Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model

Isao Ishida and Toshiaki Watanabe
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Toshiaki Watanabe: Institute of Economic Research, Hitotsubashi University

No CIRJE-F-608, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: In this paper, we apply the ARFIMA-GARCH model to the realized volatility and the continuous sample path variations constructed from high-frequency Nikkei 225 data. While the homoskedastic ARFIMA model performs excellently in predicting the Nikkei 225 realized volatility time series and their square-root and log transformations, the residuals of the model suggest presence of strong conditional heteroskedasticity similar to the finding of Corsi et al. (2007) for the realized S&P 500 futures volatility. An ARFIMA model augmented by a GARCH(1,1) specification for the error term largely captures this and substantially improves the fit to the data. In a multi-day forecasting setting, we also find some evidence of predictable time variation in the volatility of the Nikkei 225 volatility captured by the ARFIMA-GARCH model.

Pages: 32pages
Date: 2009-01
New Economics Papers: this item is included in nep-for and nep-ore
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model (2009)
Working Paper: Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2009cf608

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