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Informed trading, market efficiency and volatility

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  • Sung, Ming-Chien
  • Johnson, Johnnie E.V.
  • McDonald, David C.J.

Abstract

We establish relationships that have proved difficult to capture in financial markets, between informed trading, efficiency and volatility. We examine the efficiency and volatility of market prices in 6058 parallel horserace betting exchange and bookmaker markets (1.8 million price points). We find that informed trading is associated with increased efficiency and volatility.

Suggested Citation

  • Sung, Ming-Chien & Johnson, Johnnie E.V. & McDonald, David C.J., 2016. "Informed trading, market efficiency and volatility," Economics Letters, Elsevier, vol. 149(C), pages 56-59.
    • Handle: RePEc:eee:ecolet:v:149:y:2016:i:c:p:56-59
    DOI: 10.1016/j.econlet.2016.10.015
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    References listed on IDEAS

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    1. Johnnie E. V. Johnson & Owen Jones & Leilei Tang, 2006. "Exploring Decision Makers' Use of Price Information in a Speculative Market," Management Science, INFORMS, vol. 52(6), pages 897-908, June.
    2. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    3. Tavakoli, Manouchehr & McMillan, David & McKnight, Phillip J., 2012. "Insider trading and stock prices," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 254-266.
    4. Shiller, Robert J, 1990. "Market Volatility and Investor Behavior," American Economic Review, American Economic Association, vol. 80(2), pages 58-62, May.
    5. Law, David & Peel, David A, 2002. "Insider Trading, Herding Behaviour and Market Plungers in the British Horse-Race Betting Market," Economica, London School of Economics and Political Science, vol. 69(274), pages 327-338, May.
    6. Marshall Gramm & Douglas H. Owens, 2006. "Efficiency in Pari-Mutuel Betting Markets across Wagering Pools in the Simulcast Era," Southern Economic Journal, John Wiley & Sons, vol. 72(4), pages 926-937, April.
    7. Robert Bloomfield & Maureen O'Hara & Gideon Saar, 2009. "How Noise Trading Affects Markets: An Experimental Analysis," Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2275-2302, June.
    8. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    9. Michael A. Smith & David Paton & Leighton Vaughan Williams, 2006. "Market Efficiency in Person‐to‐Person Betting," Economica, London School of Economics and Political Science, vol. 73(292), pages 673-689, November.
    10. Shin, Hyun Song, 1993. "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims," Economic Journal, Royal Economic Society, vol. 103(420), pages 1141-1153, September.
    11. David Johnstone, 2016. "The Effect of Information on Uncertainty and the Cost of Capital," Contemporary Accounting Research, John Wiley & Sons, vol. 33(2), pages 752-774, June.
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    Cited by:

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    6. Kee H. Chung & Chairat Chuwonganant, 2023. "Tick size and price efficiency: Further evidence from the Tick Size Pilot Program," Financial Management, Financial Management Association International, vol. 52(3), pages 483-511, September.
    7. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    8. Tadgh Hegarty, 2021. "Information and price efficiency in the absence of home crowd advantage," Applied Economics Letters, Taylor & Francis Journals, vol. 28(21), pages 1902-1907, December.

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    More about this item

    Keywords

    Informed trading; Efficiency; Volatility;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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