Presentation 2007-09-27
Multi-fractality Analysis of Artificial Stock Prices Generated by Behaviors of Multi-agants using GP Learning and its Applications to Recognition of Factors Governing Prices
Yoshikazu IKEDA, Shozo TOKINAGA,
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Abstract(in English) This report deals with the multi-fractality analysis of artificial stock prices generated by behaviors of multi-agants using GP learning and its applications to recognition of factors governing prices. Then, it is shown that the time series of artificial stock price reveals as a multi-fractal signal. By applying prediction method for mono-fractal time series, the feature of the multi-fractal time series are extracted. We classify several cases by changing the composition (number) of agents of types. A backward method is applied to estimate the composition of agents who are seemed to dominate the stock market by using discriminant analysis.
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Keyword(in English) Multi-fractal / Artificial stock market / Multi-Agent-based modeling / Genetic Programming
Paper # SIP2007-84,SIS2007-20,SP2007-46
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Committee SIS
Conference Date 2007/9/20(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Multi-fractality Analysis of Artificial Stock Prices Generated by Behaviors of Multi-agants using GP Learning and its Applications to Recognition of Factors Governing Prices
Sub Title (in English)
Keyword(1) Multi-fractal
Keyword(2) Artificial stock market
Keyword(3) Multi-Agent-based modeling
Keyword(4) Genetic Programming
1st Author's Name Yoshikazu IKEDA
1st Author's Affiliation Faculty of Economics, Shinshu University()
2nd Author's Name Shozo TOKINAGA
2nd Author's Affiliation Graduate School of Economics, Kyushu University
Date 2007-09-27
Paper # SIP2007-84,SIS2007-20,SP2007-46
Volume (vol) vol.107
Number (no) 236
Page pp.pp.-
#Pages 6
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