Recent 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 dataSome recent laboratory work on expectationsformation in an asset pricing framework is also discussed.