Master of Science
Statistics and Actuarial Sciences
In this thesis, we consider a framework under which three correlated factors, namely, financial, mortality and lapse risks, are modelled in an integrated way. This modelling framework supports the valuation of a guaranteed minimum accumulation benefit (GMAB). The change-of-measure approach is employed to come up with a compact and implementable valuation expressions. We provide a numerical demonstration to confirm the efficiency and accuracy of our proposed pricing methodology. In particular, our approach on average takes only 0.07% of the computing time entailed by the Monte-Carlo (MC) simulation technique. Furthermore, the standard errors of our approach’s results are lower than those obtained from MC-based computations. When there are no renewal options in a GMAB contract, we get the special case of a guaranteed minimum maturity benefit for which a closed-form pricing solution is derived.
Summary for Lay Audience
When a customer comes to an insurance company to learn something about one specific insurance product, the insurer will be asked to provide the corresponding purchase price. After obtaining the customer's essential information, they start to calculate the price. However, if they can't give a response within a short time, they would provide a negative customer service experience, which consequently might force the customer to switch to another company. Therefore, it is important for the insurer to have a quick-response evaluation system in order to get an edge over the competition. This thesis will provide such an evaluation framework in the valuation of a specific insurance product, called the guaranteed minimum accumulation benefit (GMAB).
Huang, Yiming, "A computationally efficient methodology in pricing a guaranteed minimum accumulation benefit" (2019). Electronic Thesis and Dissertation Repository. 6507.