The informational content of implied volatility: Application to the USD/JPY exchange rates

Qing Peng, Jie Li, Yu Zhao and Han Wu

Journal of Asian Economics, 2021, vol. 76, issue C

Abstract: This paper tests the information content of the Japanese Yen Implied Volatility Index (JYVIX) regarding the future volatility of USD/JPY exchange rates. We find that JYVIX contains significant information about future volatility, and it even has incremental predictive power over the traditional GARCH-Type models. Implicitly, JYVIX as a looking-forward index provides better forecasts on conditional volatility rather than realized volatility. Our analysis further shows that the forecastability of the GARCH-Type model combined with JYVIX is more credible than these individual models. Specifically, the EGARCH model combined with the exogenous variable JYVIX outperforms all prediction models. Our findings provide a better prediction approach to the volatility of USD/JPY exchange rates, which has far-reaching significance for risk management in Asian economies.

Keywords: Volatility forecast; JYVIX; GARCH-Type models (search for similar items in EconPapers)
JEL-codes: F31 F37 G15 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:asieco:v:76:y:2021:i:c:s1049007821000920

DOI: 10.1016/j.asieco.2021.101363

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