AbstractTo 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 InfoPaper provided by Department of Applied Mathematics, Università Ca' Foscari Venezia in its series Working Papers with number 138.
Length: 23 pages
Date of creation: Sep 2006
Date of revision:
Risk preferences; genetic algorithm;
Find related papers by 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-11-04 (All new papers)
- NEP-CMP-2006-11-04 (Computational Economics)
- NEP-EVO-2006-11-04 (Evolutionary Economics)
- NEP-UPT-2006-11-04 (Utility Models & Prospect Theory)
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