Description: This paper develops an option pricing model that takes cost of capital concepts as its foundation rather than dynamic replication. The resulting model, called the 'C' measure in this paper, is related to the family of Affine Jump Diffusion models that are well known in the finance literature, so it is fairly easy to understand and implement. We argue that this is a reasonable model to use for estimating equity implied volatilities that are beyond the five- to 10-year horizon that can typically be observed in today‘s capital markets. The paper concludes with a short discussion of how to grade from observable market data to the 'C' measure.

Description: An excerpt from a presentation at the 2014 Living to 100 Symposium, this article describes an open-source model for use by actuaries attempting to estimate future health benefit costs, discusses its strengths and limitations, and projects that spending for those age over 65 will take more than $13 trillion by 2055, about 50 percent of total medical expenditures.

Description: Discussion of the separate and joint effects of obesity and diabetes on disability and mortality, and ways these effects can be used to improved insurance pricing and reserving, reverse the increasing rates of obesity and diabetes, and improve current projections of disability and mortality risks.

Description: This study note focuses on actuarial applications and loss distributions for insurance products.

Description: This paper discusses the actuarial risk measures and uses a variety of estimation techniques such as nonparametric approach, parametric methods and robust procedures. From 39th Actuarial Research Conference, Iowa City, Iowa, August 5-7, 2004.

Description: This paper presents a random selection method with the Monte Carlo simulation technique in the estimation of loss reserves. The future loss development factors are randomly selected from a weighted empirical distribution of observed loss development factors. This nonparametric approach provides an estimate of the distribution of total loss reserve.

Description: This is a presentation From 38th Annual Actuarial Research Conference 8/9/2003, University of Michigan, Ann Arbor, Michigan. Pricing health insurance presents numerous statistical problems. This paper develops a non-parametric method for handling these problems. This method involves kernel density estimation of the charge level distribution and also kernel smoothing between the reimbursement function derivatives. It derives some properties of the estimates so obtained. It illustrates the method with some dental data and compares the results to some other simpler estimation techniques.