Počet záznamů: 1

On the Favorable Estimation for Fitting Heavy Tailed Data

  1. 1.
    0342150 - UIVT-O 2011 RIV DE eng J - Článek v odborném periodiku
    Stehlík, M. - Potocký, R. - Waldl, H. - Fabián, Zdeněk
    On the Favorable Estimation for Fitting Heavy Tailed Data.
    Computational Statistics. Roč. 25, č. 3 (2010), s. 485-503 ISSN 0943-4062
    Grant ostatní:ASO(SK) SK-0607-BA-018; VEGA(SK) 1/0077/09; 50p14(CZ-AT) AKTION; AKTION(CZ-AT) 54p13
    Výzkumný záměr: CEZ:AV0Z10300504
    Klíčová slova: heavy-tailed distribution * exact likelihood ratio test * T-score moment estimator * insurance * Basel II
    Kód oboru RIV: BB - Aplikovaná statistika, operační výzkum
    Impakt faktor: 0.500, rok: 2010

    Assessment of heavy tailed data and its compound sums has many applications in insurance, auditing and operational risk capital assessment among others. In this paper, we compare the classical estimators (maximum likelihood, QQ and moment estimators) with the recently introduced robust estimators of “generalized median”, “trimmed mean” and estimators based on t-score moments. We derive the exact distribution of the likelihood ratio tests of homogeneity and simple hypothesis on the tail index of a two-parameter Pareto model. Such exact tests support the assessment of the performance of estimators. In particular, we discuss some problems that one can encounter when misemploying the log-normal assumption based methods supported by the Basel II framework. Real data and simulated examples illustrate the methods.
    Trvalý link: http://hdl.handle.net/11104/0184964