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Microeconomic Models for Long-Memory in the Volatility of Financial Time Series

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Author Info
Gilles Teyssière (European Commission, GREQAM)
Alan Kirman

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Abstract

We 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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Publisher Info
Paper 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.

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Date of creation: 04 Jan 2001
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Handle: RePEc:ams:cdws01:5a.4

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  1. TEYSSIERE, Gilles, 2003. "Interaction models for common long-range dependence in asset price volatilities," CORE Discussion Papers 2003026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
  2. De Grauwe, Paul & Grimaldi, Marianna, 2004. "Exchange Rate Puzzles: A Tale of Switching Attractors," Working Paper Series 163, Sveriges Riksbank (Central Bank of Sweden). [Downloadable!]
  3. Jonathan Dark, 2004. "Long memory in the volatility of the Australian All Ordinaries Index and the Share Price Index futures," Monash Econometrics and Business Statistics Working Papers 5/04, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  4. Thomas Lux, 2008. "Stochastic Behavioral Asset Pricing Models and the Stylized Facts," Kiel Working Papers 1426, Kiel Institute for the World Economy. [Downloadable!]
  5. Hommes, C.H.,, 2005. "Heterogeneous Agents Models: two simple examples, forthcoming In: Lines, M. (ed.) Nonlinear Dynamical Systems in Economics, CISM Courses and Lectures, Springer, 2005, pp.131-164," CeNDEF Working Papers 05-01, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
  6. Paul De Grauwe & Pablo Rovira Kaltwasser, 2006. "A Behavioral Finance Model of the Exchange Rate with Many Forecasting Rules," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
  7. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2006,11, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  8. Alfarano, Simone & Lux, Thomas, 2005. "A noise trader model as a generator of apparent financial power laws and long memory," Economics Working Papers 2005,13, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  9. Carl Chiarella & Mauro Gallegati & Roberto Leombruni & Antonio Palestrini, 2003. "Asset Price Dynamics among Heterogeneous Interacting Agents," Computational Economics, Springer, vol. 22(2), pages 213-223, October. [Downloadable!] (restricted)
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  10. Christian Conrad & Menelaos Karanasos & Ning Zeng, 2008. "Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study," Working Papers 0472, University of Heidelberg, Department of Economics, revised Jul 2008. [Downloadable!]
  11. Carl Chiarella & Giulia Iori & Josep Perello, 2007. "The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows," Quantitative Finance Papers 0711.3581, arXiv.org. [Downloadable!]
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  12. Jonathan Dark, 2004. "Bivariate error correction FIGARCH and FIAPARCH models on the Australian All Ordinaries Index and its SPI futures," Monash Econometrics and Business Statistics Working Papers 4/04, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  13. Markus Haas, 2007. "Volatility Components and Long Memory-Effects Revisited," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(2), pages 1411-1411. [Downloadable!] (restricted)
  14. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2005. "Time-variation of higher moments in a financial market with heterogeneous agents : an analytical approach," Economics Working Papers 2005,14, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
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  15. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008,08, Christian-Albrechts-University of Kiel, Department of Economics. [Downloadable!]
  16. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Springer, vol. 26(1), pages 19-49, August. [Downloadable!] (restricted)
  17. Paul De Grauwe & Pablo Rovira Kaltwasser, 2007. "Modeling Optimism and Pessimism in the Foreign Exchange Market," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
  18. repec:att:wimass:192017 is not listed on IDEAS
  19. G. Teyssiere, . "Long-Memory Analysis," Sonderforschungsbereich 373 2000-57, Humboldt Universitaet Berlin.
  20. Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2002. "Evolutionary dynamics in markets with many trader types," CeNDEF Working Papers 02-10, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
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  21. Gaunersdorfer, A. & Hommes, C.H.,, 2005. "A nonlinear structural model for volatility clustering," CeNDEF Working Papers 05-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance. [Downloadable!]
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