IDEAS home Printed from https://ideas.repec.org/a/rnd/arimbr/v2y2011i6p252-258.html
   My bibliography  Save this article

Martingales, Efficient Market Hypothesis and Kolmogorov’s Complexity Theory

Author

Listed:
  • Amaresh Das

Abstract

Efficient market theory states that financial markets can process information instantly. Empirical observations have challenged the stricter form of the efficient market hypothesis (EMH). These empirical observations and theoretical considerations show that price changes are difficult to predict if one starts from the time series of price changes. This paper provides an explanation in terms of algorithmic complexity theory of Kolmogorov that makes a clearer connection between the efficient market hypothesis and the unpredictable character of stock returns.

Suggested Citation

  • Amaresh Das, 2011. "Martingales, Efficient Market Hypothesis and Kolmogorov’s Complexity Theory," Information Management and Business Review, AMH International, vol. 2(6), pages 252-258.
  • Handle: RePEc:rnd:arimbr:v:2:y:2011:i:6:p:252-258
    DOI: 10.22610/imbr.v2i6.905
    as

    Download full text from publisher

    File URL: https://ojs.amhinternational.com/index.php/imbr/article/view/905/905
    Download Restriction: no

    File URL: https://ojs.amhinternational.com/index.php/imbr/article/view/905
    Download Restriction: no

    File URL: https://libkey.io/10.22610/imbr.v2i6.905?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
    ---><---

    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
    3. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    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. Wang, Fang & Gacesa, Marko, 2023. "Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models," International Review of Financial Analysis, Elsevier, vol. 88(C).

    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. Connor, Gregory & Linton, Oliver, 2007. "Semiparametric estimation of a characteristic-based factor model of common stock returns," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 694-717, December.
    2. Faiza Siddiqui & Yusheng Kong & Hyder Ali & Salma Naz, 2024. "Energy-Related Uncertainty and Idiosyncratic Return Volatility: Implications for Sustainable Investment Strategies in Chinese Firms," Sustainability, MDPI, vol. 16(17), pages 1-39, August.
    3. Coen, Alain & Racicot, Francois-Eric, 2007. "Capital asset pricing models revisited: Evidence from errors in variables," Economics Letters, Elsevier, vol. 95(3), pages 443-450, June.
    4. Alain Coen & Francois-Éric Racicot, 2006. "A New Approach Based on Cumulants for Estimating Financial Regression Models with Errors in the Variables: the Fama and French Model Revisited," RePAd Working Paper Series UQO-DSA-wp142006, Département des sciences administratives, UQO.
    5. J. Ginger Meng & Gang Hu & Jushan Bai, 2011. "Olive: A Simple Method For Estimating Betas When Factors Are Measured With Error," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 34(1), pages 27-60, March.
    6. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.
    7. Carolin Pflueger & Emil Siriwardane & Adi Sunderam, 2019. "Financial Market Risk Perceptions and the Macroeconomy," NBER Working Papers 26290, National Bureau of Economic Research, Inc.
    8. Tomasz Wisniewski & Geoffrey Lightfoot & Simon Lilley, 2012. "Speculating on presidential success: exploring the link between the price–earnings ratio and approval ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 106-122, January.
    9. Fuerst, Michael E., 2006. "Investor risk premia and real macroeconomic fluctuations," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 540-563, September.
    10. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    11. Wan Mahmood, Wan Mansor & Abdul Fatah, Faizatul Syuhada, 2007. "Multivariate Causal Estimates of Dividend Yields, Price Earning Ratio and Expected Stock Returns: Experience from Malaysia," MPRA Paper 14614, University Library of Munich, Germany.
    12. Carmichael, Benoît & Coën, Alain, 2008. "Asset pricing models with errors-in-variables," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 778-788, September.
    13. Hanna, J. Douglas & Ready, Mark J., 2005. "Profitable predictability in the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 78(3), pages 463-505, December.
    14. Cássio Roberto de Andrade Alves & Márcio Laurini, 2023. "Estimating the Capital Asset Pricing Model with Many Instruments: A Bayesian Shrinkage Approach," Mathematics, MDPI, vol. 11(17), pages 1-20, September.
    15. Oliver Linton & Gregory Connor, 2000. "Semiparametric Estimation of a Characteristic-Based Factor Model of Stock Returns," FMG Discussion Papers dp346, Financial Markets Group.
    16. Himme, Alexander & Fischer, Marc, 2014. "Drivers of the cost of capital: The joint role of non-financial metrics," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 224-238.
    17. Hillebrand, Eric & Schnabl, Gunther & Ulu, Yasemin, 2009. "Japanese foreign exchange intervention and the yen-to-dollar exchange rate: A simultaneous equations approach using realized volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 490-505, July.
    18. 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.
    19. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    20. Frederico Belo & Chen Xue & Lu Zhang, 2010. "Cross-sectional Tobin's Q," NBER Working Papers 16336, National Bureau of Economic Research, Inc.

    More about this item

    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:rnd:arimbr:v:2:y:2011:i:6:p:252-258. 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: Muhammad Tayyab (email available below). General contact details of provider: https://ojs.amhinternational.com/index.php/imbr .

    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.