This study examines the Chinese implied volatility index (iVIX) to determine whether jump information from the index is useful for volatility forecasting of the Shanghai Stock Exchange 50ETF. Specifically, we consider the jump sizes and intensities of the 50ETF and iVIX as well as cojumps. The findings show that both the jump size and intensity of the 50ETF can improve the forecasting accuracy of the 50ETF volatility. Moreover, we find that the jump size and intensity of the iVIX provide no significant predictive ability in any forecasting horizon. The cojump intensity of the 50ETF and iVIX is a powerful predictor for volatility forecasting of the 50ETF in all forecasting horizons, and the cojump size is helpful for forecasting in short forecasting horizon. In addition, for a one-day forecasting horizon, the iVIX jump size in the cojump is more predictive of future volatility than that of the 50ETF when simultaneous jumps occur. Our empirical results are robust and consistent. This work provides new insights into predicting asset volatility with greater accuracy.
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Univ Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R ChinaUniv Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R China
Chen, Tian
Deng, Jun
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Univ Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R ChinaUniv Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R China
Deng, Jun
Nie, Jing
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Univ Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R ChinaUniv Int Business & Econ, China Sch Banking & Finance, Beijing, Peoples R China
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Cardiff Business Sch, Investment Management Res Unit, Cardiff CF10 3EU, S Glam, WalesCardiff Business Sch, Investment Management Res Unit, Cardiff CF10 3EU, S Glam, Wales
Wong, Woon K.
Tu, Anthony H.
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Natl Chengchi Univ, Taipei, TaiwanCardiff Business Sch, Investment Management Res Unit, Cardiff CF10 3EU, S Glam, Wales
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International Graduate School of Business, University of South Australia, AdelaideInternational Graduate School of Business, University of South Australia, Adelaide
Li S.
Yang Q.
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School of Economics and Finance, Queensland University of Technology, BrisbaneInternational Graduate School of Business, University of South Australia, Adelaide
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Northwestern Univ, Kellogg Sch Management, Dept Finance, Evanston, IL 60208 USA
NBER, Cambridge, MA 02138 USA
CREATES, Aarhus, DenmarkNorthwestern Univ, Kellogg Sch Management, Dept Finance, Evanston, IL 60208 USA
Andersen, Torben G.
Bollerslev, Tim
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NBER, Cambridge, MA 02138 USA
CREATES, Aarhus, Denmark
Duke Univ, Dept Econ, Durham, NC 27708 USANorthwestern Univ, Kellogg Sch Management, Dept Finance, Evanston, IL 60208 USA
Bollerslev, Tim
Meddahi, Nour
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Toulouse Sch Econ GREMAQ IDEI, F-31000 Toulouse, FranceNorthwestern Univ, Kellogg Sch Management, Dept Finance, Evanston, IL 60208 USA