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Assessment of Local Influence in GARCH Processes

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Author Info
Xibin Zhang

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Abstract

This paper investigates the problem of assessing local influence of small perturbations in GARCH processes. First, we examine the local influence on the Lagrange multiplier (LM) statistic. Second, we assess the local influence on the pseudo-likelihood of the GARCH model. We find that short patches of high volatility observations that have a strong influence on the LM statistic may not necessarily be influential on the pseudo-likelihood. This is mainly due to the fact that the effects of high volatility could be incorporated through GARCH modeling. An empirical example is presented to illustrate the effectiveness of the proposed methods. It is interesting to note that observations which have a very strong influence on the LM statistic are far less influential on the GARCH pseudo-likelihood, suggesting that under the GARCH model they should not be regarded as outliers. Copyright 2004 Blackwell Publishing Ltd.

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Publisher Info
Article provided by Blackwell Publishing in its journal Journal of Time Series Analysis.

Volume (Year): 25 (2004)
Issue (Month): 2 (03)
Pages: 301-313
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Handle: RePEc:bla:jtsera:v:25:y:2004:i:2:p:301-313

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  1. M. Angeles Carnero & Daniel Peña & Esther Ruiz, 2004. "Spurious And Hidden Volatility," Statistics and Econometrics Working Papers ws042007, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
    Other versions:
  2. Xibin Zhang & Maxwell L. King, 2002. "Influence Diagnostics in GARCH Processes," Monash Econometrics and Business Statistics Working Papers 19/02, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
  3. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy). [Downloadable!]
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This page was last updated on 2009-11-22.


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