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Robust volatility forecasts and model selection in financial time series

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Author Info
L. Grossi
G. Morelli ()
Abstract

In order to cope with the stylized facts of financial time series, many models have been proposed inside the GARCH family (e.g. EGARCH, GJR-GARCH, QGARCH, FIGARCH, LSTGARCH) and the stochastic volatility models (e.g. SV). Generally, all these models tend to produce very similar results as concerns forecasting performance. Most of the time it is difficult to choose which is the most appropriate specification. In addition, all these models are very sensitive to the presence of atypical observations. The purpose of this paper is to provide the user with new robust model selection procedures in financial models which downweight or eliminate the effect of atypical observations. The extreme case is when outliers are treated as missing data. In this paper we extend the theory of missing data to the family of GARCH models and show how to robustify the loglikelihood to make it insensitive to the presence of outliers. The suggested procedure enables us both to detect atypical observations and to select the best models in terms of forecasting performance.

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Paper provided by Department of Economics, Parma University (Italy) in its series Economics Department Working Papers with number 2006-SE02.

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Length: 23 pages
Date of creation: 2006
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Handle: RePEc:par:dipeco:2006-se02

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Related research
Keywords: GARCH models extreme value robust estimation

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Find related papers by JEL classification:
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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  2. Rossi, Alessandro & Gallo, Giampiero M., 2006. "Volatility estimation via hidden Markov models," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 203-230, March. [Downloadable!] (restricted)
    Other versions:
  3. Charles, Amelie & Darne, Olivier, 2005. "Outliers and GARCH models in financial data," Economics Letters, Elsevier, vol. 86(3), pages 347-352, March. [Downloadable!] (restricted)
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  12. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March. [Downloadable!] (restricted)
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