Modeling Mortality with Jumps: Applications to Mortality Securitization

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Modeling Mortality with Jumps: Applications to Mortality Securitization

INTRODUCTION

Mortality risk management is fundamental to life insurance and pension industries. Mortality models make it available to quantify the risks and provide the basis of pricing and reserving. Traditionally, reinsurance, and more recently, securitization, renders a mean of transferring or hedging mortality risks. Naturally, mortality models are fundamental to these transactions.

Mortality securitizations differ from reinsurance transactions in several ways. Perhaps the most important is that investors in a securitization typically do not have the mortality expertise that a reinsurer has. Also, in order to avoid moral hazard problems, the basis of a securitization may be a public index rather than the actual lives insured by the ceding party. Therefore, it is important that a mortality model clearly conveys the nature of risk transfer to investors, reflects the characteristics of available data, and provides for scenario analysis.

A wide variety of stochastic models have been proposed for modeling the dynamics of mortality over time. Cairns, Blake, and Dowd (2006a) provide a detailed overview and categorization. Most of the literature in this field is in the framework of short-rate models, among which continuous time models focus on the spot force of mortality and discrete time models concentrate on the spot mortality rates. Continuous time models (e.g., Milevsky and Promislow, 2001; Dahl, 2004; Biffis, 2005; Dahl and Moller, 2006; Miltersen and Persson, 2005; Schräger, 2006) help us understand the evolution of mortality rates over time, but they are relatively intractable. We prefer discrete time models because mort...

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