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Martingales, Efficient Market Hypothesis and Kolmogorov’s Complexity Theory

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  • 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.

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  • 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
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    References listed on IDEAS

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    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.
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    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).
    2. Fang Wang & Marko Gacesa, 2024. "Semi-strong Efficient Market of Bitcoin and Twitter: an Analysis of Semantic Vector Spaces of Extracted Keywords and Light Gradient Boosting Machine Models," Papers 2409.15988, arXiv.org.

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