We introduce a simple asset pricing model with two types of adaptively learning traders, fundamentalists and technical traders. Traders update their beliefs according to past performance and to market conditions. The model generates endogenous price fluctuations and captures some stylized facts observed in real returns data, such as excess volatility, fat tails of returns distributions, volatility clustering, and long memory. We show that the results are quite robust w.r.t. to different choices for the performance measure.
CITATION STYLE
Gaunersdorfer, A., & Hommes, C. H. (2001). Nonlinear adaptive beliefs and the dynamics of financial markets: The role of the evolutionary fitness measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 782–789). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_109
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