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Stock Market Volatility and Trading Volume: A Special Case in Hong Kong With Stock Connect Turnover

Author

Listed:
  • Brian Sing Fan Chan

    (CASH Algo Finance Group Limited, Hong Kong, China)

  • Andy Cheuk Hin Cheng

    (CASH Algo Finance Group Limited, Hong Kong, China)

  • Alfred Ka Chun Ma

    (CASH Algo Finance Group Limited, Hong Kong, China)

Abstract

The cross-boundary Shanghai-Hong Kong and Shenzhen-Hong Kong Stock Connect provides a special data set to study the dynamic relationships among volatility, trading volume and turnover among three stock markets, namely Shanghai, Shenzhen, and Hong Kong. We employ the Granger Causality test with the vector autoregressive model (VAR) to examine whether Stock Connect turnover contributes to future realized volatility and market volume of these three markets. Our results support the evidence of causality from Stock Connect turnover to market volatility and trading volume. The finding of this causality is consistent with the implication of the sequential information arrival model in the literature.

Suggested Citation

  • Brian Sing Fan Chan & Andy Cheuk Hin Cheng & Alfred Ka Chun Ma, 2018. "Stock Market Volatility and Trading Volume: A Special Case in Hong Kong With Stock Connect Turnover," JRFM, MDPI, vol. 11(4), pages 1-17, October.
    • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:4:p:76-:d:179490
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    References listed on IDEAS

    as
    1. Wang, Qiyu & Chong, Terence Tai-Leung, 2018. "Co-integrated or not? After the Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connection Schemes," Economics Letters, Elsevier, vol. 163(C), pages 167-171.
    2. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    3. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    4. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    5. Burdekin, Richard C.K. & Siklos, Pierre L., 2018. "Quantifying the impact of the November 2014 Shanghai-Hong Kong Stock Connect," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 156-163.
    6. Lee, Bong-Soo & Rui, Oliver M., 2002. "The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence," Journal of Banking & Finance, Elsevier, vol. 26(1), pages 51-78, January.
    7. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    8. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    9. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    10. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    11. Yang-Chao Wang & Jui-Jung Tsai & Qiaoqiao Li, 2017. "Policy Impact on the Chinese Stock Market: From the 1994 Bailout Policies to the 2015 Shanghai-Hong Kong Stock Connect," IJFS, MDPI, vol. 5(1), pages 1-19, January.
    12. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    13. Thomas C. Chiang & Zhuo Qiao & Wing-Keung Wong, 2010. "New evidence on the relation between return volatility and trading volume," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(5), pages 502-515.
    14. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," The Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
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