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What actuaries call cash flow testing is a large-scale simulation pitting a company''s current policy obligation against future earnings based on interest rates. While life contingency issues associated with contract payoff are a mainstay of the actuarial sciences, modeling the random fluctuations of US Treasury rates is less studied. Furthermore, applying standard simulation techniques, such as the Monte Carlo method, to actual multi-billion dollar companies produce a simulation that can be computationally prohibitive. In practice, only hundreds of sample paths can be considered, not the usual hundreds of thousands one might expect for a simulation of this complexity. Hence, insurance companies have a desire to accelerate the convergence of the estimation procedure. The paper reports the results of cash flow testing simulations performed for Conseco L.L.C. using so-called quasi-Monte Carlo techniques. In these, pseudo-random number generation is replaced with deterministic low discrepancy sequences. It was found that by judicious choice of subsequences, that the quasi-Monte Carlo method provided a consistently tighter estimate than the traditional methods for a fixed, small number of sample paths. The techniques used to select these subsequences are discussed.
- Monte Carlo Method,
- Monte Carlo Methods,
- US Treasury Rates,
- Actuarial Sciences,
- Actuaries,
- Cash Flow Testing Simulations,
- Contract Payoff,
- Current Policy Obligation,
- Deterministic Low Discrepancy Sequences,
- Digital Simulation,
- Estimation Procedure,
- Future Earnings,
- Insurance Companies,
- Insurance Data Processing,
- Interest Rates,
- Investment,
- Large-Scale Simulation,
- Life Contingency Issues,
- Multi-Billion Dollar Companies,
- Pseudo-Random Number Generation,
- Quasi-Monte Carlo Methods,
- Random Fluctuations,
- Random Processes,
- Sample Paths,
- Sequences,
- Standard Simulation Techniques
Available at: http://works.bepress.com/michael-hilgers/18/