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Short-term market efficiency indicator based on the waiting-time distribution

Author

Listed:
  • Syed Mujahid Hussain

    (Sultan Qaboos University)

  • Sergey Osmekhin

    (Hanken School of Economics)

  • Frédéric Délèze

    (Hanken School of Economics)

Abstract

This paper presents a quantitative approach to measure market efficiency based on the waiting-time distribution. We use the spread between two classes of ordinary shares of Royal Dutch Shell Plc, and two listings of Australia and New Zealand Banking Group Limited to observe market inefficient states. We find that the parameter of the waiting-time distribution provides a quantitative measure of the market inefficiency and can be used as a short-term market efficiency indicator. This approach can be applied to liquid financial markets and has clear implications for the investors, hedgers, regulators and policymakers.

Suggested Citation

  • Syed Mujahid Hussain & Sergey Osmekhin & Frédéric Délèze, 2021. "Short-term market efficiency indicator based on the waiting-time distribution," Review of Managerial Science, Springer, vol. 15(6), pages 1561-1572, August.
    • Handle: RePEc:spr:rvmgts:v:15:y:2021:i:6:d:10.1007_s11846-020-00398-w
    DOI: 10.1007/s11846-020-00398-w
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    References listed on IDEAS

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    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. Krauss, Christopher & Do, Xuan Anh & Huck, Nicolas, 2017. "Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500," European Journal of Operational Research, Elsevier, vol. 259(2), pages 689-702.
    3. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    4. Ronen, Tavy, 1997. "Tests and Properties of Variance Ratios in Microstructure Studies," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(2), pages 183-204, June.
    5. Mainardi, Francesco & Raberto, Marco & Gorenflo, Rudolf & Scalas, Enrico, 2000. "Fractional calculus and continuous-time finance II: the waiting-time distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 468-481.
    6. Scalas, Enrico & Gorenflo, Rudolf & Mainardi, Francesco, 2000. "Fractional calculus and continuous-time finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 284(1), pages 376-384.
    7. Wright, Jonathan H, 2000. "Alternative Variance-Ratio Tests Using Ranks and Signs," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 1-9, January.
    8. Chung, Dennis & Hrazdil, Karel, 2010. "Liquidity and market efficiency: A large sample study," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2346-2357, October.
    9. Belaire-Franch, Jorge & Opong, Kwaku K., 2005. "Some evidence of random walk behavior of Euro exchange rates using ranks and signs," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1631-1643, July.
    10. Bo Liu & Lo-Bin Chang & Hélyette Geman, 2017. "Intraday pairs trading strategies on high frequency data: the case of oil companies," Quantitative Finance, Taylor & Francis Journals, vol. 17(1), pages 87-100, January.
    11. Álvaro Cartea & Thilo Meyer-Brandis, 2010. "How Duration Between Trades of Underlying Securities Affects Option Prices," Review of Finance, European Finance Association, vol. 14(4), pages 749-785.
    12. Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2016. "The profitability of pairs trading strategies: distance, cointegration and copula methods," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1541-1558, October.
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    More about this item

    Keywords

    Market efficiency indicator; Market inefficiency; Statistical arbitrage; Waiting-time distribution;
    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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