The development of risk management methodologies for non-gaussian markets relies often on the assumption that the underlying market factors have a gaussian distribution. While advances have been made in the modeling of more general marginal distributions of the risk factors, the modeling of non-gaussian dependence structures is much less advanced. For commodities markets that often exhibit sudd...

We consider the problem of distributing goods from one or more plants through a set of warehouses in anticipation of forecasted customer demands. Two results are provided in this paper. First, we present a methodology for approximating stochastic distribution problems that are computationally tractable for problems of realistic size. Comparisons are made to standard deterministic formulations a...

The shift from version 9 to version 10 of the ICD-code (“International Statistical Classification of Diseases and Related Health Problems”) causes enormous problems for the exploitation of medical data warehouses, since conventional data warehouses do not support the change of the structure of dimensions, i.e. the content and relationships of master data like the diagnostic codes, or other key ...

Data Warehouses and on-line analytical processing (OLAP) systems are a promising area for the application of Abstract State Machines (ASMs). In this paper a ground model specification for data warehouses is sketched that is based on the fundamental idea of separating input from operational databases and output to OLAP systems. On this basis we start defining formal refinement rules for such sys...

Data warehouses are users driven; that is, they allow end-users to be in control of the data. As user satisfaction is commonly acknowledged as the most useful measurement of system success, we identify the underlying factors of end-user satisfaction with data warehouses and develop an instrument to measure these factors. The study demonstrates that most of the items in classic end-user satisfac...

I. ABSTRACT How large are data warehouses? How fast are they growing? How big are they going to get? What is driving their growth? Why is all this data of value in commercial enterprises? What can we say about how these large data warehouses are being used? What are some key challenges ahead? In this talk, Richard Winter will share his views and observations concerning these questions and other...

Data Warehouses are a crucial technology for current competitive organizations in the globalized world. Size, speed and distributed operation are major challenges concerning those systems. Many data warehouses have huge sizes and the requirement that queries be processed quickly and efficiently, so parallel solutions are deployed to render the necessary efficiency. Distributed operation, on the...

Asymmetric GARCH models were developped for equity stocks to take into account the larger response of the conditional variance to negative price shocks. We show that these asymmetric GARCH models are also relevant for modelling commodity prices. Contrary to the equity case, positive shocks are the main contributors to the conditional variance of commodity prices. The theory of storage, by relat...