Apicella, Giovanna and Dacorogna, Michel M (2016): A General framework for modelling mortality to better estimate its relationship with interest rate risks.

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Abstract
The need for having a good knowledge of the degree of dependence between various risks is fundamental for understanding their real impacts and consequences, since dependence reduces the possibility to diversify the risks.
This paper expands in a more theoretical approach the methodology developed in for exploring the dependence between mortality and market risks in case of stress. In particular, we investigate, using the Feller process, the relationship between mortality and interest rate risks. These are the primary sources of risk for life (re)insurance companies. We apply the Feller process to both mortality and interest rate intensities.
Our study cover both the short and the longterm interest rates (3m and 10y) as well as the mortality indices of ten developed countries and extending over the same time horizon. Specifically, this paper deals with the stochastic modelling of mortality. We calibrate two different specifications of the Feller process (a twoparameters Feller process and a threeparameters one) to the survival probabilities of the generation of males born in 1940 in ten developed countries. Looking simultaneously at different countries gives us the possibility to find regularities that go beyond one particular case and are general enough to gain more confidence in the results. The calibration provides in most of the cases a very good fit to the data extrapolated from the mortality tables. On the basis of the principle of parsimony, we choose the twoparameters Feller process, namely the hypothesis with the fewer assumptions. These results provide the basis to study the dynamics of both risks and their dependence.
Item Type:  MPRA Paper 

Original Title:  A General framework for modelling mortality to better estimate its relationship with interest rate risks 
Language:  English 
Keywords:  Mortality Model, Interest Rate Model, Dependence 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C  Mathematical and Quantitative Methods > C4  Econometric and Statistical Methods: Special Topics > C40  General 
Item ID:  75788 
Depositing User:  Dr Michel M Dacorogna 
Date Deposited:  25 Dec 2016 13:05 
Last Modified:  25 Dec 2016 13:05 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/75788 