Evolvement Complexity in an Artificial Stock Market
YANG Chun-Xia, ZHOU Tao, ZHOU Pei-Ling, LIU Jun, TANG Zi-Nan
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230026
Evolvement Complexity in an Artificial Stock Market
YANG Chun-Xia;ZHOU Tao;ZHOU Pei-Ling;LIU Jun;TANG Zi-Nan
Department of Electronic Science and Technology, University of Science and Technology of China, Hefei 230026
关键词 ：
89.90.+n ,
02.50.Le ,
64.60.Cn ,
87.10.+e
Abstract ： An artificial stock market is established based on the multi-agent model. Each agent has a limited memory of the history of stock price, and will choose an action according to its memory and trading strategy. The trading strategy of each agent evolves ceaselessly as a result of a self-teaching mechanism. The simulation results exhibit that large events are frequent in the fluctuation of the stock price generated by the present model when compared with a normal process, and the price returns distribution is a Lévy distribution in the central part followed by an approximately exponential truncation. In addition, by defining a variable to gauge the evolvement complexity of this system, we have found a phase cross-over from simple-phase to complex-phase along with the increase of the number of individuals, which may be a ubiquitous phenomenon in multifarious real-life systems.
Key words ：
89.90.+n
02.50.Le
64.60.Cn
87.10.+e
出版日期: 2005-04-01
:
89.90.+n
(Other topics in areas of applied and interdisciplinary physics)
02.50.Le
(Decision theory and game theory)
64.60.Cn
(Order-disorder transformations)
87.10.+e
引用本文:
YANG Chun-Xia;ZHOU Tao;ZHOU Pei-Ling;LIU Jun;TANG Zi-Nan. Evolvement Complexity in an Artificial Stock Market[J]. 中国物理快报, 2005, 22(4): 1014-1017.
链接本文:
https://cpl.iphy.ac.cn/CN/
或
https://cpl.iphy.ac.cn/CN/Y2005/V22/I4/1014
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