Agent-based computational modeling of the stock price-volume relation

被引:30
|
作者
Chen, SH [1 ]
Liao, CC
机构
[1] Natl Chengchi Univ, Dept Econ, AI ECON Res Ctr, Taipei 116, Taiwan
[2] Natl Taiwan Univ, Dept Int Business, Taipei 106, Taiwan
关键词
agent-based model; artificial stock markets; genetic programming; Granger causality test; stock price-volume relation; micro-macro relation;
D O I
10.1016/j.ins.2003.03.026
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:75 / 100
页数:26
相关论文
共 50 条
  • [21] An Agent-Based Modeling Approach to Brain Drain
    Gursoy, Furkan
    Badur, Bertan
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2022, 9 (02) : 356 - 365
  • [22] Trading restrictions, price dynamics and allocative efficiency in double auction markets: Analysis based on agent-based modeling and simulations
    Chen, SH
    Tai, CC
    ADVANCES IN COMPLEX SYSTEMS, 2003, 6 (03): : 283 - 302
  • [23] Creative potential and migration patterns: an agent-based computational approach
    Favaretto, Leonardo Francisco
    da Silva Catela, Eva Yamila
    REVISTA BRASILEIRA DE INOVACAO, 2020, 19
  • [24] Testing the rational expectations hypothesis with agent-based models of stock markets
    Chen, SH
    Yeh, CH
    Liao, CC
    INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL I AND II, 1999, : 381 - 387
  • [25] Surrogate Modeling of Agent-Based Airport Terminal Operations
    De Leeuw, Benyamin
    Ziabari, S. Sahand Mohammadi
    Sharpanskykh, Alexei
    MULTI-AGENT-BASED SIMULATION XXIII, MABS 2022, 2023, 13743 : 82 - 94
  • [26] Climate shocks and migration: an agent-based modeling approach
    Entwisle, Barbara
    Williams, Nathalie E.
    Verdery, Ashton M.
    Rindfuss, Ronald R.
    Walsh, Stephen J.
    Malanson, George P.
    Mucha, Peter J.
    Frizzelle, Brian G.
    McDaniel, Philip M.
    Yao, Xiaozheng
    Heumann, Benjamin W.
    Prasartkul, Pramote
    Sawangdee, Yothin
    Jampaklay, Aree
    POPULATION AND ENVIRONMENT, 2016, 38 (01) : 47 - 71
  • [27] Climate shocks and migration: an agent-based modeling approach
    Barbara Entwisle
    Nathalie E. Williams
    Ashton M. Verdery
    Ronald R. Rindfuss
    Stephen J. Walsh
    George P. Malanson
    Peter J. Mucha
    Brian G. Frizzelle
    Philip M. McDaniel
    Xiaozheng Yao
    Benjamin W. Heumann
    Pramote Prasartkul
    Yothin Sawangdee
    Aree Jampaklay
    Population and Environment, 2016, 38 : 47 - 71
  • [28] Agent-based Crowd Simulation Modeling in a Gaming Environment
    Ahmad, Imran Shafiq
    Sun, Songqiao
    Boufama, Boubakeur
    PROCEEDINGS OF 2018 6TH INTERNATIONAL CONFERENCE ON MULTIMEDIA COMPUTING AND SYSTEMS (ICMCS), 2018, : 1 - 6
  • [29] Agent-based modeling of urban energy supply systems
    Wittmann, Tobias
    Bruckner, Thomas
    WIRTSCHAFTSINFORMATIK, 2007, 49 (05): : 352 - 360
  • [30] An agent-based approach to modeling zero energy communities
    Mittal, Anuj
    Krejci, Caroline C.
    Dorneich, Michael C.
    Fickes, David
    SOLAR ENERGY, 2019, 191 : 193 - 204