility approaches are poor by comparison. The diversification benefit that arises from indices with larger numbers of stocks appears to make forecasting the volatility of larger indices more accurate. However, as the sampling interval is reduced, the non-trading effects evident in the larger indices start to counteract this benefit.

Date: 1998
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DOI: 10.1080/096031098332772

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