Description: Presented at August 2011 Actuarial Research Conference. Summarizes the Heston model, discusses hedging equity indexed annuities, and provides numerical results of the Black-Scholes and Heston hedging strategies.

Description: The April 2016 Issue of The Modeling Platform

Description: Presentation at the 41st Actuarial Research Conference held on August 10-12, 2006 in Montreal, QC. This paper considers the problem of extending regime-switching models for asset returns to the situation with multiple asset markets. The conditional tail expectation CTE is highly sensitive to the assumed dependence structure between the regime models for the different markets. A Monte Carlo simulation is used to illustrate the cost of misspecification. The authors find that the model most commonly used by practitioners is worse than all of the alternatives that they investigate.

Description: This paper first derives the fair participation rate based on a fair value of the equity-indexed annuity EIA. Then using risk measures, a new participation rate is obtained, based on the tail loading of the hedging error distribution. Risk management strategies reducing risk related to the hedging error are also presented. A detailed numerical analysis is performed for a point-to-point EIA.

Description: Discussion of the movement toward principle-based reserves for LTC insurance.

Description: Discussion of Capital Market Modeling techniques

Description: This article explains why stochastic modeling is becoming more pervasive, and describes a specific stochastic application with metrics to measure results.

Description: In this paper we give new general criteria for the weak convergence of one-dimensional distributions of generalized risk processes and describe the class of possible limit laws under an infinite growth of stochastic portfolio size and stochastic intensity of insurance payment.

Description: The behavior of extreme paths in the usual stochastic interest rate models is not nearly so plausible as the behavior of their expected values and variances. This paper proposes a new class of models that deliver more plausible extreme paths while preserving the usual expected value and variance behavior. Along the way we derive the closed form solution for the traditional mean-reverting lognormal process, including the drift compensation.

Description: These are Charts 1-4 from a presentation entitled 'Stochastic Immunization' From a session at a meeting of the Society of Actuaries held in San Diego, CA, June 22-23, 2000