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Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility

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  • Teräsvirta, Timo

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Zhao, Zhenfang

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

Financial 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 GARCH, EGARCH and 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 Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 662.

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Length: 51 pages
Date of creation: 01 Jun 2007
Date of revision: 05 Jun 2007
Publication status: Published as Teräsvirta, Timo and Zhenfang Zhao, 'Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility' in Applied Financial Economics, 2011, pages 67-94.
Handle: RePEc:hhs:hastef:0662

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Keywords: GARCH; EGARCH; ARSV; extreme observations; autocorrelation function; kurtosis; robust measure; confidence region.;

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Cited by:
  1. 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.
  2. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
  3. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effect in Financial Returns," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00973922, HAL.
  4. 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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