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Automatic variance ratio test under conditional heteroskedasticity

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  • Kim, Jae H.

Abstract

An extensive Monte Carlo experiment is conducted to evaluate small sample properties of the automatic variance ratio test under conditional heteroskedasticity. It is found that the test shows serious size distortion in small samples. For improved small sample performance, this paper proposes the use of wild bootstrap. When wild bootstrapped, the automatic variance ratio test shows no size distortion, and it has power substantially higher than its competitors such as the Chen-Deo test and wild bootstrap Chow-Denning test.

Suggested Citation

  • Kim, Jae H., 2009. "Automatic variance ratio test under conditional heteroskedasticity," Finance Research Letters, Elsevier, vol. 6(3), pages 179-185, September.
    • Handle: RePEc:eee:finlet:v:6:y:2009:i:3:p:179-185
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    References listed on IDEAS

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