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Search costs and investor trading activity: evidences from limit order book

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  • Lin, William
  • Tsai, Shih-Chuan
  • Sun, David

Abstract

We analyze in this study investor trading behavior based not on information related assumptions but on the search model of Vayanos and Wang (2007). Our study shows that search cost dictates trading polarization across investors, firm size and time of day. We find that individual investors prefer to trade at market open, while institutional investors trade more heavily near market close. Trading costs indicate that it is less costly for institutional investors to trade large cap stocks at market close than at open. Search cost is related significantly to order-based market liquidity measures depending on time of day, market capitalizations and investor type.

Suggested Citation

  • Lin, William & Tsai, Shih-Chuan & Sun, David, 2010. "Search costs and investor trading activity: evidences from limit order book," MPRA Paper 37284, University Library of Munich, Germany, revised Aug 2011.
  • Handle: RePEc:pra:mprapa:37284
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    References listed on IDEAS

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    1. Dimitri Vayanos & Pierre‐Olivier Weill, 2008. "A Search‐Based Theory of the On‐the‐Run Phenomenon," Journal of Finance, American Finance Association, vol. 63(3), pages 1361-1398, June.
    2. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2005. "Limit Order Book as a Market for Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1171-1217.
    3. Daniel Dorn & Gur Huberman & Paul Sengmueller, 2008. "Correlated Trading and Returns," Journal of Finance, American Finance Association, vol. 63(2), pages 885-920, April.
    4. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    5. Lokman Gündüz & Abdulnasser Hatemi-J, 2005. "Stock Price and Volume Relation in Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 41(1), pages 29-44, January.
    6. Vayanos, Dimitri & Wang, Tan, 2007. "Search and endogenous concentration of liquidity in asset markets," Journal of Economic Theory, Elsevier, vol. 136(1), pages 66-104, September.
    7. Chan, Kalok & Menkveld, Albert J. & Yang, Zhishu, 2007. "The informativeness of domestic and foreign investors' stock trades: Evidence from the perfectly segmented Chinese market," Journal of Financial Markets, Elsevier, vol. 10(4), pages 391-415, November.
    8. Kerry Back & C. Henry Cao & Gregory A. Willard, 2000. "Imperfect Competition among Informed Traders," Journal of Finance, American Finance Association, vol. 55(5), pages 2117-2155, October.
    9. Hu, Shing-yang, 2006. "A simple estimate of noise and its determinant in a call auction market," International Review of Financial Analysis, Elsevier, vol. 15(4-5), pages 348-362.
    10. G. Mujtaba Mian & Christopher Adam, 2001. "Volatility dynamics in high frequency financial data: an empirical investigation of the Australian equity returns," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 341-352.
    11. Michael D. McKenzie, 2007. "Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 46-73, August.
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    Cited by:

    1. Zhang, Hang & Tsai, Wei-Che & Weng, Pei-Shih & Tsai, Pin-Chieh, 2023. "Overnight returns and investor sentiment: Further evidence from the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    2. Chu, Gang & Zhang, Yongjie & Zhang, Xiaotao, 2021. "An analysis of impact of cancellation activity on market quality: Evidence from China," Economic Modelling, Elsevier, vol. 102(C).
    3. Lin, William & Sun, David & Tsai, Shih-Chuan, 2010. "Does trading remove or bring frictions?," MPRA Paper 37285, University Library of Munich, Germany, revised Jan 2011.
    4. Rajesh Mohnot, 2020. "Examining Granger Causality in the Behavioral Reactions of Institutional Investors— Evidence from India," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-21, January.
    5. Hsieh, Shu-Fan & Chan, Chia-Ying & Wang, Ming-Chun, 2020. "Retail investor attention and herding behavior," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 109-132.

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    More about this item

    Keywords

    Liquidity; search model; limit order book; market depth; execution cost;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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