• Title/Summary/Keyword: The First-Order Stochastic Dominance

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An Efficient Algorithm to Find Portfolio Weights for the First Degree Stochastic Dominance with Maximum Expected Return (1차 확률적 지배를 하는 최대수익 포트폴리오 가중치의 탐색에 관한 연구)

  • Ryu, Choon-Ho
    • Journal of the Korean Operations Research and Management Science Society
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    • v.34 no.4
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    • pp.153-163
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    • 2009
  • Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

Optimizing Portfolio Weights for the First Degree Stochastic Dominance with Maximum Utility (1차 확률적 지배를 하는 최대효용 포트폴리오 가중치의 탐색에 관한 연구)

  • Ryu, Choonho
    • Journal of the Korean Operations Research and Management Science Society
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    • v.39 no.1
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    • pp.113-127
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    • 2014
  • The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

Stochastic thermo-mechanically induced post buckling response of elastically supported nanotube-reinforced composite beam

  • Chaudhari, Virendra Kumar;Shegokar, Niranjan L.;Lal, Achchhe
    • Advances in aircraft and spacecraft science
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    • v.4 no.5
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    • pp.585-611
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    • 2017
  • This article covenants with the post buckling witticism of carbon nanotube reinforced composite (CNTRC) beam supported with an elastic foundation in thermal atmospheres with arbitrary assumed random system properties. The arbitrary assumed random system properties are be modeled as uncorrelated Gaussian random input variables. Unvaryingly distributed (UD) and functionally graded (FG) distributions of the carbon nanotube are deliberated. The material belongings of CNTRC beam are presumed to be graded in the beam depth way and appraised through a micromechanical exemplary. The basic equations of a CNTRC beam are imitative constructed on a higher order shear deformation beam (HSDT) theory with von-Karman type nonlinearity. The beam is supported by two parameters Pasternak elastic foundation with Winkler cubic nonlinearity. The thermal dominance is involved in the material properties of CNTRC beam is foreseen to be temperature dependent (TD). The first and second order perturbation method (SOPT) and Monte Carlo sampling (MCS) by way of CO nonlinear finite element method (FEM) through direct iterative way are offered to observe the mean, coefficient of variation (COV) and probability distribution function (PDF) of critical post buckling load. Archetypal outcomes are presented for the volume fraction of CNTRC, slenderness ratios, boundary conditions, underpinning parameters, amplitude ratios, temperature reliant and sovereign random material properties with arbitrary system properties. The present defined tactic is corroborated with the results available in the literature and by employing MCS.