Titlebook: Dynamic Stochastic Optimization; Kurt Marti,Yuri Ermoliev,Georg Pflug Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 2004 A

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Approximation and Optimization for Stochastic Networksions in place of most of the simulation runs required in the conventional approach. We present a simple example of balancing an airlift network, in which this approach successfully solves the problem in much less time than simulation would have required. We also discuss further work currently in progress to refine and extend this approach.

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Estimating LIBOR/Swaps Spot-Volatilities: the EpiVolatility Modelare interested in being able to estimate spot volatilities for time steps of arbitrary length. Further, this technique does not assume any particular form for the volatility function of forward Libor rates. We propose a new approach based on Approximation Theory and develop an optimization procedure that has been implemented at EpiSolutions Inc.

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Perturbation Analysis of Chance-constrained Programs under Variation of all Constraint Dataon . and . ∈ (0, 1) is some probability level. In the simplest case of linear chance constraints, . is linear, . is a polyhedron and .(.) = {. ∈ ?.|. ≥ .} , where A is a matrix of order (.) and the inequality sign has to be understood component-wise.

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Meinungspotential von Wirtschaftswerbungumption of non-anticipativity and the (unrealistic) assumption of clairvoyance..This comparison allows to define a value of information. We argue that this value of information may serve as a measure of risk, derive properties and finally study the stochastic process generated by this risk measure.

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Optimal Solutions for Undiscounted Variance Penalized Markov Decision Chains] on mean variance selection rules for the portfolio selection problem. Following the mean variance selection rule, the investor selects from among a given set of investment alternatives only investments with a higher mean and lower variance than a member of the given set.

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