Optimal Financial Decision Making Under Uncertainty

Giorgio Consigli (), Daniel Kuhn () and Paolo Brandimarte ()
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Giorgio Consigli: University of Bergamo
Daniel Kuhn: École Polytechnique Fédérale de Lausanne
Paolo Brandimarte: Politecnico di Torino

Chapter Chapter 11 in Optimal Financial Decision Making under Uncertainty, 2017, pp 255-290 from Springer

Abstract: Abstract We use a fairly general framework to analyze a rich variety of financial optimization models presented in the literature, with emphasis on contributions included in this volume and a related special issue of OR Spectrum. We do not aim at providing readers with an exhaustive survey, rather we focus on a limited but significant set of modeling and methodological issues. The framework is based on a benchmark discrete-time stochastic control optimization framework, and a benchmark financial problem, asset-liability management, whose generality is considered in this chapter. A wide set of financial problems, ranging from asset allocation to financial engineering problems, is outlined, in terms of objectives, risk models, solution methods, and model users. We pay special attention to the interplay between alternative uncertainty representations and solution methods, which have an impact on the kind of solution which is obtained. Finally, we outline relevant directions for further research and optimization paradigms integration.

Keywords: Stochastic control; Dynamic programming; Multistage stochastic programming; Robust optimization; Distributionally robust optimization; Decision rules; Asset-liability management; Pension fund management (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-41613-7_11

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DOI: 10.1007/978-3-319-41613-7_11

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