Research on learning behavior of traders in artificial stock market based on genetic algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Jinbo:2011:ICEE,

• author = "Wang Jinbo and Su Bo",
• booktitle = "E-Business and E-Government (ICEE), 2011 International Conference on",
• title = "Research on learning behavior of traders in artificial stock market based on genetic algorithm",
• year = "2011",
• note = "in chinese",
• DOI = "doi:10.1109/ICEBEG.2011.5882429",
• abstract = "In this paper, one kind of artificial stock market which based on genetic algorithm is built. By using statistic theories and methods, learning behaviour of traders in this market is researched. In order to survive in the stock market, traders should learn from each other as new information becoming available and adapt their behaviour accordingly over time. It is the interacting of the adaptive traders causing the complexity of stock market and the abnormal phenomena of the market. Therefore, the conclusions based on this study have the theoretical and realistic significance.",
• keywords = "genetic algorithms, genetic programming, Banking, Pricing, Stock markets, Time series analysis, Artificial Stock Market, Individual Learning, Social Learning",
• notes = "Also known as \cite{5882429}",

}

Genetic Programming entries for Wang Jinbo Su Bo

Citations