Forecasting the volatility of Nikkei 225 futures

This article proposes an indirect method for forecasting the volatility of futures returns, based on the relationship between futures and the underlying asset for the returns and time‐varying volatility. The paper considers the stochastic volatility model with asymmetry and long memory, using high frequency data of the underlying asset, for forecasting its volatility. The empirical results for Nikkei 225 futures indicate that the adjusted R-super-2 supports the appropriateness of the indirect method, and that the new method based on stochastic volatility models with asymmetry and long memory outperforms the forecasting model based on the direct method using the pseudo long time series.