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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- M. Keith Chen & Venkat Lakshminarayanan & Laurie R. Santos, 2006. "How Basic Are Behavioral Biases? Evidence from Capuchin Monkey Trading Behavior," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 517-537, June.
- Sanford Grossman & Oliver Hart, .
"An Analysis of the Principal-Agent Problem,"
Rodney L. White Center for Financial Research Working Papers
15-80, Wharton School Rodney L. White Center for Financial Research.
- Jerry R. Green & Nancy L. Stokey, 1982.
"A Comparison of Tournaments and Contracts,"
NBER Working Papers
0840, National Bureau of Economic Research, Inc.
- Arthur J. Robson, 2002. "Evolution and Human Nature," Journal of Economic Perspectives, American Economic Association, vol. 16(2), pages 89-106, Spring.
- Joost M. E. Pennings & Ale Smidts, 2003. "The Shape of Utility Functions and Organizational Behavior," Management Science, INFORMS, vol. 49(9), pages 1251-1263, September.
- Lettau, Martin, 1997. "Explaining the facts with adaptive agents: The case of mutual fund flows," Journal of Economic Dynamics and Control, Elsevier, vol. 21(7), pages 1117-1147, June.
- Matthew Rabin, 2001.
"Inference by Believers in the Law of Small Numbers,"
Method and Hist of Econ Thought
- Matthew Rabin, 2002. "Inference By Believers In The Law Of Small Numbers," The Quarterly Journal of Economics, MIT Press, vol. 117(3), pages 775-816, August.
- Matthew Rabin., 2000. "Inference by Believers in the Law of Small Numbers," Economics Working Papers E00-282, University of California at Berkeley.
- Rabin, Matthew, 2000. "Inference by Believers in the Law of Small Numbers," Department of Economics, Working Paper Series qt4sw8n41t, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
- John A. List, 2004.
"Neoclassical Theory Versus Prospect Theory: Evidence from the Marketplace,"
Econometric Society, vol. 72(2), pages 615-625, 03.
- John List, 2004. "Neoclassical theory versus prospect theory: Evidence from the marketplace," Framed Field Experiments 00174, The Field Experiments Website.
- John A. List, 2003. "Neoclassical Theory Versus Prospect Theory: Evidence from the Marketplace," NBER Working Papers 9736, National Bureau of Economic Research, Inc.
- Thomas Riechmann, 1999.
"Learning and behavioral stability An economic interpretation of genetic algorithms,"
Journal of Evolutionary Economics,
Springer, vol. 9(2), pages 225-242.
- Riechmann, Thomas, 1997. "Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms," Hannover Economic Papers (HEP) dp-209, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Robson, Arthur J., 1996. "A Biological Basis for Expected and Non-expected Utility," Journal of Economic Theory, Elsevier, vol. 68(2), pages 397-424, February.
- Levy, Moshe, 2005. "Is risk-aversion hereditary?," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 157-168, February.
- Arthur J. Robson, 2001. "The Biological Basis of Economic Behavior," Journal of Economic Literature, American Economic Association, vol. 39(1), pages 11-33, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marco LiCalzi).
If references are entirely missing, you can add them using this form.