IDEAS home Printed from https://ideas.repec.org/r/cup/bracjl/v8y2002i03p443-518_00.html
   My bibliography  Save this item

Stochastic Claims Reserving in General Insurance

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Massimo De Felice & Franco Moriconi, 2023. "Stochastic Chain-Ladder Reserving with Modeled General Inflation," Risks, MDPI, vol. 11(12), pages 1-31, December.
  2. Crevecoeur, Jonas & Antonio, Katrien & Verbelen, Roel, 2019. "Modeling the number of hidden events subject to observation delay," European Journal of Operational Research, Elsevier, vol. 277(3), pages 930-944.
  3. Avanzi, Benjamin & Taylor, Greg & Vu, Phuong Anh & Wong, Bernard, 2020. "A multivariate evolutionary generalised linear model framework with adaptive estimation for claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 50-71.
  4. Karthik Sriram & Peng Shi, 2021. "Stochastic loss reserving: A new perspective from a Dirichlet model," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 195-230, March.
  5. Ihsan Chaoubi & Camille Besse & H'el`ene Cossette & Marie-Pier C^ot'e, 2022. "Micro-level Reserving for General Insurance Claims using a Long Short-Term Memory Network," Papers 2201.13267, arXiv.org.
  6. Lindholm, Mathias & Verrall, Richard, 2020. "Regression based reserving models and partial information," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 109-124.
  7. Maciak, Matúš & Okhrin, Ostap & Pešta, Michal, 2021. "Infinitely stochastic micro reserving," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 30-58.
  8. Jonas Harnau, 2018. "Misspecification Tests for Log-Normal and Over-Dispersed Poisson Chain-Ladder Models," Risks, MDPI, vol. 6(2), pages 1-25, March.
  9. D. Kuang & B. Nielsen & J. P. Nielsen, 2008. "Forecasting with the age-period-cohort model and the extended chain-ladder model," Biometrika, Biometrika Trust, vol. 95(4), pages 987-991.
  10. Portugal, Luís & Pantelous, Athanasios A. & Verrall, Richard, 2021. "Univariate and multivariate claims reserving with Generalized Link Ratios," Insurance: Mathematics and Economics, Elsevier, vol. 97(C), pages 57-67.
  11. Nataliya Chukhrova & Arne Johannssen, 2017. "State Space Models and the K alman -Filter in Stochastic Claims Reserving: Forecasting, Filtering and Smoothing," Risks, MDPI, vol. 5(2), pages 1-23, May.
  12. Alessandro Ricotta & Gian Paolo Clemente, 2016. "An Extension of Collective Risk Model for Stochastic Claim Reserving," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(5), pages 1-3.
  13. repec:osf:osfxxx:3pjr9_v1 is not listed on IDEAS
  14. Najafabadi, Amir T. Payandeh & Bazaz, Ali Panahi, 2018. "An optimal multi-layer reinsurance policy under conditional tail expectation," Annals of Actuarial Science, Cambridge University Press, vol. 12(1), pages 130-146, March.
  15. Corneliu Cristian Bente, 2017. "Actuarial Estimation Of Technical Reserves In Insurance Companies. Basic Chain Ladder Method," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 227-234, July.
  16. D Kuang & Bent Nielsen & J P Nielsen, 2013. "The Geometric Chain-Ladder," Economics Papers 2013-W11, Economics Group, Nuffield College, University of Oxford.
  17. Kevin Kuo, 2018. "DeepTriangle: A Deep Learning Approach to Loss Reserving," Papers 1804.09253, arXiv.org, revised Sep 2019.
  18. Zoë Fannon & B. Nielsen, 2018. "Age-period cohort models," Economics Papers 2018-W04, Economics Group, Nuffield College, University of Oxford.
  19. Di Kuang & Bent Nielsen & Jens Perch Nielsen, 2011. "Forecasting in an Extended Chain‐Ladder‐Type Model," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(2), pages 345-359, 06.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.