DocumentCode
1654312
Title
Notice of Retraction
Research on learning behavior of traders in artificial stock market based on genetic algorithm
Author
Jinbo, Wang ; Bo, Su
Author_Institution
Department of Planning and Statistic, Xiamen University, Xiamen, China
fYear
2011
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, one kind of artificial stock market which based on genetic algorithm is built. By using statistic theories and methods, learning behavior 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 behavior 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.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, one kind of artificial stock market which based on genetic algorithm is built. By using statistic theories and methods, learning behavior 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 behavior 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
Banking; Genetic algorithms; Genetic programming; Pricing; Stock markets; Time series analysis; Artificial Stock Market; Individual Learning; Social Learning; genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
E -Business and E -Government (ICEE), 2011 International Conference on
Conference_Location
Shanghai, China
Print_ISBN
978-1-4244-8691-5
Type
conf
DOI
10.1109/ICEBEG.2011.5882429
Filename
5882429
Link To Document