文章基本信息

标题：Modified Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity
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作者：Sohail Chand ; Nuzhat Aftab
期刊名称：The Lahore Journal of Economics
印刷版ISSN：1811-5438
电子版ISSN：1811-5446
出版年度：2018
卷号：23
期号：1
页码：1-19
出版社：Lahore School of Economics
摘要：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.
关键词：Regression; variance break; wild bootstrap.