IDEAS home Printed from https://ideas.repec.org/a/spr/rvmgts/v15y2021i6d10.1007_s11846-020-00398-w.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11846-020-00398-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11846-020-00398-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    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. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Semenov, Andrei, 2015. "The small-cap effect in the predictability of individual stock returns," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 178-197.
    2. Md Lutfur Rahman & Mahbub Khan & Samuel A. Vigne & Gazi Salah Uddin, 2021. "Equity return predictability, its determinants, and profitable trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 162-186, January.
    3. Hellström, Jörgen & Liu, Yuna & Sjögren, Tomas, 2016. "Stock exchange mergers and weak-form information efficiency: Evidence from the OMX Nordic and Baltic consolidation," Umeå Economic Studies 923, Umeå University, Department of Economics.
    4. Choi, Gahyun & Park, Kwangyeol & Yi, Eojin & Ahn, Kwangwon, 2023. "Price fairness: Clean energy stocks and the overall market," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    5. Kim, Jae H. & Shamsuddin, Abul, 2008. "Are Asian stock markets efficient? Evidence from new multiple variance ratio tests," Journal of Empirical Finance, Elsevier, vol. 15(3), pages 518-532, June.
    6. Krzysztof Kompa & Aleksandra Matuszewska-Janica, 2009. "Efficiency of the Warsaw Stock Exchange: Analysis of Selected Properties," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(1), pages 59-70, February.
    7. Fahad Almudhaf, 2014. "Testing for random walk behaviour in CIVETS exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 21(1), pages 60-63, January.
    8. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1-2), pages 27-35, January.
    9. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.
    10. Peter C. B. Phillips & Sainan Jin, 2014. "Testing the Martingale Hypothesis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(4), pages 537-554, October.
    11. Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
    12. Kim, Jae H., 2009. "Automatic variance ratio test under conditional heteroskedasticity," Finance Research Letters, Elsevier, vol. 6(3), pages 179-185, September.
    13. Dilip Kumar & Srinivasan Maheswaran, 2014. "Are major global stock markets efficient? An application of the martingale difference hypothesis with wild bootstrap," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 3(2/3/4), pages 217-233.
    14. Torricelli, Lorenzo, 2020. "Trade duration risk in subdiffusive financial models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    15. Amélie Charles & Olivier Darné, 2009. "Variance‐Ratio Tests Of Random Walk: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 23(3), pages 503-527, July.
    16. Omid Sabbaghi & Navid Sabbaghi, 2017. "The Chicago Climate Exchange and market efficiency: an empirical analysis," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(4), pages 711-734, October.
    17. Katusiime, Lorna & Shamsuddin, Abul & Agbola, Frank W., 2015. "Foreign exchange market efficiency and profitability of trading rules: Evidence from a developing country," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 315-332.
    18. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    19. Johannes Stübinger & Sylvia Endres, 2018. "Pairs trading with a mean-reverting jump–diffusion model on high-frequency data," Quantitative Finance, Taylor & Francis Journals, vol. 18(10), pages 1735-1751, October.
    20. Zhang, Chris H. & Frijns, Bart, 2019. "Noise trading and informational efficiency," EconStor Preprints 198037, ZBW - Leibniz Information Centre for Economics.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:rvmgts:v:15:y:2021:i:6:d:10.1007_s11846-020-00398-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.