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Chinese stock market volatility and the role of U.S. economic variables

Author

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  • Chen, Jian
  • Jiang, Fuwei
  • Li, Hongyi
  • Xu, Weidong

Abstract

This paper investigates the effects of U.S. economic variables on the time variation of Chinese stock market volatility. We find that U.S. economic variables such as the dividend price ratio, dividend yield and industrial production strongly forecast the future monthly volatilities of the Chinese stock market. The predictability is statistically and economically significant and can be further improved when combining the information in all U.S. economic variables together. Forecast encompassing tests and regression tests show that the forecasting power of U.S. economic variables is incremental when comparing with the Chinese domestic economic variables. Our findings are robust for the out-of-sample analysis and a number of Chinese industry portfolios volatilities.

Suggested Citation

  • Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
  • Handle: RePEc:eee:pacfin:v:39:y:2016:i:c:p:70-83
    DOI: 10.1016/j.pacfin.2016.05.013
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    10. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
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    13. Libing Fang & Baizhu Chen & Honghai Yu & Yichuo Qian, 2018. "The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 413-422, March.
    14. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
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    16. Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
    17. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
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    19. Cheng, Hang & Shi, Yongdong, 2020. "Forecasting China's stock market variance," Pacific-Basin Finance Journal, Elsevier, vol. 64(C).
    20. Dehua Shen & Yongjie Zhang & Xiong Xiong & Wei Zhang, 2017. "Baidu index and predictability of Chinese stock returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-8, December.
    21. Seyed Alireza Athari & Dervis Kirikkaleli & Tomiwa Sunday Adebayo, 2023. "World pandemic uncertainty and German stock market: evidence from Markov regime-switching and Fourier based approaches," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1923-1936, April.
    22. Mauck, Nathan & Pruitt, Stephen & Zhang, Wenjia, 2022. "Words matter: Market responses to changes in U.S. and Chinese trade-related internet search frequency under different U.S. administrations," Global Finance Journal, Elsevier, vol. 53(C).
    23. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.
    24. Shen, Lihua & Lu, Xinjie & Luu Duc Huynh, Toan & Liang, Chao, 2023. "Air quality index and the Chinese stock market volatility: Evidence from both market and sector indices," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 224-239.

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    More about this item

    Keywords

    Volatility forecasting; U.S. economic variables; Out-of-sample forecasting; Combination forecast; Chinese stock market;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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