Description: This paper outlines a risk measurement framework in which risk measures are derived by qualifying cash-flow-based risk measures on the state of the firm's debt capacity. This risk framework overcomes some of the weaknesses of the popular 'at-risk' framework. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: This article sees enterprise risk management as a specific application of knowledge in Order to control deviations from strategic objectives, shareholders’ values and stakeholders’ relationships. Before and after a modeling process it is necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a proposed methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

Description: The intent of this paper is the analysis of the influence of risk that took place during winter and summer 2006 on economic results of utilities selling power to final customers. Efficient risk management requires the restructuring of the approach to company management. From 2007 Enterprise Risk Management Symposium, M-AS07-1.

Description: The paper argues that Risks Evaluation at its core is a psychological process that can lead to the special type of chaos described in modern Chaos Theory. It will argue that quantification and scientific modeling does not exempt risk assessment from the potential for deep biases. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: There have been continual advances in the modeling of financial series but most are aimed at the pricing of derivatives. Different criteria are needed for development of scenarios for risk management. Some recent methods will be reviewed with an eye on risk-management applications, including using the simulated method of moments to parameterize multifactor models, fractional differencing and other methods to model series with persistent autocorrelation, and models to flatten out the volatility smile, such as jump-diffusion models. These methods will be illustrated with applications to inflation, interest rates, equity prices and exchange rates.