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 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.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 221.
Date of creation: 01 Apr 2001
Date of revision:
Contact details of provider:
Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
More information through EDIRC
long-memory; microeconomic models; field effects;
Other versions of this item:
- Alan Kirman & Gilles TeyssiÃ¨re, 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.
- 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
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2001-05-02 (All new papers)
- NEP-FIN-2001-05-02 (Finance)
- NEP-MIC-2001-05-02 (Microeconomics)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statistics
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.