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Temporal Aggregation of Volatility Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Nour Meddahi ()
Éric Renault ()
In this paper, we consider temporal aggregation of volatility models. We introduce a semiparametric class of volatility models termed square-root stochastic autoregressive volatility (SR-SARV) and characterized by an autoregressive dynamic of the stochastic variance. Our class encompasses the usual GARCH models and various asymmetric GARCH models. Moreover, our stochastic volatility models are characterized by observable multiperiod conditional moment restrictions. The SR-SARV class is a natural extension of the weak GARCH models. Our extension has four advantages: i) we do not assume that the fourth moment is finite; ii) we allow for asymmetries (skewness, leverage effect) that are excluded by the weak GARCH models; iii) we derive conditional moment restrictions which are useful for non-linear inference; iv) our framework allows us to study temporal aggregation of IGARCH models and non-linear models such as EGARCH and Exponential SV in discrete and continuous time. Dans cet article, nous considérons l'agrégation temporelle des modèles de volatilité. Nous introduisons une classe de modèles de volatilité semi-paramétrique dénommée SR-SARV et caractérisée par une variance stochastique ayant une dynamique autorégressive. Notre classe contient les modèles GARCH usuels ainsi que plusieurs variantes asymétriques. De plus, nos modèles à volatilité stochastique sont caractérisés par des moments conditionnels observables et à plusieurs horizons. La classe des modèles SR-SARV est une généralisation naturelle des modèles GARCH faibles. Notre extension présente quatre avantages: i) nous ne supposons pas que le moment d'ordre quatre est fini; ii) nous permettons des asymétries (de type skewness et effet de levier) qui sont exclues par les modèles GARCH faibles; iii) nous dérivons des restrictions sur des moments conditionnels utiles pour l'inférence non-linéaire; iv) notre cadre de travail nous permet d'étudier l'agrégation temporelle des modèles IGARCH ainsi que des modèles non linéaires comme le modèle EGARCH et les modèles exponentiels à volatilité stochastique en temps discret et continu.
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Date of creation: 01 Jul 2000Date of revision:
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Keywords: GARCH ; stochastic volatility ; state-space ; SR-SARV ; aggregation ; asset returns ; diffusion processes ; infinitesimal generator ; Eigenfunctions ; GARCH ; volatilité stochastique ; espace-état ; SR-SARV ; agrégation ; rendements d'actifs ; processus de diffusion ; générateur infinitésimal ; fonctions propres ; Other versions of this item:
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Nour Meddahi, 2001.
"A Theoretical Comparison Between Integrated andRealized Volatilities / A Theoretical Comparison Between Integrated and Realized Volatilities ,"
CIRANO Working Papers
2001s-71, CIRANO.
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Peter Christoffersen & Francis X. Diebold, 2002.
"Financial Asset Returns, Market Timing, and Volatility Dynamics ,"
CIRANO Working Papers
2002s-02, CIRANO.
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Nour Meddahi, 2001.
"An Eigenfunction Approach for Volatility Modeling ,"
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2001s-70, CIRANO.
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René Garcia & Eric Ghysels & Éric Renault, 2004.
"The Econometrics of Option Pricing ,"
CIRANO Working Papers
2004s-04, CIRANO.
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Nour Meddahi, 2002.
"A theoretical comparison between integrated and realized volatility ,"
Journal of Applied Econometrics ,
John Wiley & Sons, Ltd., vol. 17(5), pages 479-508.
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Neil Shephard & Ole Barndorff-Nielsen, 2001.
"Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models ,"
Economics Series Working Papers
071, University of Oxford, Department of Economics.
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Ole E. Barndorff-Nielsen & Neil Shephard, 2000.
"Econometric analysis of realised volatility and its use in estimating stochastic volatility models ,"
Economics Papers
2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.
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"Econometric analysis of realized volatility and its use in estimating stochastic volatility models ,"
Journal Of The Royal Statistical Society Series B ,
Royal Statistical Society, vol. 64(2), pages 253-280.
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Tim Bollerslev & Hao Zhou, 2001.
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Finance and Economics Discussion Series
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