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.     

Pervasive 2007: It's about the User

Pervasive computing is as much about the user as it is about the technology. So, the Fifth International Conference on Pervasive Computing emphasized desirability rather than just feasibility. Featured themes included user benefits, human-computer interaction, group and social interactions, context awareness, finding and positioning people and objects, and personal privacy.     

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.     

Action and reason in the theory of Āyurveda

The paper explores the relation between reason and action as it emerges from the texts of āyurveda. Life or Ayus (commonly understood as life-span) is primary subject matter of Ayurveda. Life is a locus of experience, action and disposition. Experiences and actions are differentially determined by dispositions that characterize the organism; otherwise all living organisms will be identical. Ayus of each living being is uniquely individual and remains constant between birth and death. In this journey, upkeep of ayus is the purpose of āyurveda or science of life. Ayurveda is a science of experienced matter as well as of experienced body. The living body is critically dependent on the influx of matter for its upkeep. āyurveda offers a conceptual system to reason about balance and imbalances of the system and the causal role of the material flux through the system. This sensate matter is causally open and makes room for definite causal role for the individual and the effective insertion of the felt-purpose of action. Some of the strengths of Ayurveda are brought forth in the paper such as (a) reasoning out the compatibility between the bodily processes and the selection of the natural products for diet and drug, (b) role for heuristics in medical diagnosis, which takes into cognizance the particularity of each living body and the teleology evident in the very act of diagnostic reasoning. The paper shows that āyurvedic theory is built on experiential datum whereas scientific medical theory is built on experience-independent datum. āyurveda explores causal efficacy of ‘secondary qualities’ whereas scientific medicine explores causal efficacy of ‘primary qualities’. The actionable experiential reasoning is at the foundations of āyurveda whereas modern medical science is ab initio saddled with difficult ‘hiatus theoreticus’ between theory and practice. For Ayurveda it is experience of qualities that discloses behavior of matter. The types of qualities that appear in experience have a special significance for theorizing about the actions of matter with the help of qualities. The paper explores the relation between experience of qualities and the method of science. It shows how efficacy of medical practice is based on the foundational stance of experiential realism in theory. To bring the point home, the paper borrows Aristotalian concepts to show how the relation between phantasm and phronesis is honored in the very theory of āyurveda.     

Creating a Student Centered Learning Environment at the University of Denver

A team of faculty members at the University of Denver changed the learning environment in key courses in the Department of Engineering from predominately teacher centered to student centered. Through this funded project new grading methods were implemented, classrooms were renovated and wired with studio layouts to facilitate learning, the Engineering Circuits Laboratory was rewired and instrumented for automated data acquisition and reporting, and two new pedagogical approaches were developed. At the onset of the project, six goals were established related to student learning. The introduction of industry standard hardware and software provided students with unprecedented hands‐on experience and project related activities stimulated faculty innovations in other current and future courses. Assessment results indicate that the new grading system improved the clarity of expectations for students before assignments were given resulting in increased reported motivation for learning in many courses. Even though course GPAs did not always reflect higher achievement on graded work, faculty members firmly believe that deeper understanding was achieved because more complex material was assimilated.