Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/167918
Authors: 
Hirz, Jonas
Schmock, Uwe
Shevchenko, Pavel V.
Year of Publication: 
2017
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 5 [Year:] 2017 [Issue:] 2 [Pages:] 1-29
Abstract: 
We introduce an additive stochastic mortality model which allows joint modelling and forecasting of underlying death causes. Parameter families for mortality trends can be chosen freely. As model settings become high dimensional, Markov chain Monte Carlo (MCMC) is used for parameter estimation. We then link our proposed model to an extended version of the credit risk model CreditRisk+. This allows exact risk aggregation via an efficient numerically stable Panjer recursion algorithm and provides numerous applications in credit, life insurance and annuity portfolios to derive P&L distributions. Furthermore, the model allows exact (without Monte Carlo simulation error) calculation of risk measures and their sensitivities with respect to model parameters for P&L distributions such as value-at-risk and expected shortfall. Numerous examples, including an application to partial internal models under Solvency II, using Austrian and Australian data are shown.
Subjects: 
stochastic mortality model
extended CreditRisk+
risk aggregation
partial internal model
mortality risk
longevity risk
Markov chain Monte Carlo
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
Appears in Collections:

Files in This Item:
File
Size
653.99 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.