Description: In the context of reinsurance, this paper addresses finding the quota share retention level and the retention limit, with a diffusion process being added to the claim process, that maximizes the adjustment coefficient in the Sparre Anderson model. From Actuarial Research Clearing House, 2006.

Description: This paper provides a new insight to the previous work of Briys and de Varenne [1994], Grosen and Jørgensen [2002] and Chen and Suchanecki [2007]. It shows that if an insurance company follows a risk management strategy, it can significantly change the risk exposure of the company, and that it should thus be taken into account by the regulators.

Description: Poisson regression models are commonly used in actuarial science to model count data e.g., the number of claims and covariates. The standard parametric formulation assumes that the response to covariates is constant across the population under study. Additionally, the shape of the posterior distribution is rather inflexible. In practice, however, the response to covariates may depend on a latent class and the posterior distribution may be highly nonparametric. This paper proposes a Bayesian nonparametric model in which a Dirichlet process prior on the regression coefficients leads to a clustering of observations into groups having the same response to covariates. This paper illustrates the utility of this approach with an example dataset of diabetes deaths.

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.

Description: The theme of this presentation relates to solving portfolio selection problems using linear and fractional programming. Two key contributions: 1. Generalization of the CVaR linear optimization framework. 2. Equivalences among four formulations of Coherent Distortion Risk Mearures optimization problems. From Actuarial Research Clearing House, 2012, Vol. 1.

Description: Presented at August 2011 46th Actuarial Research Conference. This paper focuses on mainly focus on the case in which the risk variable follows a distribution function from a max-domain of attraction.

Description: This is a finalist submission for the 2018 Student Case Study Challenge.

Description: This is the third place submission for the 2018 Student Case Study Challenge.

Description: This is the 2nd place submission for the 2018 Student Case Study Challenge.

Description: This study is an update of a 2015 study that illustrates the differences that occur when measurement is made under different accounting bases. The observations come from research performed on two products (term life insurance and universal life insurance with secondary guarantees.