The valuation of an insurance balance sheet is a complex exercise that requires the simulation of various stochastic variables, such as risk-neutral economic scenarios. In practice, given typical run-time constraints, the number of economic scenarios to be considered is limited. This paper focuses on exploring the reduction of the number of simulations to achieve a reasonable objective in terms of valuation accuracy while significantly decreasing the computational time required for standard valuations. The main sections of the paper discuss:
- Analysis of the Prudent Harmonized Reduced Set of Scenarios
- Implementation of scenario reduction techniques
- Adaptive numbers of scenarios
Reducing the number of scenarios used for stochastic ALM valuation
We offer some valuable insights into scenario reduction and trajectory selection for stochastic ALM valuation that could help improve results and minimize computation.