Trading restrictions, price dynamics and allocative efficiency in double auction markets: Analysis based on agent-based modeling and simulations
Authored by CC Tai
Date Published: 2003-09
DOI: 10.1142/s021952590300089x
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Abstract
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.
Tags
genetic programming
agent-based DA market
alhpa value
allocative efficiency
quote limit