Publication detail

Learning in Heterogeneous Agent Model with the WOA

Author(s): Mgr. Lukáš Vácha Ph.D., Vosvrda, M
Type: Article in collection
Year: 2003
Number: 0
Published in: 6th International Conference on Applications of Mathematics and Statistics in Economy, 2003, Slovakia
Publishing place: Banska Bystrica,
JEL codes:
Suggested Citation:
Abstract: The Efficient Markets Hypothesis provides a theoretical basis for trading rules. Technical trading rules provide a signal of when to buy or sell an asset based on such price patterns to the user. Technical traders tend to put little faith in strict efficient markets. Fundamentalists rely on their model employing fundamental information basis to forecast the next price period. The traders determine whether current conditions call for the acquisition of fundamental information in a forward looking manner rather than relying on past performance. This approach relies on heterogeneity in the agent information and subsequent decisions either as fundamentalists or as chartists. It was shown that implementation of the learning agents process can significantly change the preferences of trader strategies. The Worst Out Algorithm (WOA) is used with this heterogeneous agent model to simulate more realistic market conditions. After every i iterations the WOA replaces the worst performing trading strategy (belief type) with the new one.
This paper shows an influence of the learning agents process on a heterogeneous agent model with the WOA.




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