Interaction models for common long-range dependence in asset price volatilities

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Interaction models for common long-range dependence in asset price volatilities

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TEYSSIERE, Gilles

Abstract

We consider a class of microeconomic models with interacting agents which replicate the main properties of asset prices time series: nonlinearities i levels and common degree of long-memory in the volatilities and co-volatilities of multivariate time series. For these models, longrange dependence in asset price volatility is the consequence of swings in opinions and herding behavior of market participants, which generate switches in the heteroskedastic structure of asset prices. Thus, the observed long-memory in asset prices volatility might be the outcome of a change-point in the conditional variance process, a conclusion supported by a wavelet analysis of the volatility series. This explains why volatility processes share only the properties of the second moments of long-memory processes, but not the properties of the first moments.

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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 2003026.

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Date of creation: 01 Feb 2003
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Handle: RePEc:cor:louvco:2003026

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
D40 - Microeconomics - - Market Structure and Pricing - - - General

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Other versions:
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Other versions:
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KIRMAN, Alan & TEYSSIéRE, 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). [Downloadable!]
Other versions:
- 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.
- 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.
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Other versions:
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation, Yale University. [Downloadable!]
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.

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