IDEAS home Printed from https://ideas.repec.org/p/new/wpaper/2116.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: http://www.economicpolicyresearch.org/econ/2021/NSSR_WP_162021.pdf
    File Function: First version, 2021
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. George Soros, 2013. "Fallibility, reflexivity, and the human uncertainty principle," Journal of Economic Methodology, Taylor & Francis Journals, vol. 20(4), pages 309-329, December.
    3. 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.
    4. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    5. 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.
    6. Soofi, E. S. & Retzer, J. J., 2002. "Information indices: unification and applications," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 17-40, March.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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. 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).

    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. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    2. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    3. Eduard Marinov, 2017. "The 2017 Nobel Prize in Economics," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 117-159.
    4. Committee, Nobel Prize, 2017. "Richard H. Thaler: Integrating Economics with Psychology," Nobel Prize in Economics documents 2017-1, Nobel Prize Committee.
    5. Giuseppe Pernagallo & Benedetto Torrisi, 2020. "A theory of information overload applied to perfectly efficient financial markets," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 14(2), pages 223-236, October.
    6. Samuel Tabot Enow, 2023. "Investigating Joint Market Hypothesis during Periods of Financial Distress and its Implications," International Journal of Economics and Financial Issues, Econjournals, vol. 13(2), pages 46-50, March.
    7. Thomas J. Brennan & Andrew W. Lo & Ruixun Zhang, 2018. "Variety Is the Spice of Life: Irrational Behavior as Adaptation to Stochastic Environments," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 8(03), pages 1-39, September.
    8. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    9. Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Joseph E. Stiglitz & Tania Treibich, 2020. "Rational Heuristics? Expectations And Behaviors In Evolving Economies With Heterogeneous Interacting Agents," Economic Inquiry, Western Economic Association International, vol. 58(3), pages 1487-1516, July.
    10. Khrennikova, Polina, 2016. "Application of quantum master equation for long-term prognosis of asset-prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 253-263.
    11. Maria De Paola & Francesca Gioia & Fabio Piluso, 2020. "Does Reminding of Behavioural Biases Increase Returns from Financial Trading? A Field Experiment," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 12(2), pages 1-1, February.
    12. Frankfurter, George M. & McGoun, Elton G. & Allen, Douglas E., 2004. "The prescriptive turn in behavioral finance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(4), pages 449-468, September.
    13. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    14. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    15. Paolo Barucca & Fabrizio Lillo, 2017. "Behind the price: on the role of agent's reflexivity in financial market microstructure," Papers 1708.07047, arXiv.org.
    16. Rilwan Sakariyahu & Mohamed Sherif & Audrey Paterson & Eleni Chatzivgeri, 2021. "Sentiment‐Apt investors and UK sector returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3321-3351, July.
    17. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    18. Sabiou M. Inoua, 2020. "News-Driven Expectations and Volatility Clustering," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    19. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    20. Yoshiyuki Nakazono, 2012. "Heterogeneity and anchoring in financial markets," Applied Financial Economics, Taylor & Francis Journals, vol. 22(21), pages 1821-1826, November.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:new:wpaper:2116. 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: Mark Setterfield (email available below). General contact details of provider: https://edirc.repec.org/data/denewus.html .

    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.