Microeconomic models for long-memory in the volatility of financial time series
Abstract
We show that a class of microeconomic behavioral models with interacting agents, derived from 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 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, while 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 co-volatility of financial time series, revealed by TeyssiDownload Info
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Paper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2002056.Length:
Date of creation: 00 Mar 2002
Date of revision:
Handle: RePEc:cor:louvco:2002056
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Related research
Keywords: long-memory; microeconomic models; field effects; semiparametric tests; conditional heteroskedasticity;Other versions of this item:
- Alan Kirman & Gilles Teyssière, 2002. "Microeconomic Models for Long Memory in the Volatility of Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(4), pages 3.
- 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.
- 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.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- D40 - Microeconomics - - Market Structure and Pricing - - - General
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