Valuation of Large Variable Annuity Portfolios: Monte Carlo Simulation and Benchmark Datasets

Abstract

Metamodeling techniques have recently been proposed to address the computational issues related to the valuation of large portfolios of variable annuity contracts. However, it is extremely difficult, if not impossible, for researchers to obtain real datasets from insurance companies in order to test their metamodeling techniques on such real datasets and publish the results in academic journals. Even if a researcher can obtain real datasets from insurance companies, it is difficult for the re- searcher to share the datasets with the public at large. To facilitate the development and dissemination of research related to the efficient valuation of large variable annuity portfolios, this paper creates a large synthetic portfolio of variable annuity contracts based on the properties of real portfolios of variable annuities and implements a Monte Carlo simulation engine for valuing the synthetic portfolio. In addition, this paper develops benchmark datasets of fair market values and Greeks, which are important quantities for managing the financial risks associated with variable annuities. The resulting datasets provide researchers with a common basis for testing and comparing the performance of various metamodeling techniques.