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Inference for performance measures for financial assets

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  • Lucio Capitani
  • Leo Pasquazzi

Abstract

In this work the precision of point and interval estimators for some performance measures for risky financial assets is analyzed and the conditions under which the point estimators are asymptotically normally distributed are provided. The findings of this research suggest that a huge number of observations is needed to get reasonably precise point and interval estimates. Therefore, the considered performance measures may be surely employed as descriptive statistics for ex-post performance comparisons but they should be employed with caution in ex-ante evaluations for investment choices. Copyright Sapienza Università di Roma 2015

Suggested Citation

  • Lucio Capitani & Leo Pasquazzi, 2015. "Inference for performance measures for financial assets," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 73-98, April.
    • Handle: RePEc:spr:metron:v:73:y:2015:i:1:p:73-98
    DOI: 10.1007/s40300-014-0055-y
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    References listed on IDEAS

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    Cited by:

    1. Sally G. Arcidiacono & Damiano Rossello, 2022. "A hybrid approach to the discrepancy in financial performance’s robustness," Operational Research, Springer, vol. 22(5), pages 5441-5476, November.
    2. Claudio Giovanni Borroni & Lucio De Capitani, 2022. "Some measures of kurtosis and their inference on large datasets," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 573-607, December.

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