Stylized facts of return series, robust estimates and three popular models of volatility
AbstractFinancial return series of sufficiently high frequency display stylized facts such as volatility clustering, high kurtosis, low starting and slow-decaying autocorrelation function of squared returns and the so-called Taylor effect. In order to evaluate the capacity of volatility models to reproduce these facts, we apply both standard and robust measures of kurtosis and autocorrelation of squares to first-order Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Exponential GARCH (EGARCH) and Autoregressive Stochastic Volaticity (ARSV) models. Robust measures provide a fresh view of stylized facts, which is useful because many financial time series can be viewed as being contaminated with outliers.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Financial Economics.
Volume (Year): 21 (2011)
Issue (Month): 1-2 ()
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Web page: http://www.tandfonline.com/RAFE20
Other versions of this item:
- Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 05 Jun 2007.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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- Amado, Cristina & Teräsvirta, Timo, 2013.
"Modelling volatility by variance decomposition,"
Journal of Econometrics,
Elsevier, vol. 175(2), pages 142-153.
- Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
- Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," CREATES Research Papers 2011-01, School of Economics and Management, University of Aarhus.
- Amado, Cristina & Teräsvirta, Timo, 2008.
"Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure,"
Working Paper Series in Economics and Finance
691, Stockholm School of Economics.
- Cristina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," NIPE Working Papers 03/2008, NIPE - Universidade do Minho.
- Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, School of Economics and Management, University of Aarhus.
- Lorenzo Pascual & Esther Ruiz & Diego Fresoli, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," Statistics and Econometrics Working Papers ws113426, Universidad Carlos III, Departamento de Estadística y Econometría.
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