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Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach

Author

Listed:
  • Emanuele Citera

    (Department of Economics, New School for Social Research)

Abstract

This paper attempts to develop a theory of statistical equilibrium based on an entropy-constrained framework, that allow us to explain the distribution of stock returns over different market trends. By making use of the Quantal Response Statistical Equilibrium model (Scharfenaker and Foley, 2017), we recover the cross-sectional distribution of daily returns of individual company listed the S&P 500, over the period 1988-2019. We then make inference on the frequency distributions of returns by studying them over bull markets, bear markets and corrections. The results of the model shed light on the microscopic as well as macroscopic behavior of the stock market, in addition to provide insights in terms of stock returns distribution.

Suggested Citation

  • Emanuele Citera, 2021. "Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach," Working Papers 2116, New School for Social Research, Department of Economics.
    • Handle: RePEc:new:wpaper:2116
    as

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    File URL: http://www.economicpolicyresearch.org/econ/2021/NSSR_WP_162021.pdf
    File Function: First version, 2021
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    References listed on IDEAS

    as
    1. Kai-Yin Woo & Chulin Mai & Michael McAleer & Wing-Keung Wong, 2020. "Review on Efficiency and Anomalies in Stock Markets," Economies, MDPI, vol. 8(1), pages 1-51, March.
    2. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    3. Duncan K. Foley, 2020. "Unfulfilled Expectations: One Economist’s History," Springer Studies in the History of Economic Thought, in: Arie Arnon & Warren Young & Karine van der Beek (ed.), Expectations, pages 3-17, Springer.
    4. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    5. George Soros, 2013. "Fallibility, reflexivity, and the human uncertainty principle," Journal of Economic Methodology, Taylor & Francis Journals, vol. 20(4), pages 309-329, December.
    6. Paulo L dos Santos & Ellis Scharfenaker, 2019. "Competition, self-organization, and social scaling—accounting for the observed distributions of Tobin’s q," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(6), pages 1587-1610.
    7. Ellis Scharfenaker & Duncan Foley, 2017. "Maximum Entropy Estimation of Statistical Equilibrium in Economic Quantal Response Models," Working Papers 1710, New School for Social Research, Department of Economics, revised May 2017.
    8. Soofi, E. S. & Retzer, J. J., 2002. "Information indices: unification and applications," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 17-40, March.
    9. Emanuele Citera & Lino Sau, 2021. "Reflexivity, Financial Instability and Monetary Policy: A ‘Convention-Based’ Approach," Review of Political Economy, Taylor & Francis Journals, vol. 33(2), pages 327-343, April.
    10. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Theodosio, Bruno Miller & Weber, Jan, 2023. "Back to the classics: R-evolution towards statistical equilibria," ifso working paper series 28, University of Duisburg-Essen, Institute for Socioeconomics (ifso).

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    More about this item

    Keywords

    Stock returns; statistical equilibrium; information theory; stock market; maximum entropy;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G40 - Financial Economics - - Behavioral Finance - - - General

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