Multi-agent modeling of stock market with multiple trading strategies

被引：0
|
作者：
Xu, Chi [1 ]
Zhao, Xiaoyu [1 ]
Chi, Zheru [1 ]
机构：
[1] Hong Kong Polytech Univ, Elect & Informat Engn Dept, Kowloon, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE INFORMATION COMPUTING AND AUTOMATION, VOLS 1-3 | 2008年
关键词：
multi-agent modeling; artificial neural networks; genetic algorithm; fuzzy logic control;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The artificial intelligence and information discovery technologies are applied to construct the intelligent agents for SF-ASM. The moves of agents in the market compose a complicated interaction with a collection of relatively autonomous entities with no central control. The important features in an actual financial market can be quantitatively replicated, in which trading volume volatility and market price dynamics are favorably persistent.
引用
收藏
页码：333 / 336
页数：4
相关论文
共 50 条
  • [21] Deep Q-Learning Market Makers in a Multi-Agent Simulated Stock Market
    Fernandez Vicente, Oscar
    Fernandez Rebollo, Fernando
    Garcia Polo, Francisco Javier
    [J]. ICAIF 2021: THE SECOND ACM INTERNATIONAL CONFERENCE ON AI IN FINANCE, 2021,
  • [22] Simulation of a trading multi-agent system
    Mariano, P
    Pereira, A
    Correia, L
    Ribeiro, R
    Abramov, V
    Szirbik, N
    Goossenaerts, J
    Marwala, T
    De Wilde, P
    [J]. 2001 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: E-SYSTEMS AND E-MAN FOR CYBERNETICS IN CYBERSPACE, 2002, : 3378 - 3384
  • [23] Multi-agent framework for distributed trading
    Sabaz, Dorian
    Alibhai, Zafeer
    Gruver, William A.
    [J]. DIS 2006: IEEE WORKSHOP ON DISTRIBUTED INTELLIGENT SYSTEMS: COLLECTIVE INTELLIGENCE AND ITS APPLICATIONS, PROCEEDINGS, 2006, : 237 - +
  • [24] Ontological Trading in a Multi-agent System
    Criado, J.
    Padilla, N.
    Iribarne, L.
    Asensio, J. A.
    Munoz, F.
    [J]. TRENDS IN PRACTICAL APPLICATIONS OF AGENTS AND MULTIAGENT SYSTEMS, 2010, 71 : 321 - 329
  • [25] Deep Reinforcement Learning based Multi-Agent Collaborated Network for Distributed Stock Trading
    Kim, Jung-Jae
    Cha, Si-Ho
    Cho, Kuk-Hyun
    Ryu, Minwoo
    [J]. INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING, 2018, 11 (02): : 11 - 20
  • [26] Performance evaluation of trading strategies in multi-agent systems - Case of A-Trader
    Korczak, Jerzy
    Hernes, Marcin
    [J]. PROCEEDINGS OF THE 2018 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS), 2018, : 839 - 844
  • [27] Modeling Multi-agent Interaction between Labor Market Participants
    Malafeyev, Oleg
    Zaitseva, Irina
    Abdullaev, Jabir
    Bondar, Victoria
    Skvortsova, Olga
    [J]. INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019, 2020, 2293
  • [28] Labor Market in Multi-agent Environment Modeling Virtual Economy
    Blecha, Petr
    [J]. HRADEC ECONOMIC DAYS, PT I, 2018, 2018, 8 : 114 - 120
  • [29] Multi-agent market modeling based on analysis of consumer lifestyles
    Kito, Tomomi
    Fujita, Kousuke
    Takenaka, Takeshi
    Ueda, Kanji
    [J]. MANUFACTURING SYSTEMS AND TECHNOLOGIES FOR THE NEW FRONTIER, 2008, : 507 - +
  • [30] Multi-agent FX-market modeling by neural networks
    Zimmermann, HG
    Grothmann, R
    Neuneier, R
    [J]. OPERATIONS RESEARCH PROCEEDINGS 2001, 2002, : 413 - 420
12345