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http://hdl.handle.net/10071/19981
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Title: Detecting outliers in multivariate volatility models: a wavelet procedure
Authors: Grané, A.
Martín-Barragan, B.
Veiga, H.
Keywords: Correlations
Multivariate GARCH models
Outliers
Wavelets
Issue Date: 2019
Publisher: INST ESTADISTICA CATALUNYA-IDESCAT
Abstract: It is well known that outliers can affect both the estimation of parameters and volatilities when fitting a univariate GARCH-type model. Similar biases and impacts are expected to be found on correlation dynamics in the context of multivariate time series. We study the impact of outliers on the estimation of correlations when fitting multivariate GARCH models and propose a general detection algorithm based on wavelets, that can be applied to a large class of multivariate volatility models. Its effectiveness is evaluated through a Monte Carlo study before it is applied to real data. The method is both effective and reliable, since it detects very few false outliers.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/19981
DOI: 10.2436/20.8080.02.89
ISSN: 1696-2281
Ciência-IUL: https://ciencia.iscte-iul.pt/id/ci-pub-69297
Accession number: WOS:000510397400005
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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