Financial Markets as Nonlinear Adaptive Evolutionary Systems
AbstractRecent work on complex adaptive systems for modeling financialmarkets is surveyed. Financia1 markets areviewed as evolutionary systems between different, competing tradingstrategies. Agents are boundedly rational inthe sense that they tend to follow strategies that have performedwell, according to realized profits or accumulatedwea1th, in the recent past. Simple technical trading rules maysurvive evolutionary competition in a heterogeneousworld where prices and beliefs co-evolve over time. The evolutionarymodel explains stylized facts, such as fat tails,volatility clustering and long memory, of real financial series.Although our adaptive belief systems are very simple, they can matchthe autocorrelation patterns of returns,squared returns and absolute returns of 40 years of S&P 500 data"Some recent laboratory work on expectationsformation in an asset pricing framework is also discussed.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 01-014/1.
Date of creation: 06 Feb 2001
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Other versions of this item:
- C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
- Hommes, C.H., 2000. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," CeNDEF Working Papers 00-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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