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Title: Agent-Based Computational Modeling of the Stock Price-Volume Relation
Authors: 陳樹衡;C.-C. Liao
Contributors: 政大經濟系
Keywords: Agent-based model;Artificial stock markets;Genetic programming;Granger causality test;Stock price–volume relation;Micro–macro relation
Date: 2005-02
Issue Date: 2009-01-09 12:14:42 (UTC+8)
Abstract: From the perspective of the agent-based model of stock markets, this paper examines the possible explanations for the presence of the causal relation between stock returns and trading volume. Using the agent-based approach, we find that the explanation for the presence of the stock price–volume relation may be more fundamental. Conventional devices such as information asymmetry, reaction asymmetry, noise traders or tax motives are not explicitly required. In fact, our simulation results show that the stock price–volume relation may be regarded as a generic property of a financial market, when it is correctly represented as an evolving decentralized system of autonomous interacting agents. One striking feature of agent-based models is the rich profile of agents' behavior. This paper makes use of the advantage and investigates the micro–macro relations within the market. In particular, we trace the evolution of agents' beliefs and examine their consistency with the observed aggregate market behavior. We argue that a full understanding of the price–volume relation cannot be accomplished unless the feedback relation between individual behavior at the bottom and aggregate phenomena at the top is well understood.
Relation: Information Sciences,170(1),75-100
Data Type: article
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