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 R2 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.

Additional Metadata
JEL Time-Series Models; Dynamic Quantile Regressions (jel C22), Forecasting and Other Model Applications (jel C53), Financial Econometrics (jel C58), Financial Forecasting (jel G17)
Persistent URL,
Journal The Journal of Futures Markets
Asai, M, & McAleer, M.J. (2017). Forecasting the volatility of Nikkei 225 futures. The Journal of Futures Markets. doi:10.1002/fut.21847