Linking Agent-Based Models and Stochastic Models of Financial Markets

Proceedings of the National Academy of Sciences 109, 8388-8393 (2012)

6 Pages Posted: 18 Dec 2012

See all articles by Ling Feng

Ling Feng

Boston University

Baowen Li

National University of Singapore (NUS)

Boris Podobnik

Boston University; University of Rijeka

Tobias Preis

Data Science Lab, Behavioural Science, Warwick Business School; The Alan Turing Institute

H. Eugene Stanley

Boston University - Center for Polymer Studies

Date Written: May 29, 2012

Abstract

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Keywords: Complex Systems, Power Law, Scaling Laws, Agent-Based Models, Stochastic Processes

JEL Classification: A10, B40, C10, C20, C22, C53, C90, D70, D79, D83, J10, J11, O40, O47

Suggested Citation

Feng, Ling and Li, Baowen and Podobnik, Boris and Preis, Tobias and Stanley, H. Eugene, Linking Agent-Based Models and Stochastic Models of Financial Markets (May 29, 2012). Proceedings of the National Academy of Sciences 109, 8388-8393 (2012), Available at SSRN: https://ssrn.com/abstract=2190512

Ling Feng

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

Baowen Li

National University of Singapore (NUS) ( email )

1E Kent Ridge Road
NUHS Tower Block Level 7
Singapore, 119228
Singapore

Boris Podobnik

Boston University ( email )

University of Rijeka ( email )

Rijeka, 51000
Croatia

Tobias Preis (Contact Author)

Data Science Lab, Behavioural Science, Warwick Business School ( email )

University of Warwick
Coventry, CV4 7AL
United Kingdom

HOME PAGE: http://www.tobiaspreis.com

The Alan Turing Institute ( email )

British Library, 96 Euston Road
96 Euston Road
London, NW12DB
United Kingdom

HOME PAGE: http://https://www.turing.ac.uk/people/researchers/tobias-preis

H. Eugene Stanley

Boston University - Center for Polymer Studies ( email )

Boston, MA 02215
United States

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