Microeconomic models for long memory in the volatility of financial time series
AbstractWe 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 the individuals in the markets 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 models is able to replicate the common long-memory properties in the volatility and co-volatility of financial time series, uncovered by TeyssiÃ¨re (1997, 1998). These properties are investigated by using various model independent tests and estimators, i.e., semiparametric and nonparametric, introduced by Lo (1991), Kwiatkowski, Phillips, Schmidt and Shin (1992), Robinson (1995), Lobato adn Robinson (1998), Giraitis, Kokoszka and Leipus (1999), Giraitis, Kokoszka, Leipus and TeyssiÃ¨re (1999). The relative performance of these tests and estimators for long-memory in an non-standard data generating process is then assessed.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers RP with number -1593.
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Note: In : Studies in Nonlinear Dynamics and Econometrics, 5(4), 281-302, 2002
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Other versions of this item:
- Kirman Alan & Teyssière Gilles, 2002. "Microeconomic Models for Long Memory in the Volatility of Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(4), pages 1-23, January.
- Gilles TeyssiÃ¨re & Alan Kirman, 2001. "Microeconomic Models for Long-Memory in the Volatility of Financial Time Series," CeNDEF Workshop Papers, January 2001, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance 5A.4, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
- KIRMAN, Alan & TEYSSIÃˆRE, Gilles, 2002. "Microeconomic models for long-memory in the volatility of financial time series," CORE Discussion Papers, UniversitÃ© catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2002056, UniversitÃ© 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, Society for Computational Economics 221, Society for Computational Economics.
- 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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