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Sensitivity of the causality in variance tests to GARCH(1,1) processes
Lund University, Lund, Sweden..ORCID iD: 0000-0002-1488-4703
Örebro University, Örebro University School of Business.
2015 (English)In: Chilean Journal of Statistics, ISSN 0718-7912, E-ISSN 0718-7920, Vol. 6, no 1, p. 49-65Article in journal (Refereed) Published
Abstract [en]

This paper studies the impact of a number of volatile data sets on volatility spillover tests. We investigate a type of data generating process, AR(1)-GARCH(1,1), with an extensive set of Monte Carlo simulations. It is found that causation pattern, due to causality between two series, is influenced by the intensity of volatility clustering. Two testing procedures are applied for testing causality in the variance. We notice a severe size and power distortion when the clustering parameter is high and when the process is near integration. Furthermore, whenever there is a severe size distortion, there is a serial autocorrelation in the standardized residuals. This is seen when the asymptotic distribution of the statistics is used to define a critical region. So, instead of relying on the asymptotic distribution, we calculate the percentiles of the test statistic with the null hypothesis of no spillover effect and use them as a critical region for both size and power. We observe a significant improvement in the results.

Place, publisher, year, edition, pages
2015. Vol. 6, no 1, p. 49-65
Keywords [en]
Causality, GARCH, Spillover, Volatility
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:oru:diva-54702ISI: 000360110300004OAI: oai:DiVA.org:oru-54702DiVA, id: diva2:1065092
Available from: 2017-01-13 Created: 2017-01-13 Last updated: 2017-11-08Bibliographically approved

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Javed, FarrukhMantalos, Panagiotis

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