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Why a simple herding model may generate the stylized facts of daily returns: Explanation and estimation

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  • Franke, Reiner
  • Westerhoff, Frank

Abstract

The paper proposes an elementary agent-based asset pricing model that, invoking the two trader types of fundamentalists and chartists, comprises four features: (i) price determination by excess demand; (ii) a herding mechanism that gives rise to a macroscopic adjustment equation for the market fractions of the two groups; (iii) a rush towards fundamentalism when the price misalignment becomes too large; and (iv) a stronger noise component in the demand per chartist trader than in the demand per fundamentalist trader, which implies a structural stochastic volatility in the returns. Combining analytical and numerical methods, the interaction between these elements is studied in the phase plane of the price and a majority index. In addition, the model is estimated by the method of simulated moments, where the choice of the moments reflects the basic stylized facts of the daily returns of a stock market index. A (parametric) bootstrap procedure serves to set up an econometric test to evaluate the model's goodness-of-fit, which proves to be highly satisfactory. The bootstrap also makes sure that the estimated structural parameters are well identified.

Suggested Citation

  • Franke, Reiner & Westerhoff, Frank, 2011. "Why a simple herding model may generate the stylized facts of daily returns: Explanation and estimation," BERG Working Paper Series 83, Bamberg University, Bamberg Economic Research Group.
  • Handle: RePEc:zbw:bamber:83
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    References listed on IDEAS

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    Cited by:

    1. Fabio Tramontana, 2013. "The role of cognitively biased imitators in a small scale agent-based financial market," DEM Working Papers Series 029, University of Pavia, Department of Economics and Management.

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    More about this item

    Keywords

    structural stochastic volatility; method of simulated moments; autocorrelation pattern; fat tails; bootstrapped p-values;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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