Cross‐commodity analysis and applications to risk management

The understanding of joint asset return distributions is an important ingredient for managing risks of portfolios. Although this is a well‐discussed issue in fixed income and equity markets, it is a challenge for energy commodities. In this study we are concerned with describing the joint return distribution of energy‐related commodities futures, namely power, oil, gas, coal, and carbon. The objective of the study is threefold. First, we conduct a careful analysis of empirical returns and show how the class of multivariate generalized hyperbolic distributions performs in this context. Second, we present how risk measures can be computed for commodity portfolios based on generalized hyperbolic assumptions. And finally, we discuss the implications of our findings for risk management analyzing the exposure of power plants, which represent typical energy portfolios. Our main findings are that risk estimates based on a normal distribution in the context of energy commodities can be statistically improved using generalized hyperbolic distributions. Those distributions are flexible enough to incorporate many characteristics of commodity returns and yield more accurate risk estimates. Our analysis of the market suggests that carbon allowances can be a helpful tool for controlling the risk exposure of a typical energy portfolio representing a power plant. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:197–217, 2009     

Abgabenlast in Deutschland: Ist die Höhe oder die Messung das Problem?

„Niedriger, einfacher, gerechter“ — unter diesen drei Schlagworten wird in der Politik eine grundlegende Reform des deutschen Steuersystems diskutiert. Die Forderung nach niedrigeren Steuern wird im Allgemeinen damit begründet, dass die Abgabenbelastung hierzulande vergleichsweise hoch sei. Internationale Vergleiche k?nnen diesen Befund sowohl best?tigen als auch widerlegen — je nachdem, wie die Belastung berechnet wird. Im vorliegenden Beitrag werden drei h?ufi g verwendete Messkonzepte vorgestellt und diskutiert.     

Intention and behavior: a Bayesian meta-analysis with focus on the Ajzen–Fishbein Model in the field of environmental behavior

We employ a Bayesian normal hierarchical model to investigate the relationship between intention and behavior as it is posited by Ajzen and Fishbein’s theory of planned behavior (TPB). Area of application is the field of environmental behavior. Eleven studies reporting correlations between intention and behavior were identified. Our Bayesian hierarchical model expects a correlation of r _xy = 0.54 between those variables. This effect size is above average with regard to meta-analyses, which include other, non-environmental areas of application.     

Representation of concave distortions and applications

ABSTRACT

A family of concave distortion functions is a set of concave and increasing functions, mapping the unity interval onto itself. Distortion functions play an important role defining coherent risk measures. We prove that any family of distortion functions which fulfils a certain translation equation, can be represented by a distribution function. An application can be found in actuarial science: moment-based premium principles are easy to understand but in general are not monotone and cannot be used to compare the riskiness of different insurance contracts with each other. Our representation theorem makes it possible to compare two insurance risks with each other consistent with a moment-based premium principle by defining an appropriate coherent risk measure.