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A note on the bootstrap method for testing the existence of finite moments

Author

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  • Igor Fedotenkov

    (Lithuanian Institute of Agrarian Economics, Vilnius - Ltuania)

Abstract

This paper discusses a bootstrap-based test, which checks if finite moments exist, and indicates cases of possible misapplication. It notes, that a procedure for finding the smallest power to which observations need to be raised, such that the test rejects a hypothesis that the corresponding moment is finite, works poorly as an estimator of the tail index or moment estimator. This is the case especially for very low- and high-order moments. Several examples of correct usage of the test are also shown. The main result is derived analytically, and a Monte-Carlo experiment is presented.

Suggested Citation

  • Igor Fedotenkov, 2014. "A note on the bootstrap method for testing the existence of finite moments," Statistica, Department of Statistics, University of Bologna, vol. 74(4), pages 447-453.
    • Handle: RePEc:bot:rivsta:v:74:y:2014:i:4:p:447-453
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    Cited by:

    1. Robin Merkle & Andrea Barth, 2022. "On Some Distributional Properties of Subordinated Gaussian Random Fields," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 2661-2688, December.
    2. Wai Leong Ng & Chun Yip Yau, 2018. "Test for the existence of finite moments via bootstrap," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 28-48, January.
    3. Dewitte, Ruben, 2020. "From Heavy-Tailed Micro to Macro: on the characterization of firm-level heterogeneity and its aggregation properties," MPRA Paper 103170, University Library of Munich, Germany.

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    Keywords

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    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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