VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

Domain-Driven, Actionable Knowledge Discovery

Data mining increasingly faces complex challenges in the real-life world of business problems and needs. The gap between business expectations and R&D results in this area involves key aspects of the field, such as methodologies, targeted problems, pattern interestingness, and infrastructure support. Both researchers and practitioners are realizing the importance of domain knowledge to close this gap and develop actionable knowledge for real user needs.     

Applications of the discrete element method in mechanical engineering

Compared to other fields of engineering, in mechanical engineering, the Discrete Element Method (DEM) is not yet a well known method. Nevertheless, there is a variety of simulation problems where the method has obvious advantages due to its meshless nature. For problems where several free bodies can collide and break after having been largely deformed, the DEM is the method of choice. Neighborhood search and collision detection between bodies as well as the separation of large solids into smaller particles are naturally incorporated in the method. The main DEM algorithm consists of a relatively simple loop that basically contains the three substeps contact detection, force computation and integration. However, there exists a large variety of different algorithms to choose the substeps to compose the optimal method for a given problem. In this contribution, we describe the dynamics of particle systems together with appropriate numerical integration schemes and give an overview over different types of particle interactions that can be composed to adapt the method to fit to a given simulation problem. Surface triangulations are used to model complicated, non-convex bodies in contact with particle systems. The capabilities of the method are finally demonstrated by means of application examples. Commemorative Contribution.     

The incompatibility of knowledge regimes: consequences of the material world for cross-domain work

In this paper, we argue that successful integration of knowledge across work domains in the short-term can mask the generation of long-term consequences. We explore a setting, the introduction of environmental considerations into semiconductor manufacturing, where the eventual adoption of common measurement artifacts and associated practices enabled knowledge integration, but failed to address significant underlying consequences. Drawing from observational, interview, and archival data we develop an understanding of the work practices of the Tech and EnviroTech groups as structured by the material world and broader collective conventions. We introduce the concept of knowledge regime to outline the differences in knowledge across these work domains. More specifically, we find that differences in the causal specificity and developmental time horizon of knowledge and the measurement artifacts that result contribute to the relative power of one knowledge regime over another. Understanding these sources of incompatibility provides insight into the design requirements of information systems as boundary objects for knowledge integration, but also specifies the potential limits to any design effort.