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On the distribution of stock-market returns - Implications of Evolutionary Finance

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  • Stefan Reimann

Abstract

Risk management and asset pricing benefit from simple functional descriptions of the distribution of real asset returns. Recently, several authors have proposed that asset returns in real stock markets are distributed according to a hyperbolic distribution. While asset returns are generated by trades over time, the natural question is: What does economic theory imply concerning return distributions? We propose a simple model of price formation and, thus, return distribution which is based on economic reasoning. The markets behavior is represented by a pair consisting of a time-constant strategy and a dynamical trading strategy generating a flow between funds. Simulations of the price dynamics generate returns with fat-tail behavior in line with that of a hyperbolic distribution.

Suggested Citation

  • Stefan Reimann, "undated". "On the distribution of stock-market returns - Implications of Evolutionary Finance," IEW - Working Papers 232, Institute for Empirical Research in Economics - University of Zurich.
    • Handle: RePEc:zur:iewwpx:232
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    File URL: https://www.zora.uzh.ch/id/eprint/52125/1/iewwp232.pdf
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    References listed on IDEAS

    as
    1. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    4. Blume, Lawrence & Easley, David, 1992. "Evolution and market behavior," Journal of Economic Theory, Elsevier, vol. 58(1), pages 9-40, October.
    5. Amir, Rabah & Evstigneev, Igor V. & Hens, Thorsten & Schenk-Hoppe, Klaus Reiner, 2005. "Market selection and survival of investment strategies," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 105-122, February.
    6. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    7. Igor V. Evstigneev & Thorsten Hens & Klaus Reiner Schenk‐Hoppé, 2002. "Market Selection Of Financial Trading Strategies: Global Stability," Mathematical Finance, Wiley Blackwell, vol. 12(4), pages 329-339, October.
    8. Madan, Dilip B & Seneta, Eugene, 1990. "The Variance Gamma (V.G.) Model for Share Market Returns," The Journal of Business, University of Chicago Press, vol. 63(4), pages 511-524, October.
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    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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