Title :
How much can Buffett influence the stock market? — A research of ACF
Author :
Zhigang, Zhao ; Wei, Zhang ; Xiaotao, Zhang
Author_Institution :
Coll. of Manage. & Econ, Tianjin Univ., Tianjin, China
Abstract :
Traditional classifier system is considered as a multi-population GAs architecture which represents individual learning. In real world, people learn not only from individual experience but also from others. By introducing a concept called `social learning bonus´ an extended classifier system which mixed individual learning and social learning is implemented in an artificial stock market. The results suggested social learning leads to different market statistic property around a threshold, and a state like HREE may be realized endogenously.
Keywords :
genetic algorithms; learning (artificial intelligence); multi-agent systems; stock markets; agent-based computational finance; artificial stock market; extended classifier system; individual learning; market statistic property; multipopulation genetic algorithm architecture; social learning bonus; Biological cells; Computer architecture; Educational institutions; Genetic algorithms; Portfolios; Stock markets;
Conference_Titel :
Information Science and Service Science (NISS), 2011 5th International Conference on New Trends in
Conference_Location :
Macao
Print_ISBN :
978-1-4577-0665-3