Identification of asymmetric conditional heteroscedasticity in the presence of outliers

The identification of asymmetric conditional heteroscedasticity is often based on sample cross-correlations between past and squared observations. In this paper we analyse the effects of outliers on these cross-correlations and, consequently, on the identification of asymmetric volatilities.We showt...

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Bibliographic Details
Published in:SERIEs : journal of the Spanish Economic Association 2016-03, Vol.7 (1), p.179-201
Main Authors: Carnero, M. Angeles, Pérez, Ana, Ruiz, Esther
Format: Article
Language:English
Subjects:
Correlation analysis
Cross-correlations
Economic Policy
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
EGARCH
Estimating techniques
Leverage effect
Microeconomics
Monte Carlo simulation
Original Article
Public Finance
Robust correlations
Studies
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Summary:The identification of asymmetric conditional heteroscedasticity is often based on sample cross-correlations between past and squared observations. In this paper we analyse the effects of outliers on these cross-correlations and, consequently, on the identification of asymmetric volatilities.We showthat, as expected, one isolated big outlier biases the sample cross-correlations towards zero and hence could hide true leverage effect. Unlike, the presence of two ormore big consecutive outliers could lead to detecting spurious asymmetries or asymmetries of the wrong sign. We also address the problem of robust estimation of the cross-correlations by extending some popular robust estimators of pairwise correlations and autocorrelations. Their finite sample resistance against outliers is compared through Monte Carlo experiments. Situations with isolated and patchy outliers of different sizes are examined. It is shown that a modified Ramsay-weighted estimator of the cross-correlations outperforms other estimators in identifying asymmetric conditionally heteroscedastic models. Finally, the results are illustrated with an empirical application.
ISSN:1869-4195
1869-4187
1869-4195
DOI:10.1007/s13209-015-0131-4