Modeling Aggregated Returns with Application to Segregated Fund Guarantees

Gurbakhshash Singh successfully defended his M.Sc. project entitled "Modeling Aggregated Returns with Application to Segregated Fund Guarantees" on 31 July 2006.

Segregated funds are a popular insurance product. What premium should an insurance company charge to make a profit and to keep the risk of failing to have enough funds to pay for the fund at its retention at an acceptable level.

These funds are too complicated to value using analytical methods and simulation studies are often used to study their performance.

However, in guarantee valuation for a segregated fund, the simulation process can be time-consuming. When simulation calculations are based upon weekly or monthly return models, the computation can be quite lengthy for contracts that extend over decades. Simulation run time can be reduced by decreasing the number of calculations. This is accomplished through an aggregated return model.

We study models for the aggregated returns when the estimated model is lognormal, an AR(1), two-state regime switching and a multivariate lognormal. As an illustration of the aggregate models, we use a conditional tail expectation for valuation of a segregated funds guarantee.

This type of interdisciplinary work is a hallmark of our program in Applied Statistics at Simon Fraser University. For more information, please contact Gurbakhshash Singh (gsingh1@sfu.ca) or his supervisor Gary Parker (gparker@stat.sfu.ca), Department of Statistics and Actuarial Science.

July 2006