Forecasting the Volatility of Nikkei 225 Futures
Manabu Asai and
Michael McAleer
Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute
Abstract:
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.
Keywords: Forecasting; Volatility; Futures; Realized Volatility; Realized Kernel; Leverage Effects; Long Memory (search for similar items in EconPapers)
JEL-codes: C22 C53 C58 G17 (search for similar items in EconPapers)
Pages: 28
Date: 2017-01-15
New Economics Papers: this item is included in nep-ets, nep-fmk, nep-for and nep-ore
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Citations: View citations in EconPapers (1)
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https://repub.eur.nl/pub/99517/EI2017-06.pdf (application/pdf)
Related works:
Journal Article: Forecasting the volatility of Nikkei 225 futures (2017) 
Working Paper: Forecasting the Volatility of Nikkei 225 Futures (2017) 
Working Paper: Forecasting the volatility of Nikkei 225 futures (2017) 
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:99517
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