Volatility Forecasting : The Illusion of Choosing One Model in All Cases

The volatility prediction is the most important issue in finance, as it is the key ingredient variable in forecasting the prices of options, the VaR number and, in general, the risk that investors face. By estimating not only inter-day volatility models that capture the main characteristics of asset returns, such as the non-zero skewness, the excess kurtosis relative to that of the normal distribution and the fractional integration of the conditional variance, but also an intra-day model, we investigate their forecasting performance for three European equity indices. We find out that there is no consistent relation between the examined models and the specific purpose of volatility forecasts. Researchers cannot apply, not even for the same equity index, one model for all the forecasting purposes. However, if they want to choose one model, they must prefer an inter-day specification that accounts at least for volatility clustering and the leverage effect