Omar Andrés Carmona Cortes

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In this paper, we study from the perspective of an insurance company the Reinsurance Contract Placement problem. Given a reinsur-ance contract consisting of a fixed number of layers and a set of expected loss distributions (one per layer) as produced by a Catastrophe Model, plus a model of current costs in the global reinsurance market, identifying optimal(More)
Risk hedging strategies are at the heart of financial risk management. As with many financial institutions, insurance companies try to hedge their risk against potentially large losses, such as those associated with natural catastrophes. Much of this hedging is facilitated by engaging in risk transfer contracts with the global reinsurance market. Devising(More)
—In this paper we propose MO-PBIL, a parallel multidimensional variant of the Population Based Incremental Learning (PBIL) technique that executes efficiently on both multi-core and many-core architectures. We show how MO-PBIL can be used to address an important problem in Reinsurance Risk Analytics namely the Reinsurance Contract Optimization problem. A(More)
—The purpose of this paper is to evaluate the performance of Vector Evaluated Differential Evolution (VEDE) and Vector Evaluated Particle Swarm Optimization (VEPSO) in solving a real world financial optimization problem. The algorithms have been applied to the Reinsurance Contract Problem, which is a challenging problem in computational finance, and their(More)
The primary angiitis of the central nervous system (PACNS) is an entity with a very low incidence and prevalence. It is not clear why the inflammatory process of this entity is limited to the cerebral vasculature without systemic manifestations. Its clinical manifestations are very heterogeneous and make clinical diagnosis difficult. In most cases, a brain(More)