Testing the rational expectations hypothesis with agent-based models of stock markets

被引：0

作者：

Chen, SH ^{[1
]}

Yeh, CH ^{[1
]}

Liao, CC ^{[1
]}

机构：

[1] Natl Chengchi Univ, Dept Econ, AI ECON Res Grp, Taipei 11623, Taiwan

来源：

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL I AND II | 1999年

关键词：

genetic programming; agent-based stock markets; rational expectations hypothesis; bounded rationality; business school; LISP trees;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Using agent-based models of stock markets, this paper examines the rational expectations hypothesis from a bottom-up perspective. We apply standard linear and nonlinear econometric tests to artificial time series generated from two artificial stock markets composed of bounded-rational traders. The two artificial stock markets differs in their architectures: one has a business school, and one does not. While the linear test shows that the market with the business school fails to reject the rational expectations hypothesis quite often, the nonlinear one does not. Therefore, strictly speaking, these two agent-based markets of bounded-rational traders do not collectively behave as what rational expectations hypothesis predicts, and hence do not lend support to rational expectations hypothesis.

引用

页码：381 / 387

页数：7