• DocumentCode
    1798449
  • Title

    Research on risk measurement model based on WHI estimator

  • Author

    Xia Cai ; Xiu-Min Li ; Yan Li

  • Author_Institution
    Sch. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
  • Volume
    2
  • fYear
    2014
  • fDate
    13-16 July 2014
  • Firstpage
    777
  • Lastpage
    781
  • Abstract
    Risk measurement plays an important role in fields of finance and insurance. In this paper, extreme value theory is used to construct a new risk measurement model. The underlying distribution of finance and insurance data usually belongs to the domain of attraction of extreme value distribution. The type of extreme value distribution depends on the extreme value index. Therefore, the estimation method for the extreme value index is important. The traditional Weiss-Hill estimator of the extreme value index is not shift invariant In this paper, the new Weiss-Hill-Invariant estimator is proposed, and the properties of shift and scale invariants are presented. Finally, the new WHI estimator is applied to study the logarithmic rate of return in the stock market. The tail probabilities and high quantiles are also derived.
  • Keywords
    estimation theory; insurance; risk management; WHI estimator; Weiss-Hill-Invariant estimator; extreme value distribution; extreme value index; finance; insurance; risk measurement model; stock market; Abstracts; Finance; Heating; Insurance; Mathematics; Extreme value index; Heavy tailed distribution; Shift and scale invariant; WHI estimator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
  • Conference_Location
    Lanzhou
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4799-4216-9
  • Type

    conf

  • DOI
    10.1109/ICMLC.2014.7009708
  • Filename
    7009708