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Selection matters

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  • Paolo Pin

    ()
    (Department of Applied Mathematics, University of Venice)

Abstract

To test for the adaptive optimization of risk attitudes, we use a simple model of preferences among lotteries, where agents evolve with a Genetic Algorithm. We find that the genetic selection operator are fundamental in determining the outcomes of the simulations, along with the possibility of iterate choices in a single generation and an eventual factor of heritage across generations (all innocuous technical parameters at a first sight). Different choices of these mechanisms may easily lead to opposite behaviors, from risk aversion to even risk love. The simulations give a hint on the possible implications of the different selection operators, when trying to model the evolution of risk attitudes in different social and economic settings.

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Bibliographic Info

Paper provided by Department of Applied Mathematics, Università Ca' Foscari Venezia in its series Working Papers with number 138.

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Length: 23 pages
Date of creation: Sep 2006
Date of revision:
Handle: RePEc:vnm:wpaper:138

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Keywords: Risk preferences; genetic algorithm;

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