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This paper proposes a test to verify whether the k-th moment of a random variable is Önite. We use the fact that, under general assumptions, sample moments either converge to a Önite number or diverge to inÖnity according as the corresponding population moment is Önite or not. Building on this, we propose a test for the null that the k-th moment does not exist. Since, by construction, our test statistic diverges under the null and converges under the alternative, we propose a randomised testing procedure to discern between the two cases. We study the application of the test to raw data, and to regression residuals. Monte Carlo evidence shows that the test has the correct size and good power; the results are further illustrated through an application to Önancial data.
|Subjects:||H Social Sciences > HG Finance|
|Divisions:||Cass Business School > Faculty of Finance|
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