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Why a Simple Herding Model May Generate the Stylized Facts of Daily Returns: Explanation and Estimation

  • 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’sThe 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.show moreshow less

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Metadaten
Institutes:Fakultät Sozial- und Wirtschaftswissenschaften / Lehrstuhl für Volkswirtschaftslehre, insbesondere Wirtschaftspolitik
Author:Reiner Franke, Frank Westerhoff
Contributer:Felix Stübben
Publishing Institution:BERG (Bamberg Economic Research Group)
Place of publication:Bamberg
Publisher:opus
Year of publication:2012
Pages / Size:33 S. : graph. Darst.
Collections (Serial Number):BERG working paper series (83)
Year of first publication:2011
Source/Other editions:zuerst erschienen im BERG-Verlag, 2011
To order a print copy:http://www.uni-bamberg.de/vwl/forschung/wps/
SWD-Keyword:Capital-Asset-Pricing Modell ; Mehragentensystem ; Volabilität ; Online-Publikation
Keywords:Structural stochastic volatility; method of simulated moments; autocorrelation pattern; fat tails; bootstrapped p-values
DDC-Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
RVK-Classification:QK 622
URN:urn:nbn:de:bvb:473-opus4-24194
ISBN:978-3-931052-93-5
Document Type:Working paper
Language:English
Publishing Institution:Otto-Friedrich-Universität Bamberg
Release Date:2013/01/25