ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Kæde-stige tabsafsættelse (Mack-modellen)×Loss Distribution Model×
FagområdeAktuarvidenskabAktuarvidenskab
FamilieRegression modelRegression model
Oprindelsesår19932012
OphavspersonThomas MackKlugman, Panjer & Willmot
TypeStochastic loss reserving modelParametric probability model
Oprindelig kildeMack, T. (1993). Distribution-free calculation of the standard error of chain ladder reserve estimates. ASTIN Bulletin, 23(2), 213–225. DOI ↗Klugman, S. A., Panjer, H. H., & Willmot, G. E. (2012). Loss Models: From Data to Decisions (4th ed.). Wiley. ISBN: 978-1-118-31532-3
AliasserDevelopment Factor Method, Link Ratio Method, Loss Development Method, Zincir Merdiven YöntemiSeverity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı Modeli
Relaterede33
ResuméChain-Ladder Reserving is a stochastic actuarial method for estimating outstanding claim liabilities from a run-off triangle of cumulative paid losses. Formalized by Thomas Mack in 1993, it provides distribution-free estimates of reserve amounts along with their standard errors, making it a cornerstone of property-casualty insurance reserving and regulatory practice worldwide.A Loss Distribution Model is a parametric statistical framework used in actuarial science to characterise the probabilistic behaviour of insurance claim amounts and frequencies. Developed comprehensively by Klugman, Panjer, and Willmot in their foundational text Loss Models: From Data to Decisions (first edition 1998, fourth edition 2012), these models underpin premium rating, reserving, reinsurance pricing, and regulatory capital calculations across the insurance and risk-management industries.
ScholarGateDatasæt
  1. v1
  2. 1 Kilder
  3. PUBLISHED
  1. v1
  2. 1 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Chain-Ladder Reserving · Loss Distribution Model. Hentet 2026-06-18 fra https://scholargate.app/da/compare