Antonio Heras Martínez, Ana García Aguado (1998)
Revista de la Real Academia de Ciencias Exactas Físicas y Naturales
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In this article we discuss several alternative formulations for Stochastic Goal Programming. Only one of these models, which is a particular case of the Stochastic Programs with Recourse, is also compatible with Bayesian Decision Theory. Moreover, it is posible to approximate its solutions by means of an iterative algorithm.
Helgard Raubenheimer, Machiel F. Kruger (2010)
Kybernetika
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Maintaining liquid asset portfolios involves a high carry cost and is mandatory by law for most financial institutions. Taking this into account a financial institution's aim is to manage a liquid asset portfolio in an “optimal” way, such that it keeps the minimum required liquid assets to comply with regulations. In this paper we propose a multi-stage dynamic stochastic programming model for liquid asset portfolio management. The model allows for portfolio rebalancing decisions over...
Laureano F. Escudero (1998)
Revista de la Real Academia de Ciencias Exactas Físicas y Naturales
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We present a model1ing framework for multistage planning problems under uncertainty in the objective function coefficients and right-hand-side. A multistagy scenario analysis scheme with partial recourse is used. So, the decisíon polícy can be implemented for a given set of initial time periods (so-called implementable time stage), such that the solution for the other periods lioes not need' to be anticipated and, then, it depends upon the scenario group to occur at each stage. In any...
A. Alonso-Ayuso, L. F. Escudero, M.T. Ortuño (2007)
SORT
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We present a modelling framework for two-stage and multi-stage mixed 0-1 problems under uncertainty for strategic Supply Chain Management, tactical production planning and operations assignment and scheduling. A scenario tree based scheme is used to represent the uncertainty. We present the Deterministic Equivalent Model of the stochastic mixed 0-1 programs with complete recourse that we study. The constraints are modelled by compact and splitting variable representations via scenarios. ...
Tomáš Rusý, Miloš Kopa (2018)
Kybernetika
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We build a multi-stage stochastic program of an asset-liability management problem of a leasing company, analyse model results and present a stress-testing methodology suited for financial applications. At the beginning, the business model of such a company is formulated. We introduce three various risk constraints, namely the chance constraint, the Value-at-Risk constraint and the conditional Value-at-Risk constraint along with the second-order stochastic dominance constraint, which...
Łukasz Delong (2012)
Applicationes Mathematicae
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We investigate novel applications of a new class of equations which we call time-delayed backward stochastic differential equations. Time-delayed BSDEs may arise in insurance and finance in an attempt to find an investment strategy and an investment portfolio which should replicate a liability or meet a target depending on the strategy applied or the past values of the portfolio. In this setting, a managed investment portfolio serves simultaneously as the underlying security on which...
Wan, Zhong, Hao, Aiyun, Meng, Fuzheng, Hu, Chaoming (2010)
Journal of Inequalities and Applications [electronic only]
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Jitka Dupačová (2008)
Kybernetika
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In applications of stochastic programming, optimization of the expected outcome need not be an acceptable goal. This has been the reason for recent proposals aiming at construction and optimization of more complicated nonlinear risk objectives. We will survey various approaches to risk quantification and optimization mainly in the framework of static and two-stage stochastic programs and comment on their properties. It turns out that polyhedral risk functionals introduced in Eichorn...