Browsing Stochastic Programming Eprint Series (SPEPS) by Title
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19991220BuchThe Application of Operations Research Techniques to Financial Markets This paper reviews the application of OR to financial markets. After considering reasons for the attractiveness of general finance problems to OR researchers, the main types of financial market problem amendable to OR are ...

20001219BuchThe C 3 theorem and a D 2 algorithm for large scale stochastic integer programming Set convexificationThis paper considers the two stage stochastic integer programming problems, with an emphasis on problems in which integer variables appear in the second stage. Drawing heavily on the theory of disjunctive programming, we ...

20030930BuchThe duality of option investment strategies for hedge funds This paper explores the structure of optimal investment strategies using stochastic programming and duality theory in investment portfolios containing options for a hedge fund manager who attempts to beat a benchmark. ...

20040219BuchThe millionvariable "march" for stochastic combinatorial optimization Combinatorial optimization problems have applications in a variety of sciences and engineering. In the presence of data uncertainty, these problems lead to stochastic combinatorial optimization problems which result in ...

20130409BuchThe Natural Banach Space for Version Independent Risk Measures Risk measures, or coherent measures of risk are often considered on the space $L^\infty$, andimportant theorems on risk measures build on that space. Other risk measures, among themthe most important risk measure – the ...

20000401BuchThe performance of stochastic dynamic and fixed mix portfolio models The purpose of this paper is to demonstrate how to evaluate stochastic programming models, and more specifically to compare two different approaches to asset liability management. The first uses multistage stochastic ...

20090724BuchThe role of information in multiperiod risk measurement Multiperiod risk functionals assign a risk value to a discretetime stochasticprocess $Y = (Y_1 , . . . , Y_T )$. While convexity and monotonicity properties extend ina natural way from the singleperiod case and several ...

19991129BuchThe Sample Average Approximation Method for Stochastic Discrete Optimization In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and consequently the expected value function ...

20001128BuchThe stable nonGaussian asset allocation A comparison with the classical Gaussian approachWe analyze a multistage stochastic asset allocation problem with decision rules. The uncertainty is modeled using economic scenarios with Gaussian and stable Paretian nonGaussian innovations. The optimal allocations under ...

20020213BuchThe stochastic single node service provision problem The service provision problem described in this paper comes from an application of distributed processing in telecommunications networks. The objective is to maximize a service provider's profit from offering computational ...

20050706BuchThe value of multistage stochastic programming in capacity planning under uncertainty This paper addresses a general class of capacity planning problems under uncertainty, which arises, for example, in semiconductor tool purchase planning. Using a scenario tree to model the evolution of the uncertainties, ...

20121123BuchThreshold Boolean Form for Joint Probabilistic Constraints with Random Technology Matrix We develop a new modeling and exact solution method for stochastic programming problems thatinclude a joint probabilistic constraint in which the multirow random technology matrix is discretely distributed. We binarize ...

20000413BuchTime to wealth goals in capital accumulation This paper considers the problem of continuous investment of capital in risky assets over time. Using a Bayesian framework, a model for asset prices is developed where the current price dynamics depend on the history of ...

20040615BuchTreasury management model with foreign exchange exposure In this paper we formulate a model for foreign exchange exposure management and (international) cash management taking into consideration random fluctuations of exchange rates. A vector error correction model (VECM) is ...

20010923BuchTreesparse convex programs Dynamic stochastic programs are prototypical for optimization problems with an inherent tree structure including characteristic sparsity patterns in the KKT systems of interior methods. We propose an integrated modeling ...

20041002BuchTwostage integer programs with stochastic righthand sides A superadditive dual approachWe consider twostage pure integer programs with discretely distributed stochastic righthand sides. We present an equivalent superadditive dual formulation that uses the value functions in both stages. We give two algorithms ...

20050311BuchTwostage stochastic semidefinite programming and decomposition based interior point methods TheoryWe introduce two stage stochastic semidefinite programs with recourse and present a Benders decomposition based linearly convergent interior point algorithm to solve them. This extends the results in Zhao [16] wherein it ...

20091016BuchUncertainties in minimax stochastic programs When using the minimax approach one tries to hedge against the worst possible distribution belonging to a speciﬁed class P. A suitable stability analysis of results with respect to the choice of this class is an important ...

20160905BuchUniformly monotone functions  defiitions, properties, characterizations Quasiconcave functions play an important role in economics and finance as utility functions, measures of risk or other objects used, mainly,in portfolio selection analysis. A special attention is paid to these functions ...

20000131BuchVariablesample methods and simulated annealing for discrete stochastic optimization (revised version)In this paper we study a modifcation of the wellknown simulated annealing method, adapting it to discrete stochastic optimization problems. Our algorithm is based on a variablesample Monte Carlo technique, in which the ...