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Asset Price Dynamics in a Financial Market with Heterogeneous Trading Strategies and Time Delays

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  • Giuseppe Garofalo
  • Alessandro Sansone

Abstract

In this paper we present a continuous time dynamical model of heterogeneous agents interacting in a financial market where transactions are cleared by a market maker. The market is composed of fundamentalist, trend following and contrarian agents who process information from the market with different time delays. Each class of investor is characterized by path dependent risk aversion. We also allow for the possibility of evolutionary switching between trend following and contrarian strategies. We find that the system shows periodic, quasi-periodic and chaotic dynamics as well as synchronization between technical traders. Furthermore, the model is able to generate time series of returns that exhibit statistical properties similar to those of the S&P500 index, which is characterized by excess kurtosis, volatility clustering and long memory.

Suggested Citation

  • Giuseppe Garofalo & Alessandro Sansone, 2005. "Asset Price Dynamics in a Financial Market with Heterogeneous Trading Strategies and Time Delays," Working Papers in Public Economics 88, University of Rome La Sapienza, Department of Economics and Law.
    • Handle: RePEc:sap:wpaper:wp88
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    Cited by:

    1. Raquel Almeida Ramos & Federico Bassi & Dany Lang, 2020. "Bet against the trend and cash in profits," CEPN Working Papers halshs-02956879, HAL.
    2. Federico Bassi & Raquel Ramos & Dany Lang, 2023. "Bet against the trend and cash in profits: An agent-based model of endogenous fluctuations of exchange rates," Journal of Evolutionary Economics, Springer, vol. 33(2), pages 429-472, April.
    3. Ho, Kin-Yip & Zheng, Lin & Zhang, Zhaoyong, 2012. "Volume, volatility and information linkages in the stock and option markets," Review of Financial Economics, Elsevier, vol. 21(4), pages 168-174.
    4. Wan, Jer-Yuh & Kao, Chung-Wei, 2009. "Evidence on the contrarian trading in foreign exchange markets," Economic Modelling, Elsevier, vol. 26(6), pages 1420-1431, November.
    5. Tokár, T. & Horváth, D., 2012. "Market inefficiency identified by both single and multiple currency trends," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5620-5627.
    6. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    7. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.

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    More about this item

    Keywords

    Dynamic asset pricing; Heterogeneous agents; Complex dynamics; Strange attractors; Chaos; Intermittency; Stock market dynamics; Synchronization.;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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