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Investment Behaviour under Knightian Uncertainty - An Evolutionary Approach

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  • Terje Lensberg

Abstract

The paper analyzes investment behaviour under Knightian uncertainty by means of a genetic programming algorithm. This is an experimental approach which yields analytical results at a level of generality comparable to that obtained by conventional methods. When the artificial agents receive the same information about the unknown probability distributions, they develop behaviour rules as if they were expected utility maximizers with Bayesian learning rules and logarithmic utility functions. We then introduce asymmetric information, and study how it affects the agents' implicit preferences for risk and uncertainty.

Suggested Citation

  • Terje Lensberg, 1997. "Investment Behaviour under Knightian Uncertainty - An Evolutionary Approach," CESifo Working Paper Series 126, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_126
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    1. Robert Aumann & Adam Brandenburger, 2014. "Epistemic Conditions for Nash Equilibrium," World Scientific Book Chapters,in: The Language of Game Theory Putting Epistemics into the Mathematics of Games, chapter 5, pages 113-136 World Scientific Publishing Co. Pte. Ltd..
    2. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58, pages 211-211.
    3. Philip J. Reny, 1992. "Rationality in Extensive-Form Games," Journal of Economic Perspectives, American Economic Association, vol. 6(4), pages 103-118, Fall.
    4. Camerer, Colin & Weber, Martin, 1992. "Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 325-370, October.
    5. Hakansson, Nils H., 1971. "Capital Growth and the Mean-Variance Approach to Portfolio Selection," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(01), pages 517-557, January.
    6. Dow, James & Werlang, Sergio Ribeiro da Costa, 1992. "Uncertainty Aversion, Risk Aversion, and the Optimal Choice of Portfolio," Econometrica, Econometric Society, vol. 60(1), pages 197-204, January.
    7. Blume, Lawrence & Easley, David, 1992. "Evolution and market behavior," Journal of Economic Theory, Elsevier, vol. 58(1), pages 9-40, October.
    8. Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
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    Cited by:

    1. Yu, Zuwei, 2003. "A spatial mean-variance MIP model for energy market risk analysis," Energy Economics, Elsevier, vol. 25(3), pages 255-268, May.
    2. Hans-Werner Sinn, 1999. "Inflation and Welfare: Comment on Robert Lucas," NBER Working Papers 6979, National Bureau of Economic Research, Inc.
    3. Witte, Björn-Christopher, 2012. "Fund managers - Why the best might be the worst: On the evolutionary vigor of risk-seeking behavior," Economics Discussion Papers 2012-20, Kiel Institute for the World Economy (IfW).
    4. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    5. Lensberg, Terje & Schenk-Hoppé, Klaus Reiner, 2006. "On the Evolution of Investment Strategies and the Kelly Rule – A Darwinian Approach," Discussion Papers 2006/23, Norwegian School of Economics, Department of Business and Management Science.
    6. repec:eee:tefoso:v:127:y:2018:i:c:p:38-56 is not listed on IDEAS
    7. Witte, Björn-Christopher, 2011. "Fund managers - why the best might be the worst: On the evolutionary vigor of risk-seeking behavior," BERG Working Paper Series 81, Bamberg University, Bamberg Economic Research Group.

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