Sensitivity of the Causality in Variance Test to the Garch (1,1) Parameters

19 Pages Posted: 31 May 2011

Date Written: May 31, 2011

Abstract

We discuss the sensitivity to the GARCH (1,1) parameters in the causality of variance tests. The motivation behind the study is to observe the impact of different volatile data sets on volatility spillover tests. We investigate a data generating process AR(1)-GARCH (1,1) with an extensive set of Monte Carlo experiments for different GARCH (1,1) processes. It is found that the causation pattern, due to causality between two series, is influenced by the intensity of volatility clustering. Different testing procedures are applied for testing the Causality in variance. We observe a severe size and power distortion when the clustering parameter is high and when the process is near integration. These findings are noticed 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 true underlying process with no-spillover effect and use them as a critical rigion for both size and power. We observe a meaningful improvement in the results.

Keywords: Causality, GARCH, Spillover, Volatility

Suggested Citation

Javed, Farrukh, Sensitivity of the Causality in Variance Test to the Garch (1,1) Parameters (May 31, 2011). Available at SSRN: https://ssrn.com/abstract=1856055 or http://dx.doi.org/10.2139/ssrn.1856055

Farrukh Javed (Contact Author)

Lund University ( email )

743
Lund, Skåne 220 07
Sweden

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