Can Trend Followers Survive in the Long-Run? Insights from Agent-Based Modeling

Xue-Zhong He, Philip Hamill, Youwie Li

    Research output: Chapter in Book/Report/Conference proceedingChapter

    1 Citation (Scopus)

    Abstract

    This paper uses a simple stochastic market fraction (MF) asset pric-ing model to investigate market dominance, profitability, and how traders adoptingfundamental analysis or trend following strategies can survive under various marketconditions in the long/short-run. This contrasts with the modern theory of financewhich relies on the paradigm of utility maximizing representative agents and ratio-nal expectations assumptions which some contemporary theorists regard as extreme.This school of thought would predict that trend followers will be driven out of themarkets in the long-run. Our analysis shows that in a MF framework this is notnecessarily the case and that trend followers can survive in the long-run.
    Original languageEnglish
    Title of host publicationNatural Computing in Computational Finance
    EditorsAnthony Brabazon, Michael O'Neill
    PublisherSpringer
    Pages253-269
    ISBN (Print)978-3-540-77476-1
    Publication statusPublished - 2008

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    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 (pp. 253-269). Springer.