Trading restrictions, price dynamics and allocative efficiency in double auction markets: Analysis based on agent-based modeling and simulations

被引:12
|
作者
Chen, SH [1 ]
Tai, CC [1 ]
机构
[1] Natl Chengchi Univ, Dept Econ, AI ECON Res Ctr, Taipei 11623, Taiwan
来源
ADVANCES IN COMPLEX SYSTEMS | 2003年 / 6卷 / 03期
关键词
agent-based DA market; genetic programming; quote limit; alhpa value; allocative efficiency;
D O I
10.1142/S021952590300089X
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this paper we conduct two experiments within an agent-based double auction market. These two experiments allow us to see the effect of learning and smartness on price dynamics and allocative efficiency. Our results are largely consistent with the stylized facts observed in experimental economics with human subjects. From the amelioration of price deviation and allocative efficiency, the effect of learning is vividly seen. However, smartness does not enhance market performance. In fact, the experiment with smarter agents (agents without a quote limit) results in a less stable price dynamics and lower allocative efficiency.
引用
收藏
页码:283 / 302
页数:20
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