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Evolution, efficiency and noise traders in a one-sided auction market

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  • Luo, Guo Ying

Abstract

This paper uses an evolutionary approach incorporating the idea of natural selection to examine market behavior in a one-sided buyer auction market. Even with no traders' rationality (such as rational expectations and adaptive learning) and with each trader's behavior preprogrammed with its own inherent and fixed probabilities of overpredicting, predicting correctly and underpredicting the fundamental value of the asset, an informationally efficient market can occur. Traders' behavior is consistent with systematic patterns of judgment biases as documented in the psychological literature. Specifically, shares of one unit of a risky asset are sold at the beginning and liquidated at the end of each time period. The asset's liquidation value is the product of its fundamental value and the exponential of a random shock. Buyers enter the market sequentially over time and each buyer merely acts upon its own inherent and fixed probabilities of overpredicting, predicting correctly and underpredicting the fundamental value. As time goes by there is a constant redistribution of wealth toward buyers who make better predictions. This paper shows that if each buyer's initial wealth is sufficiently small relative to the market supply and if the variation in the random shock to the asset is sufficiently small, then as time gets sufficiently large, the proportion of time, that the asset price is arbitrarily close to the fundamental liquidation value, converges to one with probability one. This conclusion is established under a weak restriction regarding the presence of traders with sufficiently low probabilities of overpredicting the fundamental value.
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  • Luo, Guo Ying, 2003. "Evolution, efficiency and noise traders in a one-sided auction market," Journal of Financial Markets, Elsevier, vol. 6(2), pages 163-197, April.
  • Handle: RePEc:eee:finmar:v:6:y:2003:i:2:p:163-197
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    Cited by:

    1. Luo, Guo Ying, 2012. "Conservative traders, natural selection and market efficiency," Journal of Economic Theory, Elsevier, vol. 147(1), pages 310-335.
    2. Jasmina Hasanhodzic & Andrew Lo & Emanuele Viola, 2011. "A computational view of market efficiency," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1043-1050.
    3. Andrew W. Lo & Mila Getmansky & Peter A. Lee, 2015. "Hedge Funds: A Dynamic Industry in Transition," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 483-577, December.

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    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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