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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.

Suggested Citation

  • Paolo Pin, 2006. "Selection matters," Working Papers 138, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:138
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    References listed on IDEAS

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    More about this item

    Keywords

    Risk preferences; genetic algorithm;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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