# 17-017/III (2017-01-30)

Manabu Asai, Soko University, Japan; Michael McAleer, National Tsing Hua University, Taiwan; Erasmus University Rotterdam, The Netherlands; Compultense University of Madrid, Spain
Forecasting; Volatility; Futures; Realized Volatility; Realized Kernel; Leverage Effects; Long Memory.
JEL codes:
C22, C53, C58, G17

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.