Additive Level Outliers in Multivariate GARCH Models

Aurea Grané*, Helena Veiga, BeléN Martín-Barragán

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work analyses the impact of additive level outliers in multivariate time series. Our proposal is to extend the procedure by Grané and Veiga (Comput Stat Data Anal 54:2580–2593, 2010) to the context of Multivariate GARCH models by considering random-projections of multivariate residuals. The effectiveness of this new procedure is evaluated through an intensive Monte Carlo study.
Original languageEnglish
Title of host publicationTopics in Statistical Simulation - Research Papers from the 7th International Workshop on Statistical Simulation
EditorsV.B. Melas, Stefania Mignani, Paola Monari
PublisherSpringer New York LLC
Pages247-255
Number of pages9
ISBN (Electronic)9781493921034
DOIs
Publication statusPublished - 2014
Event7th International Workshop on Simulation - Rimini, Italy
Duration: 21 May 201325 May 2013

Publication series

NameSpringer Proceedings in Mathematics and Statistics
Volume114
ISSN (Print)2194-1009
ISSN (Electronic)2194-1017

Conference

Conference7th International Workshop on Simulation
Country/TerritoryItaly
CityRimini
Period21/05/1325/05/13

Keywords

  • Discrete Wavelet Transform
  • Outlier Detection
  • Random Projection
  • Multivariate Time Series
  • Conditional Correlation

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