Heterogeneous agent models in financial markets: A nonlinear dynamics approach
Xuezhong (Tony) He (),
Youwei Li and
Min Zheng
International Review of Financial Analysis, 2019, vol. 62, issue C, 135-149
Abstract:
Studies on financial markets have accumulated consistent evidences of stylized facts and anomalies, which can be characterized by stochastic switching among different co-existing market states but yet difficult to reconcile with traditionally rational expectation theory. When agents are heterogeneous and boundedly rational, recent developments on the role of the adaptive behavior of interacting heterogeneous agents in financial markets have provided a nonlinear dynamics channel to such co-existence of different market states, shedding light into these stylized facts and anomalies. This survey focuses on the nonlinear dynamics approach to model the feedback of evolutionary dynamics of heterogeneous agents and to characterize the underlying mechanisms of the stylized facts and anomalies in financial markets, of which the authors and several coauthors have contributed in several papers.
Keywords: Stylized facts; Anomalies; Heterogeneous beliefs; Nonlinear dynamics; Stability and bifurcation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521918301418
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:62:y:2019:i:c:p:135-149
DOI: 10.1016/j.irfa.2018.11.016
Access Statistics for this article
International Review of Financial Analysis is currently edited by B.M. Lucey
More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().