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China’s Macroeconomic Fundamentals on Stock Market Volatility: Evidence from Shanghai and Hong Kong

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  • Andy Wui Wing Cheng

    (Department of Economics and Finance, Hang Seng Management College, Hong Kong)

  • Iris Wing Han Yip

    (Department of Mathematics and Statistics, Hang Seng Management College, Hong Kong)

Abstract

This paper examines the effect of Chinese macroeconomic variables, the industrial production growth rate, the producer price index, the 3-month short-term Shanghai Interbank Offer Rate and the consumer price index, on the volatility of the Shanghai and Hong Kong stock markets. We apply the generalized autoregressive conditional heteroskedastic mixed data sampling model for the study. Our empirical findings on various indexes and enterprises in the Shanghai and Hong Kong markets show that Chinese macroeconomic variables have a greater power to explain the volatility in Hong Kong than in Shanghai. They also contribute significantly to Hong Kong’s market volatility.

Suggested Citation

  • Andy Wui Wing Cheng & Iris Wing Han Yip, 2017. "China’s Macroeconomic Fundamentals on Stock Market Volatility: Evidence from Shanghai and Hong Kong," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(02), pages 1-57, June.
  • Handle: RePEc:wsi:rpbfmp:v:20:y:2017:i:02:n:s021909151750014x
    DOI: 10.1142/S021909151750014X
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    1. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    2. Girardin, Eric & Joyeux, Roselyne, 2013. "Macro fundamentals as a source of stock market volatility in China: A GARCH-MIDAS approach," Economic Modelling, Elsevier, vol. 34(C), pages 59-68.
    3. Francis X. Diebold & Kamil Yılmaz, 2007. "Macroeconomic Volatility and Stock Market Volatility,World-Wide," Koç University-TUSIAD Economic Research Forum Working Papers 0711, Koc University-TUSIAD Economic Research Forum.
    4. Cai, Charlie X. & McGuinness, Paul B. & Zhang, Qi, 2011. "The pricing dynamics of cross-listed securities: The case of Chinese A- and H-shares," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2123-2136, August.
    5. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    6. Jian Ke & Liming Wang & Louis Murray, 2010. "An empirical analysis of the volatility spillover effect between primary stock markets abroad and China," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 8(3), pages 315-333.
    7. Orawan Ratanapakorn & Subhash Sharma, 2007. "Dynamic analysis between the US stock returns and the macroeconomic variables," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 369-377.
    8. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    9. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    10. Beltratti, A. & Morana, C., 2006. "Breaks and persistency: macroeconomic causes of stock market volatility," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 151-177.
    11. Corradi, Valentina & Distaso, Walter & Mele, Antonio, 2013. "Macroeconomic determinants of stock volatility and volatility premiums," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 203-220.
    12. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    13. Siwei Cheng, 2009. "An Analysis of China's Stock Market in the First 10 Years," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 12(04), pages 629-653.
    14. Chiang, Thomas C & Doong, Shuh-Chyi, 2001. "Empirical Analysis of Stock Returns and Volatility: Evidence from Seven Asian Stock Markets Based on TAR-GARCH Model," Review of Quantitative Finance and Accounting, Springer, vol. 17(3), pages 301-318, November.
    15. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    16. Ravinder Kumar Arora & Himadri Das & Pramod Kumar Jain, 2009. "Stock Returns and Volatility: Evidence from Select Emerging Markets," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 12(04), pages 567-592.
    17. Lee, Cheng F & Rui, Oliver M, 2000. "Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets," Review of Quantitative Finance and Accounting, Springer, vol. 14(4), pages 341-360, June.
    18. Chiang, Thomas C & Chiang, Jeannette Jin, 1996. "Dynamic Analysis of Stock Return Volatility in an Integrated International Capital Market," Review of Quantitative Finance and Accounting, Springer, vol. 6(1), pages 5-17, January.
    19. Yeh, Yin-Hua & Lee, Tsun-siou & Pen, Jen-fu, 2002. "Stock Returns and Volatility under Market Segmentation: The Case of Chinese A and B Shares," Review of Quantitative Finance and Accounting, Springer, vol. 18(3), pages 239-257, May.
    20. Changjiang Lu & Kemin Wang & Haiwei Chen & James Chong, 2007. "Integrating A- and B-Share Markets in China: The Effects of Regulatory Policy Changes on Market Efficiency," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 10(03), pages 309-328.
    21. Qiao, Zhuo & Chiang, Thomas C. & Wong, Wing-Keung, 2008. "Long-run equilibrium, short-term adjustment, and spillover effects across Chinese segmented stock markets and the Hong Kong stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 425-437, December.
    22. Abugri, Benjamin A., 2008. "Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets," International Review of Financial Analysis, Elsevier, vol. 17(2), pages 396-410.
    23. Wang, Yuenan & Iorio, Amalia Di, 2007. "Are the China-related stock markets segmented with both world and regional stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 17(3), pages 277-290, July.
    24. Zhou, Xiangyi & Zhang, Weijin & Zhang, Jie, 2012. "Volatility spillovers between the Chinese and world equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 247-270.
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