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The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market

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  • Luo, Xingguo
  • Qin, Shihua
  • Ye, Zinan

Abstract

This paper investigates the information content of the CBOE Gold ETF Volatility Index (GVZ) and jumps in forecasting realized volatility of the Shanghai gold futures market. We find strong in-sample evidence that the GVZ and jumps are significant and both greatly improve next day volatility forecasts. Also, these results are robust when the recent financial crisis is considered. Further, out-of-sample analysis confirms that the GVZ and jumps are important factors in forecasting future volatility. More important, we show that the GVZ outperforms jumps in terms of forecasting performance.

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  • Luo, Xingguo & Qin, Shihua & Ye, Zinan, 2016. "The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market," Finance Research Letters, Elsevier, vol. 19(C), pages 105-111.
    • Handle: RePEc:eee:finlet:v:19:y:2016:i:c:p:105-111
    DOI: 10.1016/j.frl.2016.06.012
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    Cited by:

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    5. Andor, György & Bohák, András, 2017. "Identifying events in financial time series – A new approach with bipower variation," Finance Research Letters, Elsevier, vol. 22(C), pages 42-48.
    6. Bouri, Elie & Roubaud, David & Jammazi, Rania & Assaf, Ata, 2017. "Uncovering frequency domain causality between gold and the stock markets of China and India: Evidence from implied volatility indices," Finance Research Letters, Elsevier, vol. 23(C), pages 23-30.
    7. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    8. Li, Xiaoqian & Ma, Xiaoqi, 2023. "Jumps and gold futures volatility prediction," Finance Research Letters, Elsevier, vol. 58(PC).
    9. Wei, Yu & Liang, Chao & Li, Yan & Zhang, Xunhui & Wei, Guiwu, 2020. "Can CBOE gold and silver implied volatility help to forecast gold futures volatility in China? Evidence based on HAR and Ridge regression models," Finance Research Letters, Elsevier, vol. 35(C).
    10. Wang, Xinya & Liu, Huifang & Huang, Shupei, 2019. "Identification of the daily seasonality in gold returns and volatilities: Evidence from Shanghai and London," Resources Policy, Elsevier, vol. 61(C), pages 522-531.
    11. Gong, Xu & Lin, Boqiang, 2018. "Structural changes and out-of-sample prediction of realized range-based variance in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 27-39.
    12. Marc Bohmann & Vinay Patel, 2020. "Information Leakage in Energy Derivatives around News Announcements," Published Paper Series 2020-2, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    13. Mensi, Walid & Lee, Yun-Jung & Vo, Xuan Vinh & Yoon, Seong-Min, 2021. "Quantile connectedness among gold, gold mining, silver, oil and energy sector uncertainty indexes," Resources Policy, Elsevier, vol. 74(C).
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    15. Jungmu Kim & Yuen Jung Park, 2020. "Predictability of OTC Option Volatility for Future Stock Volatility," Sustainability, MDPI, vol. 12(12), pages 1-23, June.
    16. Anupam Dutta & Elie Bouri & David Roubaud, 2021. "Modelling the volatility of crude oil returns: Jumps and volatility forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 889-897, January.
    17. Qureshi, Fiza & Kutan, Ali M. & Ismail, Izlin & Gee, Chan Sok, 2017. "Mutual funds and stock market volatility: An empirical analysis of Asian emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 176-192.
    18. Bai, Yujuan & Pan, Zhiyuan & Liu, Li, 2019. "Improving futures hedging performance using option information: Evidence from the S&P 500 index," Finance Research Letters, Elsevier, vol. 28(C), pages 112-117.

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    More about this item

    Keywords

    Gold futures; Realized volatility; Volatility forecasting; Volatility Index;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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