Microeconomic Models for Long Memory in the Volatility of Financial Time Series
AbstractWe 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 Teyssière (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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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 5 (2002)
Issue (Month): 4 (January)
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Web page: http://www.degruyter.com
Other versions of this item:
- Gilles Teyssière & Alan Kirman, 2001. "Microeconomic Models for Long-Memory in the Volatility of Financial Time Series," CeNDEF Workshop Papers, January 2001 5A.4, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- KIRMAN, Alan & TEYSSIÈRE, Gilles, . "Microeconomic models for long memory in the volatility of financial time series," CORE Discussion Papers RP -1593, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Alan P. Kirman, Gilles Teyssiere, 2001. "Microeconomic Models for Long-Memory in the Volatility of Financial Time Series," Computing in Economics and Finance 2001 221, Society for Computational Economics.
- KIRMAN, Alan & TEYSSIÈRE, Gilles, 2002. "Microeconomic models for long-memory in the volatility of financial time series," CORE Discussion Papers 2002056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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