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Do order imbalances predict Chinese stock returns? New evidence from intraday data

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  • Narayan, Paresh Kumar
  • Narayan, Seema
  • Westerlund, Joakim

Abstract

In this paper we examine whether order imbalances can predict the Chinese stock market returns. We use intraday data, a panel data predictive regression model that accounts for persistent and endogenous order imbalances and cross-sectional dependence in returns, and show that order imbalances predict stock returns from 1-minute trading to 90-minute trading. On the basis of this predictability evidence using multiple trading strategies we show that profits persist during the day. These results imply that a source of Chinese market inefficiency is order imbalances.

Suggested Citation

  • Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
  • Handle: RePEc:eee:pacfin:v:34:y:2015:i:c:p:136-151
    DOI: 10.1016/j.pacfin.2015.07.003
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    as
    1. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Narayan, Paresh Kumar & Ahmed, Huson Ali & Sharma, Susan Sunila & K.P., Prabheesh, 2014. "How profitable is the Indian stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 44-61.
    4. Kalok Chan & Albert J. Menkveld & Zhishu Yang, 2008. "Information Asymmetry and Asset Prices: Evidence from the China Foreign Share Discount," Journal of Finance, American Finance Association, vol. 63(1), pages 159-196, February.
    5. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    6. Elliott, Graham & Stock, James H., 1994. "Inference in Time Series Regression When the Order of Integration of a Regressor is Unknown," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 672-700, August.
    7. Marquering, Wessel & Verbeek, Marno, 2004. "The Economic Value of Predicting Stock Index Returns and Volatility," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 407-429, June.
    8. Shenoy, Catherine & Zhang, Ying Jenny, 2007. "Order imbalance and stock returns: Evidence from China," The Quarterly Review of Economics and Finance, Elsevier, vol. 47(5), pages 637-650, December.
    9. Driesprong, Gerben & Jacobsen, Ben & Maat, Benjamin, 2008. "Striking oil: Another puzzle?," Journal of Financial Economics, Elsevier, vol. 89(2), pages 307-327, August.
    10. Eun, Cheol S. & Huang, Wei, 2007. "Asset pricing in China's domestic stock markets: Is there a logic?," Pacific-Basin Finance Journal, Elsevier, vol. 15(5), pages 452-480, November.
    11. Chan, Kalok & Menkveld, Albert J. & Yang, Zhishu, 2006. "Information Asymmetry and Asset Prices: Evidence from the China Foreign share discount," Serie Research Memoranda 0005, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    12. Narayan, Paresh Kumar & Sharma, Susan Sunila & Thuraisamy, Kannan Sivananthan, 2014. "An analysis of price discovery from panel data models of CDS and equity returns," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 167-177.
    13. Gordon, Roger H. & Li, Wei, 2003. "Government as a discriminating monopolist in the financial market: the case of China," Journal of Public Economics, Elsevier, vol. 87(2), pages 283-312, February.
    14. Wang, Changyun & Chin, Shengtyng, 2004. "Profitability of return and volume-based investment strategies in China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 541-564, November.
    15. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    16. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    17. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    18. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, March.
    19. Ferson, Wayne E. & Harvey, Campbell R., 1994. "Sources of risk and expected returns in global equity markets," Journal of Banking & Finance, Elsevier, vol. 18(4), pages 775-803, September.
    20. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    21. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    22. Yun Wang, Chang & Sang Cheng, Nam, 2004. "Extreme volumes and expected stock returns: Evidence from China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 577-597, November.
    23. Narayan, Paresh Kumar & Narayan, Seema & K.P, Prabheesh, 2014. "Stock returns, mutual fund flows and spillover shocks," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 146-162.
    24. Larsson, Rolf & Lyhagen, Johan, 2007. "Inference in Panel Cointegration Models With Long Panels," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 473-483, October.
    25. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    26. Chen, Xuanjuan & Kim, Kenneth A. & Yao, Tong & Yu, Tong, 2010. "On the predictability of Chinese stock returns," Pacific-Basin Finance Journal, Elsevier, vol. 18(4), pages 403-425, September.
    27. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2014. "Firm return volatility and economic gains: The role of oil prices," Economic Modelling, Elsevier, vol. 38(C), pages 142-151.
    28. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    29. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    30. Seasholes, Mark S. & Liu, Clark, 2011. "Trading imbalances and the law of one price," Economics Letters, Elsevier, vol. 112(1), pages 132-134, July.
    31. Narayan, Paresh Kumar & Narayan, Seema & Thuraisamy, Kannan Sivananthan, 2014. "Can institutions and macroeconomic factors predict stock returns in emerging markets?," Emerging Markets Review, Elsevier, vol. 19(C), pages 77-95.
    32. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    33. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    34. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2015. "Does data frequency matter for the impact of forward premium on spot exchange rate?," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 45-53.
    35. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2002. "Order imbalance, liquidity, and market returns," Journal of Financial Economics, Elsevier, vol. 65(1), pages 111-130, July.
    36. Lee, Yi-Tsung & Liu, Yu-Jane & Roll, Richard & Subrahmanyam, Avanidhar, 2004. "Order Imbalances and Market Efficiency: Evidence from the Taiwan Stock Exchange," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(02), pages 327-341, June.
    37. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2015. "Is carbon emissions trading profitable?," Economic Modelling, Elsevier, vol. 47(C), pages 84-92.
    38. Tan, Lin & Chiang, Thomas C. & Mason, Joseph R. & Nelling, Edward, 2008. "Herding behavior in Chinese stock markets: An examination of A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 61-77, January.
    39. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.
    40. Lee, Charles M C & Ready, Mark J, 1991. " Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    41. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2011. "New evidence on oil price and firm returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3253-3262.
    42. Burns, Kelly & Moosa, Imad A., 2015. "Enhancing the forecasting power of exchange rate models by introducing nonlinearity: Does it work?," Economic Modelling, Elsevier, vol. 50(C), pages 27-39.
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    Cited by:

    1. Narayan, Paresh Kumar & Liu, Ruipeng & Westerlund, Joakim, 2016. "A GARCH model for testing market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 121-138.
    2. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    3. Laopodis, Nikiforos T., 2016. "Industry returns, market returns and economic fundamentals: Evidence for the United States," Economic Modelling, Elsevier, vol. 53(C), pages 89-106.
    4. repec:eee:ecmode:v:64:y:2017:i:c:p:221-230 is not listed on IDEAS
    5. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    6. Narayan, Paresh Kumar & Sharma, Susan Sunila, 2016. "Intraday return predictability, portfolio maximisation, and hedging," Emerging Markets Review, Elsevier, vol. 28(C), pages 105-116.
    7. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    8. repec:eee:intfin:v:52:y:2018:i:c:p:152-172 is not listed on IDEAS
    9. repec:eee:intfin:v:48:y:2017:i:c:p:160-177 is not listed on IDEAS
    10. Kuo, Chen-Yin, 2016. "Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory," Economic Modelling, Elsevier, vol. 52(PB), pages 772-789.
    11. Linnenluecke, Martina K. & Chen, Xiaoyan & Ling, Xin & Smith, Tom & Zhu, Yushu, 2016. "Emerging trends in Asia-Pacific finance research: A review of recent influential publications and a research agenda," Pacific-Basin Finance Journal, Elsevier, vol. 36(C), pages 66-76.

    More about this item

    Keywords

    Order imbalance; Stock returns; Predictability; Intraday; Panel data; Trading strategies;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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