Template-type: ReDIF-Paper 1.0
Author-Name: Manabu Asai
Author-Workplace-Name: Faculty of Economics Soka University, Japan.
Author-Name:
 Michael McAleer
Author-Workplace-Name: Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of 
	Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of 
	Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.
Title: Forecasting the volatility of Nikkei 225 futures
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.
Classification-JEL: C22, C53, C58, G17.
Keywords: Forecasting, Volatility, Futures, Realized volatility, Realized kernel, Leverage effects, Long memory.
Length: 27 pages 
Creation-Date: 2017-01
Number: 2017-07
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1707.txt
File-URL: https://eprints.ucm.es/id/eprint/40908/1/1707.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1707