Value-at-Risk (VaR) models often are used to estimate the equity investment that is required to limit the default rate on funding debt. Typical VaR "buffer stock" capital calculations produce biased estimates. To ensure accuracy, VaR must be modified by: (1) measuring loss relative to initial...

The paper presents the basic Credit Risk+ model, and proposes some modifications. This model could be useful in the stress-testing financial sector assessments process as a benchmark for credit risk evaluations. First, we present the setting and basic definitions common to all the model...

We develop a methodology for optimal design of financial instruments aimed to hedge some forms of risk that is not traded on financial markets. The idea is to minimize the risk of the issuer under the constraint imposed by a buyer who enters the transaction if and only if her risk level remains...

We introduce the notion of a convex measure of risk, an extension of the concept of a coherent risk measure defined in Artzner et al. (1999), and we prove a corresponding extension of the representation theorem in terms of probability measures on the underlying space of scenarios. As a case...

The classes of reward-risk optimization problems that arise from different choices of reward and risk measures are considered. In certain examples the generic problem reduces to linear or quadratic programming problems. An algorithm based on a sequence of convex feasibility problems is given for...

Recent and presumable future developments tend to increase the risk associated with farming activities. This causes an increasing importance of risk management. Farmers have a wide variety of possibilities to influence the risk exposure of their operations. Among them are the choice of the...

This paper has considered a risk measure ? and a (maybe incomplete and/or imperfect) arbitrage-free market with pricing rule p. They are said to be compatible if there are no reachable strategies y such that p (y) remains bounded and ?(y) is close to - 8. We show that the lack of compatibility...

The data envelopment analysis (DEA) method is a mathematical programming approach to evaluate the relative performance of portfolios. Considering that the risk input indicators of existing DEA performance evaluation indices cannot reflect the pervasive fat tails and asymmetry in return...

Modeling risk in a prescriptively plausible way represents a major issue in decision theory. The benchmarking procedure, being based on the satisficing principle and providing a probabilistic interpretation of expected utility (EU) theory, is prescriptive. Because it is a target-based language,...