Description: This paper presents an introduction to collective risk theory. In collective risk theory one seeks to investigate directly the risk enterprise as a whole. Primary interest is focused not upon the gains, losses, or claims from individual policies but upon the amount of total claims or the total gain arising from all the policies in the portfolio considered. Followed by several discussion papers submitted.

Description: Without relying on formulas, this paper presents the important concepts underlying the theory of arbitrage-free pricing of interest-rate-contingent cash flows: absence of opportunities for riskless arbitrage, completeness of markets, relative prices that do not depend on individual investors' subjective views or risk preferences, and expected-value pricing in the risk-neutral world. Using these concepts, the paper then describes the steps required to build continuous stochastic models of interest rates, including models that are either partially or fully arbitrage free.

Description: The series expansion of a probability density function, known to actuaries by Esscher's name and to statisticians as the saddlepoint approximation, typically gets integrated to approximate probability values under the density, with a location parameter in the expansion chosen to optimize convergence of the integrated series. We review the general form, the accuracy and the derivation of the Esscher approximation. Then we propose using related series expansions for the derivative of a probability density function to approximate the value of the point of maximum likelihood for the density. The key is to make the value of the location parameter an unknown and assume it to be the point of maximum likelihood, which leads to a tractable optimization problem to find its value.