Forecasting the volatility of Nikkei 225 futures
提出一种间接方法，利用标的资产的高频数据，基于带非对称性和长记忆性的随机波动率模型，预测期货收益的波动率。实证表明该方法优于直接法。
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 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.