Effort maximization in asymmetric contest games with heterogeneous contestants

Contest rules are set up by administrators who frequently have discretionary power in specifying the details of these rules, i.e., they can bias the contest rules toward specific contestants in order to further their prime objective. We derive the optimal bias of the contest rule for a contest administrator, who is interested in maximizing the total efforts expended in the contest. The solution is obtained in closed form for a widely used class of n-person contest games. Setting the optimal bias has important implications: (i) there is never exclusion of strong players, instead there is (endogenously induced) inclusion of weak contestants; (ii) the contest administrator will optimally level the playing field by encouraging weak contestants, but he will not equalize the contestants’ chances unless they are identical; and (iii) at least three contestants will be active in equilibrium of the optimal contest, irrespective of heterogeneity.     

Portfolio optimization in a defaultable market under incomplete information

We consider the problem of maximization of expected utility from terminal wealth in a market model that is driven by a possibly not fully observable factor process and that takes explicitly into account the possibility of default for the individual assets as well as contagion (direct and information induced) among them. It is a multinomial model in discrete time that allows for an explicit solution. We discuss the solution within our defaultable and partial information setup, in particular we study its robustness. Numerical results are derived in the case of a log-utility function, and they can be analogously obtained for a power utility function.     

On the structure and estimation of hierarchical Archimedean copulas

In this paper we provide a method for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general, the true structure of the hierarchy is unknown, but we develop a computationally efficient technique to determine it from the data. For this purpose we introduce a hierarchical estimation procedure for the parameters and provide an asymptotic analysis. We consider both parametric and nonparametric estimation of the marginal distributions. A simulation study and an empirical application show the effectiveness of the grouping procedure in the sense of structure selection.     

Asymptotic behavior of the estimated weights and of the estimated performance measures of the minimum VaR and the minimum CVaR optimal portfolios for dependent data

In this paper we derive the asymptotic distributions of the estimated weights and of estimated performance measures of the minimum value-at-risk portfolio and of the minimum conditional value-at-risk portfolio assuming that the asset returns follow a strictly stationary process. It is proved that the estimated weights as well as the estimated performance measures are asymptotically multivariate normally distributed. We also present an asymptotic test for the weights and a joint test for the characteristics of both portfolios. Moreover, the asymptotic densities of the estimated performance measures are compared with the corresponding exact densities. It is shown that the asymptotic approximation performs well even for the moderate sample size.     

Discovering the “customer annoyance iceberg” through evidence controlling

There is no doubt about the relevance of complaint management for customer retention. But complaint management-objectives can only be achieved if complaints registered by the firm give a comprehensive view of the annoyances perceived by customers. In fact, a considerable share of annoyed customers do not complain and many complaint articulations are not registered. Because of these “unvoiced” and “hidden” complaints, registered complaints show only the tip of the “annoyance iceberg” leading to misinterpretations and wrong allocation decisions. As a countermeasure, the concept of evidence-controlling is developed in this paper. Relevant key figures are identified, effective information gathering is demonstrated and managerial implications and open research questions are discussed.