A NEW MODEL FOR DATA WITH STRUCTURAL CHANGE AT THRESHOLD: COMPOSITE EXPONENTIAL-LOGNORMAL MODEL


GENÇTÜRK Y. , YİĞİTER A. , HAMURKAROĞLU C.

ADVANCES AND APPLICATIONS IN STATISTICS, vol.53, no.4, pp.441-456, 2018 (Journal Indexed in ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 53 Issue: 4
  • Publication Date: 2018
  • Doi Number: 10.17654/as053040441
  • Title of Journal : ADVANCES AND APPLICATIONS IN STATISTICS
  • Page Numbers: pp.441-456

Abstract

It is important for an insurance company to predict the future claims in order to evaluate premiums, to determine the reserve necessary to meet its obligation and probabilities of ruin, etc. As claim data is highly positively skewed and has heavy tail, no standard parametric model seems to provide an acceptable fit to both small and large losses. Composite models that use one standard distribution up to a threshold and other standard distribution thereafter are developed and it is seen that these composite models provide a better fit than the standard models when claim data involve small and high claims.