IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v22y2003i2p273-284.html
   My bibliography  Save this article

Using a Stochastic Complexity Measure to Check the Efficient Market Hypothesis

Author

Listed:
  • Armin Shmilovici
  • Yael Alon-Brimer
  • Shmuel Hauser

Abstract

The weak form of the Efficient Market Hypothesis (EMH) states that current market price reflects fully the information from past prices and rules out prediction based on price data alone. No recent test of time series of stock returns rejects this weak-form hypothesis. This research offers another test of the weak form of the EHM that leads to different conclusions for some time series.The stochastic complexity of a time series is a measure of the number of bits needed to represent and reproduce the information in the time series. In an efficient market, compression of the time series is not possible, because there are no patterns and the stochastic complexity is high. In this research, Rissanen's context tree algorithm is used to identify recurring patterns in the data, and use them for compression. The weak form of the EMH is tested for 13 international stock indices and for all the stocks that comprise the Tel-Aviv 25 index (TA25), using sliding windows of 50, 75, and 100 consecutive daily returns. Statistically significant compression is detected in ten of the international stock index series. In the aggregate, 60% to 84% of the TA25 stocks tested demonstrate compressibility beyond randomness. This indicates potential market inefficiency. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • Armin Shmilovici & Yael Alon-Brimer & Shmuel Hauser, 2003. "Using a Stochastic Complexity Measure to Check the Efficient Market Hypothesis," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 273-284, October.
    • Handle: RePEc:kap:compec:v:22:y:2003:i:2:p:273-284
    DOI: 10.1023/A:1026198216929
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1026198216929
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1026198216929?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ching-Wei Tan, 1999. "Estimating the Complexity Function of Financial Time Series: An Estimation Based on Predictive Stochastic Complexity," Computing in Economics and Finance 1999 1143, Society for Computational Economics.
    2. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brandouy, Olivier & Delahaye, Jean-Paul & Ma, Lin & Zenil, Hector, 2014. "Algorithmic complexity of financial motions," Research in International Business and Finance, Elsevier, vol. 30(C), pages 336-347.
    2. Sornette, Didier & Zhou, Wei-Xing, 2006. "Predictability of large future changes in major financial indices," International Journal of Forecasting, Elsevier, vol. 22(1), pages 153-168.
    3. Lucio Maria Calcagnile & Fulvio Corsi & Stefano Marmi, 2016. "Entropy and efficiency of the ETF market," Papers 1609.04199, arXiv.org.
    4. Shternshis, Andrey & Mazzarisi, Piero & Marmi, Stefano, 2022. "Measuring market efficiency: The Shannon entropy of high-frequency financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    5. Olivier Brandouy & Jean-Paul Delahaye & Lin Ma, 2015. "Estimating the Algorithmic Complexity of Stock Markets," Papers 1504.04296, arXiv.org.

    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. Shmilovici Armin & Ben-Gal Irad, 2012. "Predicting Stock Returns Using a Variable Order Markov Tree Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-33, December.
    2. Armin Shmilovici & Yoav Kahiri & Irad Ben-Gal & Shmuel Hauser, 2009. "Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 33(2), pages 131-154, March.
    3. Brandouy, Olivier & Delahaye, Jean-Paul & Ma, Lin & Zenil, Hector, 2014. "Algorithmic complexity of financial motions," Research in International Business and Finance, Elsevier, vol. 30(C), pages 336-347.
    4. Christiane Goodfellow & Dirk Schiereck & Steffen Wippler, 2013. "Are behavioural finance equity funds a superior investment? A note on fund performance and market efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 14(2), pages 111-119, April.
    5. Das, Prashant & Füss, Roland & Hanle, Benjamin & Russ, Isabel Nina, 2020. "The cross-over effect of irrational sentiments in housing, commercial property, and stock markets," Journal of Banking & Finance, Elsevier, vol. 114(C).
    6. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    7. Carl R. Zulauf & Scott H. Irwin, 1998. "Market Efficiency and Marketing to Enhance Income of Crop Producers," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 20(2), pages 308-331.
    8. Benjamin Botor & Benjamin Boecker & Thomas Kalabis & Christoph Weber, "undated". "Estimating the value of flexibility from real options: On the accuracy of hybrid electricity price models," EWL Working Papers 1805, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    9. Dinabandhu Bag & Saurabh Goel, 2023. "Weak Form of Call Auction Prices: Simulation Using Monte Carlo Variants," Capital Markets Review, Malaysian Finance Association, vol. 31(1), pages 59-71.
    10. Roscoe, Philip & Howorth, Carole, 2009. "Identification through technical analysis: A study of charting and UK non-professional investors," Accounting, Organizations and Society, Elsevier, vol. 34(2), pages 206-221, February.
    11. Maria Teresa Medeiros Garcia & Tiago Miguel Batista Raimundo, 2024. "The Impact of Player Transfers on European Football Clubs Stock Prices: An Event Study Analysis," Working Papers REM 2024/0361, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    12. Nam, Kiseok & Pyun, Chong Soo & Kim, Sei-Wan, 2003. "Is asymmetric mean-reverting pattern in stock returns systematic? Evidence from Pacific-basin markets in the short-horizon," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(5), pages 481-502, December.
    13. Ito, Akitoshi, 1999. "Profits on technical trading rules and time-varying expected returns: evidence from Pacific-Basin equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 7(3-4), pages 283-330, August.
    14. Kuchin I.I., 2016. "Exchange rate risk exposure in asset pricing theory," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 16(3), pages 31-41.
    15. Carlo Rosa & Giovanni Verga, 2006. "The Impact of Central Bank Announcements on Asset Prices in Real Time: Testing the Efficiency of the Euribor Futures Market," CEP Discussion Papers dp0764, Centre for Economic Performance, LSE.
    16. Rabia najaf, 2017. "Hedging Effectiveness of Crude Palm Oil on the performance of stock Market Malaysia," International Journal of Academic Research in Management and Business, International Journal of Academic Research in Management and Business, vol. 2(1), pages 6-15, january.
    17. Xianfeng Jiang & Yongdong Shi, 2006. "The Impact of Insider Trading on the Secondary Market with Order-Driven System," Annals of Economics and Finance, Society for AEF, vol. 7(1), pages 129-143, May.
    18. Aaryan Gupta & Vinya Dengre & Hamza Abubakar Kheruwala & Manan Shah, 2020. "Comprehensive review of text-mining applications in finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
    19. Christian Walter, 2005. "La gestion indicielle et la théorie des moyennes," Revue d'Économie Financière, Programme National Persée, vol. 79(2), pages 113-136.
    20. Thomas Delcey, 2019. "Samuelson vs Fama on the Efficient Market Hypothesis: The Point of View of Expertise [Samuelson vs Fama sur l’efficience informationnelle des marchés financiers : le point de vue de l’expertise]," Post-Print hal-01618347, HAL.

    More about this item

    Keywords

    stochastic complexity; the Efficient Market Hypothesis; context tree;
    All these keywords.

    JEL classification:

    • 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:kap:compec:v:22:y:2003:i:2:p:273-284. 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.