Strongly consistent multivariate conditional risk measures

Time Consistent Dynamic Risk Measures

Training Conditional Random Fields with Multivariate Evaluation Measures

This paper proposes a framework for training Conditional Random Fields (CRFs) to optimize multivariate evaluation measures, including non-linear measures such as F-score. Our proposed framework is derived from an error minimization approach that provides a simple solution for directly optimizing any evaluation measure. Specifically focusing on sequential segmentation tasks, i.e. text chunking a...

Some New Classes of Consistent Risk Measures

Many types of insurance premium principles and/or risk measures can be characterized by means of a set of axioms, which in many cases are rather arbitrarily chosen and not always in accordance with economic reality. In the present paper we generalize Yaari’s risk measure by relaxing his axioms. In addition, we derive translation invariant minimal Orlicz risk measures, which we call Haezendonck ...

SSD Consistent Criteria and Coherent Risk Measures

The mean-risk approach quantifies the problem of choice among uncertain prospects in a lucid form of only two criteria: the mean, representing the expected outcome, and the risk: a scalar measure of the variability of outcomes. The model is appealing to decision makers but it may lead to inferior conclusions. Several risk measures, however, can be combined with the mean itself into the robust o...

Conditional and dynamic convex risk measures

We extend the definition of a convex risk measure to a conditional framework where additional information is available. We characterize these risk measures through the associated acceptance sets and prove a representation result in terms of conditional expectations. As an example we consider the class of conditional entropic risk measures. A new regularity property of conditional risk measures ...