Non mean reverting affine processes for stochastic mortality.

In this paper we use doubly stochastic processes (or Cox processes) in order to model the random evolution of mortality of an individual. These processes have been widely used in the credit risk literature in modelling default arrival, and in this context have proved to be quite flexible, especially when the intensity process is of the affine class. We investigate the applicability of affine processes in describing the individual's intensity of mortality, and provide a calibration to the Italian and UK populations. Results from the calibration seem to suggest that, in spite of their popularity in the financial context, mean reverting processes are not suitable for describing the death intensity of individuals. On the contrary, affine processes whose deterministic part increases exponentially seem to be appropriate. As for the stochastic part, negative jumps seem to do a better job than diffusive components. Stress analysis and analytical results indicate that increasing the randomness of the intensity process results in improvements in survivorship.doubly stochastic processes (Cox processes); stochastic mortality; affine processes

Non mean reverting affne processes for stochastic mortality

In this paper we use doubly stochastic processes (or Cox processes) in order to model the random evolution of mortality of an individual. These processes have been widely used in the credit risk literature in modelling default arrival, and in this context have proved to be quite flexible, especially when the intensity process is of the affne class. We investigate the applicability of time-homogeneous a±ne processes in describing the individual's intensity of mortality and the mortality trend, as well as in forecasting it. We calibrate them to the UK population. Calibrations suggest that, in spite of their popularity in the financial context, mean reverting time-homogeneous processes are less suitable for describing the death intensity of individuals than non mean reverting processes. Among the latter, affne processes whose determin- istic part increases exponentially seem to be appropriate. They are natural generalizations of the Gompertz law. Stress analysis and analytical results indicate that increasing the randomness of the intensity process for a given cohort results in improvements in survivorship. Mortality forecasts and their comparison with experienced mortality rates provide further encour- aging evidence in favour of non mean reverting processes. The mortality trend is evidenced through the evolution over time of the parameters and through the intensity simulation for di®erent gener- ations.doubly stochastic processes (Cox processes), affne processes, stochastic mortality, mortality forecasting.

A note on stochastic survival probabilities and their calibration.

In this note we use doubly stochastic processes (or Cox processes) in order to model the evolution of the stochastic force of mortality of an individual aged x. These processes have been widely used in the credit risk literature in modelling the default arrival, and in this context have proved to be quite flexible and useful. We investigate the applicability of these processes in describing the individual's mortality, and provide a calibration to the Italian case. Results from the calibration are twofold. Firstly, the stochastic intensities seem to better capture the development of medicine and long term care which is under our daily observation. Secondly, when pricing insurance products such as life annuities, we observe a remarkable premium increase, although the expected residual lifetime is essentially unchanged.

Single and cross-generation natural hedging of longevity and financial risk

The paper provides natural hedging strategies among death benefits and annuities written on a single and on different generations. It obtains closed-form Delta and Gamma hedges, in the presence of both longevity and interest rate risk. We present an application to UK data on survivorship and bond dynamics. We first compare longevity and financial risk exposures: Deltas and Gammas for longevity risk are greater in absolute value than the corresponding sensitivities for interest rate risk. We then calculate the optimal hedges, both within and across generations. Our results apply to both asset and asset-liability management

A note on stochastic survival probabilities and their calibration

In this note we use doubly stochastic processes (or Cox processes) in order to model the evolution of the stochastic force of mortality of an individual aged x. These processes have been widely used in the credit risk literature in modelling the default arrival, and in this context have proved to be quite flexible and useful. We investigate the applicability of these processes in describing the individual's mortality, and provide a calibration to the Italian case. Results from the calibration are twofold. Firstly, the stochastic intensities seem to better capture the development of medicine and long term care which is under our daily observation. Secondly, when pricing insurance products such as life annuities, we observe a remarkable premium increase, although the expected residual lifetime is essentially unchanged.

Modelling stochastic mortality for dependent lives

Stochastic mortality, i.e. modelling death arrival via a jump process with stochastic intensity, is gaining increasing reputation as a way to rep- resent mortality risk. This paper represents a .rst attempt to model the mortality risk of couples of individuals, according to the stochastic inten- sity approach. We extend to couples the Cox processes set up, namely the idea that mortality is driven by a jump process whose intensity is itself a stochastic process, proper of a particular generation within each gen- der. Dependence between the survival times of the members of a couple is captured by an Archimedean copula. We also provide a methodology for fitting the joint survival function by working separately on the (analytical) copula and the (analytical) mar- gins. First, we calibrate and select the best fit copula according to the methodology of Wang and Wells (2000b) for censored data. Then, we provide a sample-based calibration for the intensity, using a time- homogeneous, non mean-reverting, affine process: this gives the marginal survival functions. By coupling the best fit copula with the calibrated mar- gins we obtain a joint survival function which incorporates the stochastic nature of mortality improvements. Several measures of time dependent association can be computed out of it. We apply the methodology to a well known insurance dataset, using a sample generation. The best fit copula turns out to be a Nelsen one, which implies not only positive dependency, but dependency increasing with age.stochastic mortality, bivariate mortality, copula functions, longevity risk.

Delta and Gamma hedging of mortality and interest rate risk

This paper studies the hedging problem of life insurance policies, when the mortality and interest rates are stochastic. We focus primar- ily on stochastic mortality. We represent death arrival as the rst jump time of a doubly stochastic process, i.e. a jump process with stochastic intensity. We propose a Delta-Gamma Hedging technique for mortal- ity risk in this context. The risk factor against which to hedge is the dierence between the actual mortality intensity in the future and its "forecast" today, the instantaneous forward intensity. We specialize the hedging technique rst to the case in which survival intensities are ane, then to Ornstein-Uhlenbeck and Feller processes, providing actuarial justications for this restriction. We show that, without im- posing no arbitrage, we can get equivalent probability measures under which the HJM condition for no arbitrage is satised. Last, we ex- tend our results to the presence of both interest rate and mortality risk, when the forward interest rate follows a constant-parameter Hull and White process. We provide a UK calibrated example of Delta and Gamma Hedging of both mortality and interest rate risk.

Single and cross-generation natural hedging of longevity and financial risk

The paper provides natural hedging strategies among death benefits and annuities written on a single and on different generations. It obtains closed-form Delta and Gamma hedges, in the presence of both longevity and interest rate risk. We present an application to UK data on survivorship and bond dynamics. We first compare longevity and financial risk exposures: Deltas and Gammas for longevity risk are greater in absolute value than the corresponding sensitivities for interest rate risk. We then calculate the optimal hedges, both within and across generations. Our results apply to both asset and asset-liability management