Abstract
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.
Recommended Citation
Hilgers, M. G. (2000). Quasi-Monte Carlo Methods in Cash Flow Testing Simulations. Institute of Electrical and Electronics Engineers (IEEE).
The definitive version is available at https://doi.org/10.1109/WSC.2000.899759
Department(s)
Business and Information Technology
Keywords and Phrases
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
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2000 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2000
