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 Teyssière (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 Teyssière (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 Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Workshop Papers, January 2001 with number 5A.4.
Date of creation: 04 Jan 2001
Date of revision:
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Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands
Phone: + 31 20 525 52 58
Fax: + 31 20 525 52 83
Web page: http://www.fee.uva.nl/cendef/
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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.
- 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, . "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).
- 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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