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Bid-Ask Spread Components in an Order-Driven Environment

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  • Brockman, Paul
  • Chung, Dennis Y
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    Abstract

    The purpose of this study is to extend the bid-ask spread decomposition literature into the order-driven environment. The use of electronic limit order books combined with order-driven market making has been increasing rapidly in recent years because improvements in information technology and financial market deregulation. To date, reported bid-ask spread decompositions rely almost exclusively on quote-driven or hybrid systems. This study provides bid-ask spread component estimates from one of the world's largest order-driven markets, the Stock Exchange of Hong Kong. Based on a sample of over six million observations, we estimate a median adverse selection component of 33 percent and a median order processing component of 45 percent of the spread. Dollar volume-based decile portfolios show significant cross-sectional variation for adverse selection costs but insignificant variation for order processing costs. Finally, order persistence is consistently positive for all deciles and displays a direct relation with the level of trading activity.

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    Bibliographic Info

    Article provided by Southern Finance Association & Southwestern Finance Association in its journal Journal of Financial Research.

    Volume (Year): 22 (1999)
    Issue (Month): 2 (Summer)
    Pages: 227-46

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    Handle: RePEc:bla:jfnres:v:22:y:1999:i:2:p:227-46

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    Web page: http://www.southwesternfinance.org/
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    Cited by:
    1. Levin, Eric J. & Wright, Robert E., 2004. "Estimating the profit markup component of the bid-ask spread: evidence from the London Stock Exchange," The Quarterly Review of Economics and Finance, Elsevier, Elsevier, vol. 44(1), pages 1-19, February.
    2. Lijian Wei & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2013. "Learning and Information Dissemination in Limit Order Markets," Research Paper Series, Quantitative Finance Research Centre, University of Technology, Sydney 333, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Chen, Langnan & Luo, Jiawen & Liu, Hao, 2013. "The determinants of liquidity with G-RJMCMC-VS model: Evidence from China," Economic Modelling, Elsevier, Elsevier, vol. 35(C), pages 192-198.
    4. Weiyu Kuo & Yu‐Ching Li, 2011. "Trading Mechanisms and Market Quality: Call Markets versus Continuous Auction Markets," International Review of Finance, International Review of Finance Ltd., International Review of Finance Ltd., vol. 11(4), pages 417-444, December.
    5. He, William Peng & Lepone, Andrew & Leung, Henry, 2013. "Information asymmetry and the cost of equity capital," International Review of Economics & Finance, Elsevier, Elsevier, vol. 27(C), pages 611-620.
    6. Lecce, Steven & Lepone, Andrew & McKenzie, Michael D. & Segara, Reuben, 2012. "The impact of naked short selling on the securities lending and equity market," Journal of Financial Markets, Elsevier, Elsevier, vol. 15(1), pages 81-107.
    7. Charoenwong, Charlie & Ding, David K. & Siraprapasiri, Vasan, 2011. "Adverse selection and corporate governance," International Review of Economics & Finance, Elsevier, Elsevier, vol. 20(3), pages 406-420, June.
    8. Angelo Ranaldo, 2002. "Market Dynamics Around Public Information Arrivals," FAME Research Paper Series, International Center for Financial Asset Management and Engineering rp45, International Center for Financial Asset Management and Engineering.

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