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Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

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  • Lee, Cheng F
  • Rui, Oliver M

Abstract

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables. Copyright 2000 by Kluwer Academic Publishers

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  • 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.
  • Handle: RePEc:kap:rqfnac:v:14:y:2000:i:4:p:341-60
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    Cited by:

    1. Chunyang Zhou & Chongfeng Wu & Li Yang, 2011. "The Informational Role of Stock and Warrant Trades: Empirical Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(0), pages 78-93, January.
    2. Fredj Jawadi & Waël Louhichi & Abdoulkarim Idi Cheffou & Rivo Randrianarivony, 2016. "Intraday jumps and trading volume: a nonlinear Tobit specification," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1167-1186, November.
    3. Cetin Ciner, 2003. "Dynamic Linkages Between Trading Volume and Price Movements: Evidence for Small Firm Stocks," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 8(1), pages 87-102, Spring.
    4. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    5. Jordan, Steven J. & Vivian, Andrew & Wohar, Mark E., 2014. "Sticky prices or economically-linked economies: The case of forecasting the Chinese stock market," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 95-109.
    6. Rodrigo Aranda & Patricio Jaramillo, 2008. "Nonlinear Dynamic in the Chilean Stock Market: Evidence from Returns and Trading Volume," Working Papers Central Bank of Chile 463, Central Bank of Chile.
    7. Shyh-Wei Chen, 2008. "Untangling the nexus of stock price and trading volume: evidence from the Chinese stock market," Economics Bulletin, AccessEcon, vol. 7(15), pages 1-16.
    8. repec:wsi:rpbfmp:v:20:y:2017:i:02:n:s021909151750014x is not listed on IDEAS
    9. Jawadi, Fredj & Louhichi, Waël & Idi Cheffou, Abdoulkarim, 2015. "Testing and modeling jump contagion across international stock markets: A nonparametric intraday approach," Journal of Financial Markets, Elsevier, vol. 26(C), pages 64-84.
    10. repec:eee:ecmode:v:69:y:2018:i:c:p:127-133 is not listed on IDEAS
    11. Christos Alexakis, 2011. "Financial Crisis, Ownership Effect and Investors Sentiment: Empirical Evidence from the Banking Sector in Greece," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 3-18.
    12. Chan, Kam C. & Fung, Hung-Gay & Thapa, Samanta, 2007. "China financial research: A review and synthesis," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 416-428.
    13. Wang, Dingyan & Chong, Terence Tai-Leung & Chan, Wing Hong, 2014. "Price Limits and Stock Market Volatility in China," MPRA Paper 54146, University Library of Munich, Germany.
    14. Xiangmei Fan & Yanrui Wu & Nicolaas Groenewold, 2003. "The Stock Return-volume Relation and Policy Effects: The Case of the Chinese Energy Sector," Economics Discussion / Working Papers 03-15, The University of Western Australia, Department of Economics.
    15. Goh, Jeremy C. & Jiang, Fuwei & Tu, Jun & Wang, Yuchen, 2013. "Can US economic variables predict the Chinese stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 22(C), pages 69-87.
    16. Chunyang Zhou & Chongfeng Wu & Li Yang, 2011. "The Informational Role of Stock and Warrant Trades: Empirical Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(0), pages 78-93, January.

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