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Modified Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity

Sohail Chand () and Nuzhat Aftab ()
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Sohail Chand: Associate Professor, College of Statistical and Actuarial Sciences, University of the Punjab, Pakistan.
Nuzhat Aftab: PhD Scholar, College of Statistical and Actuarial Sciences, University of the Punjab, Pakistan.

Lahore Journal of Economics, 2018, vol. 23, issue 1, 1-19

Abstract: Given that autocorrelation tests do not perform well in the presence of heteroskedasticity and in variance-break cases, we present three modified weighted variance ratio tests of autocorrelation. The numerical results show that the proposed tests perform better for small samples. They provide a better approximation of asymptotic distributions and are more powerful when the lag length is mis-specified. The study also applies these tests to data on the daily returns of two companies listed on the Pakistan Stock Exchange.

Keywords: Regression; variance break; wild bootstrap. (search for similar items in EconPapers)
JEL-codes: C40 (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:lje:journl:v:23:y:2018:i:1:p:1-19