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Microeconomic Models for Long Memory in the Volatility of Financial Time Series

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Author Info
Alan Kirman (Institut Universitaire de France & GREQAM)
Gilles Teyssière (GREQAM & CORE)

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Abstract

We show that a class of microeconomic behavioral models with interacting agents, derived from Kirman (1991) and Kirman (1993), can replicate the empirical long-memory properties of the two first-conditional moments of financial time series. The essence of these models is that the forecasts and thus the desired trades of the individuals in the markets are influenced, directly or indirectly, by those of the other participants. These "field effects" generate "herding" behavior that affects the structure of the asset price dynamics. The series of returns generated by these models display the same empirical properties as financial returns: returns are I (0), the series of absolute and squared returns display strong dependence, and the series of absolute returns do not display a trend. Furthermore, this class of models is able to replicate the common long-memory properties in the volatility and covolatility of financial time series revealed by Teyssire (1997, 1998a). These properties are investigated by using various model-independent tests and estimators, that is, semiparametric and nonparametric, introduced by Lo (1991), Kwiatkowski et al. (1992), Robinson (1995), Lobato and Robinson (1998), and Giraitis et al. (2000, forthcoming). The relative performance of these tests and estimators for long memory in a nonstandard data-generating process is then assessed.

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Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 5 (2002)
Issue (Month): 4 ()
Pages: 1083-1083
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Related research
Keywords: long memory microeconomic models field effects semiparametric tests conditional

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References listed on IDEAS
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. De Grauwe, Paul & Grimaldi, Marianna, 2004. "Exchange Rate Puzzles: A Tale of Switching Attractors," Working Paper Series 163, Sveriges Riksbank (Central Bank of Sweden). [Downloadable!]
  2. Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  3. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Kiel Working Papers 1426, Kiel Institute for the World Economy. [Downloadable!]
  4. Hommes, C.H.,, 2005. "Heterogeneous Agents Models: two simple examples, forthcoming In: Lines, M. (ed.) Nonlinear Dynamical Systems in Economics, CISM Courses and Lectures, Springer, 2005, pp.131-164," CeNDEF Working Papers 05-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
  5. Paul De Grauwe & Pablo Rovira Kaltwasser, 2006. "A Behavioral Finance Model of the Exchange Rate with Many Forecasting Rules," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH. [Downloadable!]
  6. Lux, Thomas, 2006. "Financial power laws : empirical evidence, models, and mechanism," Economics working papers 2006,12, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
  7. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics working papers 2006,11, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  8. Alfarano, Simone & Lux, Thomas, 2005. "A Noise Trader Model as a Generator of Apparent Financial Power Laws and Long Memory," Economics working papers 2005,13, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  9. Christian Conrad & Menelaos Karanasos & Ning Zeng, 2008. "Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study," Working Papers 0472, University of Heidelberg, Department of Economics, revised Jul 2008. [Downloadable!]
  10. Jonathan Dark, 2004. "Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures," Monash Econometrics and Business Statistics Working Papers 4/04, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  11. Markus Haas, 2007. "Volatility Components and Long Memory-Effects Revisited," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(2), pages 1411-1411. [Downloadable!] (restricted)
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  13. Lux, Thomas, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Economics working papers 2008,08, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
  14. Paul De Grauwe & Pablo Rovira Kaltwasser, 2007. "Modeling Optimism and Pessimism in the Foreign Exchange Market," CESifo Working Paper Series CESifo Working Paper No. , CESifo GmbH. [Downloadable!]
  15. repec:att:wimass:192017 is not listed on IDEAS
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    Other versions:
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