For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers the stochastic volatility model with asymmetry and long memory, using high frequency data for the underlying asset. 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 the asymmetry and long memory outperforms the forecasting model based on the direct method using the pseudo long time series.

Additional Metadata
Keywords Forecasting, Volatility, Futures, Realized Volatility, Realized Kernel, Leverage Effects, Long Memory
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
Series Tinbergen Institute Discussion Paper Series , Econometric Institute Research Papers
Asai, M, & McAleer, M.J. (2017). Forecasting the Volatility of Nikkei 225 Futures (No. EI2017-06). Econometric Institute Research Papers. Retrieved from