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Generalized Variance-Ratio Tests in the Presence of Statistical Dependence

Nankervis, JC and Kougoulis, P and Coakley, J (2015) 'Generalized Variance-Ratio Tests in the Presence of Statistical Dependence.' Journal of Time Series Analysis, 36 (5). 687 - 705. ISSN 0143-9782

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Abstract

This article extends and generalizes the variance-ratio (VR) statistic by employing an estimator of the asymptotic covariance matrix of the sample autocorrelations. The estimator is consistent under the null for general classes of innovations exhibiting statistical dependence including exponential generalized autoregressive conditional heteroskedasticity and non-martingale difference sequence processes. Monte Carlo experiments show that our generalized test statistics have good finite sample size and superior power properties to other recently developed VR versions. In an application to two major US stock indices, our new generalized VR tests provide stronger rejections of the null than do competing VR tests.

Item Type: Article
Additional Information: Journal of Time Series Analysis Special Issue: John Nankervis Memorial Conference.
Uncontrolled Keywords: Variance-ratio statistic;non-MDS process;Monte Carlo
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Jim Jamieson
Date Deposited: 11 May 2015 10:20
Last Modified: 06 Feb 2019 17:15
URI: http://repository.essex.ac.uk/id/eprint/13686

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