Heterogeneous speculators and stock market dynamics: a simple agent-based computational model

Noemi Schmitt, Ivonne Schwartz and Frank Westerhoff

The European Journal of Finance, 2022, vol. 28, issue 13-15, 1263-1282

Abstract: We propose a simple agent-based computational model in which speculators’ trading behavior may cause bubbles and crashes, excess volatility, serially uncorrelated returns, fat-tailed return distributions and volatility clustering, thereby replicating five important stylized facts of stock markets. Since each speculator bets on his own (technical and fundamental) trading signals, stock prices are excessively volatile and oscillate erratically around their fundamental value. However, speculators’ heterogeneity occasionally vanishes, e.g. due to panic-induced herding behavior, yielding extreme returns. Lasting regimes with high volatility originate from the fact that speculators extract stronger trading signals out of past stock price movements when stock prices fluctuate strongly. Simulations furthermore suggest that circuit breakers may be an effective tool to combat financial market turbulences.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/1351847X.2020.1832553 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Heterogeneous speculators and stock market dynamics: A simple agent-based computational model (2020)
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:taf:eurjfi:v:28:y:2022:i:13-15:p:1263-1282

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/REJF20

DOI: 10.1080/1351847X.2020.1832553

Access Statistics for this article

The European Journal of Finance is currently edited by Chris Adcock

More articles in The European Journal of Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().