EVOLUTION AND TIME HORIZONS IN AN AGENT-BASED STOCK MARKET

Blake Lebaron ()

Macroeconomic Dynamics, 2001, vol. 5, issue 02, 225-254

Abstract: Recent research has shown the importance of time horizons in models of learning in finance. The dynamics of how agents adjust to believe that the world around them is stationary may be just as crucial in the convergence to a rational expectations equilibrium as getting parameters and model specifications correct in the learning process. This paper explores the process of this evolution in learning and time horizons in a simple agent-based financial market. The results indicate that, although the simple model structure used here replicates usual rational expectations results with long-horizon agents, the route to evolving a population of both long- and short-horizon agents to long horizons alone may be difficult. Furthermore, populations with both short- and long-horizon agents increase return variability, and leave patterns in volatility and trading volume similar to actual financial markets.

Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (54)

Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)

Related works:
Working Paper: Evolution and Time Horizons in an Agent-Based Stock Market (1999)
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:cup:macdyn:v:5:y:2001:i:02:p:225-254_01

Access Statistics for this article

More articles in Macroeconomic Dynamics from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().