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

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  • Alan P. Kirman, Gilles Teyssiere

Abstract

We show that a class of microeconomic behavioral models with interacting agents, introduced by Kirman (1991,1993), 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 individuals are influenced, directly or indirectly by those of the other participants. These "field effects" generate herding behaviour which affects the structure of the asset price dynamics. The series of squared returns and absolute returns generated by these models display long-memory, while the returns are uncorrelated. Furthermore, this class of modesl is also able to replicate the common long-memory properties in the volatility and co-volatility of financial time-series uncovered by Teyssiere (1997,1998). These properties are investigated by using various semiparametric and non-parametric tests and estimators.

Suggested Citation

  • 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.
    • Handle: RePEc:sce:scecf1:221
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    JEL classification:

    • 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; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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