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  • In this paper we propose multivariate stochastic orderings of risk positions that are consistent with the preferences of investors. Since investors maximize an expected state-dependent utility function, we analyze stochastic orderings that take into account of possible investors' benchmarks. We begin by analyzing the links among continua stochastic dominance orders, survival and inverse stochastic dominance rules. Then we tie together the consistency-isotonicity of risk and reward multivariate measures with classical orderings and we show how risk/variability multivariate measures are used to obtain non dominated choices. In second analysis we discuss an extension of the classical orderings using probability functionals that satisfy an opportune identity property and the basic rules of the theory of integral stochastic orders. In the discussion we propose several examples that clarify the main developments of the proposed analysis. In particular we describe new multivariate orderings that are consistent with a particular ordering of preferences. We discuss how to better distinguish and classify the multivariate choices using the fractional integral properties. We draw upon a recent classi cation of risk measures and orderings that is based on the theory of probability metrics. Employing the techniques of probability metrics theory, we then present further extensions and representations of probability functionals which are consistent with classic and dual orderings. Finally, we analyze some potential applications in nance of the new orderings.
  • In this paper we propose multivariate stochastic orderings of risk positions that are consistent with the preferences of investors. Since investors maximize an expected state-dependent utility function, we analyze stochastic orderings that take into account of possible investors' benchmarks. We begin by analyzing the links among continua stochastic dominance orders, survival and inverse stochastic dominance rules. Then we tie together the consistency-isotonicity of risk and reward multivariate measures with classical orderings and we show how risk/variability multivariate measures are used to obtain non dominated choices. In second analysis we discuss an extension of the classical orderings using probability functionals that satisfy an opportune identity property and the basic rules of the theory of integral stochastic orders. In the discussion we propose several examples that clarify the main developments of the proposed analysis. In particular we describe new multivariate orderings that are consistent with a particular ordering of preferences. We discuss how to better distinguish and classify the multivariate choices using the fractional integral properties. We draw upon a recent classi cation of risk measures and orderings that is based on the theory of probability metrics. Employing the techniques of probability metrics theory, we then present further extensions and representations of probability functionals which are consistent with classic and dual orderings. Finally, we analyze some potential applications in nance of the new orderings. (en)
Title
  • Multivariate stochastic orderings consistent with preferences and their possible applications
  • Multivariate stochastic orderings consistent with preferences and their possible applications (en)
skos:prefLabel
  • Multivariate stochastic orderings consistent with preferences and their possible applications
  • Multivariate stochastic orderings consistent with preferences and their possible applications (en)
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  • RIV/61989100:27510/13:86086864!RIV14-GA0-27510___
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  • P(ED1.1.00/02.0070), P(EE2.3.30.0016), P(GA13-13142S), S
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  • 90196
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  • RIV/61989100:27510/13:86086864
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  • applications; possible; their; and; preferences; with; consistent; orderings; stochastic; Multivariate (en)
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  • [169BF12CE146]
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  • Jihlava
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  • Jihlava
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  • Mathematical Methods in Economics 2013 : 31st international conference : 11-13 September 2013, Jihlava, Czech Republic
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  • Tichý, Tomáš
  • Ortobelli, Sergio Lozza
  • Petronio, Filomena
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number of pages
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  • College of Polytechnics Jihlava
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  • 978-80-87035-76-4
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  • 27510
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