Asset Pricing of Life-Contingent Contracts with n-State Longevity Data
Generating Process 
   Lead Investigator:    Russ Nel
   Institution      :    EDHEC risk institute
   E-Mail           :    russ@zasecagroup.com
   Proposal ID      :    503


   Publications:


1  Nel R
   Asset Pricing of Life-Contingent Claims with n-State Stochastic Longevity Data Generating Process
   2016   Journal Article  Insurance: Mathematics and Economics , 

   SUBMITTED





   Proposal Description:
   The goal of my research is to value life-contingent financial contracts in ages 65 and above. In this age range impaired health is an important factor to consider in computing life expectancy. I have developed a multi-state longevity data generating process that depend on two key longevity drivers being (i) impaired health and (ii) age-specificity. The expected outcomes of my research would be to provide valuation, risk assessment and dynamic asset allocation tools for financial contracts that are indexed to longevity. The proposed research will incorporate Alzheimer???s disease transition probabilities which will be derived from the Raw CDR transition count data.      The specific objectives of the research is to solve a problem in financial contract pricing ??? specifically when pricing life insurance contracts in the secondary market i.e. when pricing the life expectancy of an individual on whose life the contract is been purchased or sold, the market currently uses age-specific life tables combined with a subjective health review to adjust the age-specific life table. This legacy approach produces a deterministic life expectancy, which is subjective and does not provide acceptable valuation and risk information to market participants.      The current research proposes to utilize the raw clinical data and age-specific life tables to create a longevity data generating process utilizing multi-state markov chains and thus produce a stochastic approach to pricing these financial contract. In addition, this approach enables the market to assess higher order moments for life expectancy based on specific individual impaired health conditions. In addition, this research will bring the current market environment closer to a standardized method of valuation and risk management in longevity pricing.