Description: This paper addresses the stochastic modeling for managing asset liability process. We start with developing a jump-diffusion process for evaluating of the liabilities of the insurance company in general. We then formulate the ALM process into a stochastic control problem. With this approach, we present a Bel|man-Dreyfus Fundamental type formula for ALM process in terms of the solution of a system of algebraic equations and partial differential equations.

Description: This paper discusses both the theoretical and the application aspects of stress testing in managing enterprise risks. Effective stress testing maximizes the risk adjusted enterprise profit by controlling major risks financial, strategic, operational and hazard upon identifying risk metrics and modeling the correlations. A case study is included for demonstration purposes.

Description: Traditional mean-variance method does not take skewness of the random rate of return into consideration. It only considers minimum variance for a given acceptable rate of return, which limited the probability of obtaining higher rate of return. If the skewness of return for the portfolio is incorporated into model of traditional approach, then the resulting non-linear programing model is not computational efficient, which certainly is complicated. On the other hand, possibilistic programming provides more efficient techniques to solve the imprecision nature of rate of return and also preserves the original linear model.