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An Empirical Analysis of the Shanghai and Shenzhen Limit Order Books

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  • Huimin Chung

    (National Chiao Tung University)

  • Cheng Gao

    (Rutgers University)

  • Jie Lu

    ()
    (Rutgers University)

  • Bruce Mizrach

    ()
    (Rutgers University)

Abstract

This paper investigates the market microstructure of the Shanghai and Shenzhen Stock Exchanges. The two major Chinese stock markets are pure order-driven trading mechanisms without market makers, and we analyze empirically both limit order books. We begin our empirical modeling using the vector autoregressive model of Hasbrouck and extend the model to incorporate other information in the limit order book. We also study the market impact on A shares, B shares and H shares, and analyze how the market impact of stocks varies cross sectionally with market capitalization, tick frequencies, and turnover. Furthermore, we find that market impact is increasing in trade size. Order imbalances predict the next day's returns, with small order imbalances having a negative effect.

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Bibliographic Info

Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201319.

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Length: 20 pages
Date of creation: 16 Jul 2013
Date of revision:
Handle: RePEc:rut:rutres:201319

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Keywords: limit order book; Chinese stock market; microstructure; VAR model;

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  1. Cai, Bill M. & Cai, Charlie X. & Keasey, Kevin, 2006. "Which trades move prices in emerging markets?: Evidence from China's stock market," Pacific-Basin Finance Journal, Elsevier, vol. 14(5), pages 453-466, November.
  2. Kalok Chan & Y. Peter Chung & Wai-Ming Fong, 2002. "The Informational Role of Stock and Option Volume," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1049-1075.
  3. Bailey, Warren & Cai, Jun & Cheung, Yan Leung & Wang, Fenghua, 2009. "Stock returns, order imbalances, and commonality: Evidence on individual, institutional, and proprietary investors in China," Journal of Banking & Finance, Elsevier, vol. 33(1), pages 9-19, January.
  4. Brad M. Barber & Yi-Tsung Lee & Yu-Jane Liu & Terrance Odean, 2009. "Just How Much Do Individual Investors Lose by Trading?," Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 609-632, February.
  5. Xu, Cheng Kenneth, 2000. "The microstructure of the Chinese stock market," China Economic Review, Elsevier, vol. 11(1), pages 79-97.
  6. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
  7. Alfonso Dufour & Robert F. Engle, 2000. "Time and the Price Impact of a Trade," Journal of Finance, American Finance Association, vol. 55(6), pages 2467-2498, December.
  8. Barclay, Michael J. & Warner, Jerold B., 1993. "Stealth trading and volatility : Which trades move prices?," Journal of Financial Economics, Elsevier, vol. 34(3), pages 281-305, December.
  9. 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.
  10. Soeren Hvidkjaer, 2008. "Small Trades and the Cross-Section of Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1123-1151, May.
  11. Ng, Lilian & Wu, Fei, 2007. "The trading behavior of institutions and individuals in Chinese equity markets," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2695-2710, September.
  12. Chunyang Zhou & Chongfeng Wu & Li Yang, 2011. "The Informational Role of Stock and Warrant Trades: Empirical Evidence from China," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 47(0), pages 78-93, January.
  13. Bruce Mizrach, 2008. "The next tick on Nasdaq," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 19-40.
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