Conditional risk measures in a bipartite market structure

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.     

Displaying expected values in risk elicitation tasks: the effect of information in experimental risk research

We investigate the influence of providing expected lottery results to experiment participants in two common risk attitude elicitation tasks. In a between-subject design, either the Holt and Laury task or the Eckel and Grossman task is carried out by a sample of 208 students. We find no significant effect of shown expected values on the risk attitude measured by the tasks. This result even holds true if we divide the experiment participants into specific sub-groups, i.e. female and male, or lower numeracy and higher numeracy participants. Furthermore, comprehension and processing time are not significantly influenced by presented expected values. Therefore, we conclude that providing information on expected values does not influence decision-making in tasks involving risk. This result indicates the robustness of elicited risk attitudes to variation in common experimental methods, and demonstrates that more information could be provided without creating bias in the results.     

Are 18 Holes Enough for Tiger Woods?

This article addresses the selection problem in promotion tournaments. I consider a situation with heterogeneous employees and ask whether an employer might be interested in repeating a promotion tournament. On the one hand, this yields a reduction in uncertainty over the employees’ abilities. On the other hand, there are costs if a workplace stays vacant.     

Cumulative prospect theory and the St. Petersburg paradox

Summary. We find that in cumulative prospect theory (CPT) with a concave value function in gains, a lottery with finite expected value may have infinite subjective value. This problem does not occur in expected utility theory. The paradox occurs in particular in the setting and the parameter regime studied by Tversky and Kahneman [15] and in subsequent works. We characterize situations in CPT where the problem can be resolved. In particular, we define a class of admissible probability distributions and admissible parameter regimes for the weighting- and value functions for which finiteness of the subjective value can be proved. Alternatively, we suggest a new weighting function for CPT which guarantees finite subjective value for all lotteries with finite expected value, independent of the choice of the value function. Some of these results have already been found independently by Blavatskyy [4] in the context of discrete lotteries.Received: 14 October 2004, Revised: 6 May 2005, JEL Classification Numbers: C91, D81.We thank Pavlo Blavatskyy and Thorsten Hens for their helpful remarks regarding our paper. Moreover, we thank the referee for his constructive suggestions. This research was supported by the University Research Priority Program “Finance and Financial Markets” a research instrument of the University of Zürich.     

Maryann P. Feldman,The Geography of Innovation. Economics of Science,Technology and Innovation

Small Business Economics -