Can trend followers survive in the long-run? Insights from agent-based modeling

He, Xue Zhong; Hamill, Philip; Li, Youwei

Abstract

This chapter uses a simple stochastic market fraction (MF) asset pricing model to investigate market dominance, profitability, and how traders adopting fundamental analysis or trend following strategies can survive under various market conditions in the long/short-run. This contrasts with the modern theory of finance which relies on the paradigm of utility maximizing representative agents and rational expectations assumptions which some contemporary theorists regard as extreme. This school of thought would predict that trend followers will be driven out of the markets in the long-run. Our analysis shows that in a MF framework this is not necessarily the case and that trend followers can survive in the long-run.

Citation

He, X. Z., Hamill, P., & Li, Y. (2008). Can trend followers survive in the long-run? Insights from agent-based modeling. In A. Brabazon, & M. O'Neill (Eds.), Natural Computing in Computational Finance (253-269). Berlin, Heidelberg: Springer Verlag. https://doi.org/10.1007/978-3-540-77477-8_14

• Publication Date: Jun 10, 2008
• Deposit Date: Mar 19, 2019
• Journal: Natural Computing in Computational Finance; Studies in Computational Intelligence
• Print ISSN: 1860-949X
• Publisher: Springer Verlag
• Pages: 253-269
• Series Title: Studies in computational intelligence
• Series Number: 100
• Book Title: Natural Computing in Computational Finance
• Chapter Number: 14
• ISBN: 9783540774761
• DOI: https://doi.org/10.1007/978-3-540-77477-8_14
• Keywords: Market price; Trading strategy; Risky asset; Market maker; Asset price model
• Public URL: https://hull-repository.worktribe.com/output/1390130
• Publisher URL: https://link.springer.com/chapter/10.1007%2F978-3-540-77477-8_14