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Cross-market information transmission and stock market volatility prediction

Author

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  • Wang, Yide
  • Chen, Zan
  • Ji, Xiaodong

Abstract

The deep integration of global economic and financial activities accelerates the information transmission across financial markets. The cross-market information has become a crucial factor to influence the stock market fluctuation. This paper investigates the explanatory power and impacting mechanism of cross-market information flow in the prediction of Chinese stock market volatility. The empirical results show that the cross-market information flow exhibits significant linear and nonlinear influences on Chinese stock market volatility, and it also appears term-heterogeneous on the prediction accuracy, i.e., the cross-market information flow significantly contributes to medium-term and long-term prediction of Chinese stock market volatility, and the improvement of prediction accuracy is mainly due to nonlinear mechanism, whereas the cross-market information flow performs less value for short-term volatility prediction.

Suggested Citation

  • Wang, Yide & Chen, Zan & Ji, Xiaodong, 2023. "Cross-market information transmission and stock market volatility prediction," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823001006
    DOI: 10.1016/j.najef.2023.101977
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    References listed on IDEAS

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    1. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    2. Fama, Eugene F, et al, 1969. "The Adjustment of Stock Prices to New Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 1-21, February.
    3. Madhavan, Ananth, 2000. "Market microstructure: A survey," Journal of Financial Markets, Elsevier, vol. 3(3), pages 205-258, August.
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    Cited by:

    1. Li, Zhe & Shen, Jiashuang & Xiao, Weilin, 2024. "Volatility risk premium, good volatility and bad volatility: Evidence from SSE 50 ETF options," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).

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    More about this item

    Keywords

    Cross-market information flow; Realized volatility; Transfer entropy; Machine learning; Linear and nonlinear Granger causality test;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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