In the literature on stochastic programming models for practical portfolio investment problems, relatively little attention has been devoted to the question how the necessarily approximate description of the asset-price uncertainty in these models influences the optimal solution. In this paper...

We derive the exact loss distribution for portfolios of bonds or cor-porate loans when the number of risks grows indefinitely. We show that in many cases this distribution lies in the maximal domain of attraction of the Weibull (Type III) limit law. Knowledge of the dis-tribution and its tail...

We consider portfolio credit loss distributions based on a factor model for individual exposures and establish an analytic characterization of the credit loss distribution if the number of exposures tends to infinity. Using this limiting distribution, we explain how skewness and leptokurtosis of...

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of the distribution of credit losses. We show that in many cases of practical interest the distribution of these losses has polynomial ('fat') rather than exponential ('thin') tails. Our...

In models of decision making under uncertainty, one typically has to approximate the uncertainties by a limited number of discrete outcomes. Høyland and Wallace (2001) formulate a nonlinear programming problem to generate such a limited number of discrete outcomes while satisfying specified...