Improved Portfolio Choice Using Second-Order Stochastic Dominance*

Hodder, James E.; Jackwerth, Jens Carsten; Kolokolova, Olga

doi:10.1093/rof/rfu025

Cited by 73 publications

(19 citation statements)

References 25 publications

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“…Related papers are discussed below. Hodder et al (2015) mention that all risk-averse investors tend to choose the SSD and would prefer a dominating portfolio. However, it is still a challenging problem choosing among the SSD efficient portfolios.…”

Section: Literature Reviewmentioning

confidence: 99%

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

Uğurlu¹,

Taş²,

Güran³

et al. 2018

Prague Economic Papers

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The second order stochastic dominance (SSD) has become exceedingly popular in recent years, due to its ability to determine the dominance of one asset over another for all risk-averse investors without a strict requirement in asset distribution. In this study, 33 OECD country indexes and their enriched set of assets, which consists of some combinations of these indexes, are investigated and compared between 2007 and 2015 by utilizing pairwise SSD comparisons, with different data frequencies, such as daily, weekly, monthly and quarterly. This paper contributes to the literature in three points: Firstly, a serious portion of the best performing OECD countries has the lowest GDP (PPP) per capita level. Secondly, the SSD efficient set depends on data frequency. Thirdly, when the data frequency is lowered, the difference between two SSD pairwise efficiency tests decreases.

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Section: Literature Reviewmentioning

confidence: 99%

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

Uğurlu¹,

Taş²,

Güran³

et al. 2018

Prague Economic Papers

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show abstract

“…However, very few people considered applying the thought of stochastic dominant to SCP. Recently, optimization models with stochastic dominance constraints have increasingly been the subject of theoretical considerations and have been applied in many areas such as finance, energy, and transportation; see [8][9][10][11]. Stochastic dominance is one of the popular established ways to formalize preferences among random values.…”

Section: Introductionmentioning

confidence: 99%

A Smoothing Algorithm for a New Two-Stage Stochastic Model of Supply Chain Based on Sample Average Approximation

Liu¹,

Xiong²,

Tong³

2017

Mathematical Problems in Engineering

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We construct a new two-stage stochastic model of supply chain with multiple factories and distributors for perishable product. By introducing a second-order stochastic dominance (SSD) constraint, we can describe the preference consistency of the risk taker while minimizing the expected cost of company. To solve this problem, we convert it into a one-stage stochastic model equivalently; then we use sample average approximation (SAA) method to approximate the expected values of the underlying random functions. A smoothing approach is proposed with which we can get the global solution and avoid introducing new variables and constraints. Meanwhile, we investigate the convergence of an optimal value from solving the transformed model and show that, with probability approaching one at exponential rate, the optimal value converges to its counterpart as the sample size increases. Numerical results show the effectiveness of the proposed algorithm and analysis.

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“…SD rules are widely used to identify SD relations for pairwise comparisons of alternatives under uncertain environment [3,4]. They are robust analytical tools for solving decision making problems under uncertainty [1,5], and have been applied in economics and finance [6,7] because of less restrictive assumptions.…”

Section: Introductionmentioning

confidence: 99%

A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

Sun

et al. 2017

Entropy

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Abstract:Traditional stochastic dominance rules are so strict and qualitative conditions that generally a stochastic dominance relation between two alternatives does not exist. To solve the problem, we firstly supplement the definitions of almost stochastic dominance (ASD). Then, we propose a new definition of stochastic dominance degree (SDD) that is based on the idea of ASD. The new definition takes both the objective mean and stakeholders' subjective preference into account, and can measure both standard and almost stochastic dominance degree. The new definition contains four kinds of SDD corresponding to different stakeholders (rational investors, risk averters, risk seekers, and prospect investors). The operator in the definition can also be changed to fit in with different circumstances. On the basis of the new SDD definition, we present a method to solve stochastic multiple criteria decision-making problem. The numerical experiment shows that the new method could produce a more accurate result according to the utility situations of stakeholders. Moreover, even when it is difficult to elicit the group utility distribution of stakeholders, or when the group utility distribution is ambiguous, the method can still rank alternatives.

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Improved Portfolio Choice Using Second-Order Stochastic Dominance*

Cited by 73 publications

References 25 publications

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

SSD Efficiency at Multiple Data Frequencies: Application on the OECD Countries

A Smoothing Algorithm for a New Two-Stage Stochastic Model of Supply Chain Based on Sample Average Approximation

A New Stochastic Dominance Degree Based on Almost Stochastic Dominance and Its Application in Decision Making

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