Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

被引:2
|
作者
Kim, Minsung [1 ]
Kim, Minki [2 ]
机构
[1] Korea Adv Inst Sci & Technol, Grad Sch Innovat & Technol Management, Taejon 305701, South Korea
[2] Korea Adv Inst Sci & Technol, Grad Sch Management, Seoul, South Korea
来源
PLOS ONE | 2014年 / 9卷 / 04期
关键词
DYNAMICS;
D O I
10.1371/journal.pone.0093661
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.
引用
收藏
页数:7
相关论文
共 50 条
  • [31] A builder's guide to agent-based financial markets
    LeBaron, Blake
    QUANTITATIVE FINANCE, 2001, 1 (02) : 254 - 261
  • [32] Effects of Modularity in Financial Markets on an Agent-based Model
    Kim, Hongseok
    Kim, Seunghwan
    Oh, Gabjin
    JOURNAL OF THE KOREAN PHYSICAL SOCIETY, 2012, 60 (04) : 599 - 603
  • [33] Interactive inversion of financial markets agent-based models
    Ashburn, T
    Bonabeau, E
    CEC2004: PROCEEDINGS OF THE 2004 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2004, : 522 - 529
  • [34] AGENT-BASED MODELING OF ELECTRIC POWER MARKETS
    Macal, Charles
    Thimmapuram, Prakash
    Koritarov, Vladimir
    Conzelmann, Guenter
    Veselka, Thomas
    North, Michael
    Mahalik, Matthew
    Botterud, Audun
    Cirillo, Richard
    PROCEEDINGS OF THE 2014 WINTER SIMULATION CONFERENCE (WSC), 2014, : 276 - 287
  • [35] Agent-based modeling approach for group polarization behavior considering conformity and network relationship strength
    Zhang, Yizhou
    Wang, Yibao
    Chen, Tinggui
    Shi, Jiawen
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2020, 32 (14):
  • [36] A Feature-Based Approach For Group-Wise Grid Map Registration
    Rapp, Matthias
    Giese, Tilmann
    Hahn, Markus
    Dickmann, Juergen
    Dietmayer, Klaus
    2015 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, 2015, : 511 - 516
  • [37] Agent-based model with multi-level herding for complex financial systems
    Jun-Jie Chen
    Lei Tan
    Bo Zheng
    Scientific Reports, 5
  • [38] Agent-Based Modeling for Complex Financial Systems
    Paulin, James
    Calinescu, Anisoara
    Wooldridge, Michael
    IEEE INTELLIGENT SYSTEMS, 2018, 33 (02) : 74 - 82
  • [39] Agent-based model with multi-level herding for complex financial systems
    Chen, Jun-Jie
    Tan, Lei
    Zheng, Bo
    SCIENTIFIC REPORTS, 2015, 5
  • [40] 3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model
    Lee, Sunyoung
    Lee, Keun
    JOURNAL OF ECONOMIC INTERACTION AND COORDINATION, 2021, 16 (02) : 359 - 380