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A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility

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  • Bentes, Sónia R.

Abstract

This paper examines the accuracy of implied volatility and GARCH forecasted volatility to predict the behavior of realized volatility. The methodology adopted addresses the information content, the bias, the efficiency and the efficiency forecast of the predictor.

Suggested Citation

  • Bentes, Sónia R., 2015. "A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 105-112.
    • Handle: RePEc:eee:phsmap:v:424:y:2015:i:c:p:105-112
    DOI: 10.1016/j.physa.2015.01.020
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    References listed on IDEAS

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    Cited by:

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    2. Lv, Wendai, 2018. "Does the OVX matter for volatility forecasting? Evidence from the crude oil market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 916-922.
    3. Futeri Jazeilya Md Fadzil & John G. O’Hara & Wing Lon Ng, 2017. "Cross-sectional volatility index as a proxy for the VIX in an Asian market," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1364011-136, January.
    4. Ufuk Beyaztas & Beste H. Beyaztas, 2019. "On Jackknife-After-Bootstrap Method for Dependent Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1613-1632, April.
    5. Slim, Skander & Dahmene, Meriam & Boughrara, Adel, 2020. "How informative are variance risk premium and implied volatility for Value-at-Risk prediction? International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 22-37.
    6. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    7. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    8. Lahmiri, Salim, 2017. "Modeling and predicting historical volatility in exchange rate markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 387-395.
    9. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    10. Zhuang, Chunjuan, 2018. "Improving performance of exchange rate momentum strategy using volatility information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 741-753.
    11. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    12. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.

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