Portfolio Selection Using Stochastic Dominance Criteria

The direct application of stochastic dominance criteria to portfolio selection problems has been thought impractical because an extremely large number of combinations of returns must be considered. This paper proposes and evaluates a rigorous statistical procedure for sampling the combinations of returns on candidate risky assets so that stochastic dominance criteria may be used directly in an efficient linear programming model for portfolio selection. The sampling scheme exploits the association of the return on each candidate stock with the return on a market index in a manner analogous to the Sharpe single-index model, thereby eliminating the large number of combinations with probabilities close to or equalling zero. Portfolios computed by the proposed linear programming stochastic dominance model are compared with those computed by the single-index quadratic programming model, using 180 months of recent data on a sample of NYSE common stocks.     

基于限制优势关系的粗糙决策分析模型

针对信息不完全的偏好多属性决策问题,给出一种基于拓展粗糙集的决策分析模型.首先提出限制优势关系的概念;然后在限制优势关系下得到知识的粗糙近似,给出分类决策规则.对比分析证明,限制优势关系既保留了扩展优势关系的优点,又在一定程度上克服了扩展优势关系的局限性.最后通过一个实例验证了所提出的模型对信息不完备决策系统的处理更符合实际情况。     

多标准决策表中发现概率规则的变精度粗糙集方法

用优势关系代替不可分辨关系,本文提出了一种可以从多标准决策表中获取概率规则的扩展变精度粗糙集模型,该模型能够处理多标准决策表中可能的不一相容性,获取由偏好对象组成的概率决策规则集,并导出事例决策系统的偏好模型。研究结果表明:基于优势关系,从多标准决策表中获取的最小概率规则集,使用的条件数量较少,且导出规则的数量较少、较强。     

Avoiding Covid-19 risk information in the United States: The role of attitudes,norms, affect,social dominance orientations,and perceived trustworthiness of scientists

This study seeks guidance from the planned risk information avoidance model to explore drivers of risk information avoidance in the context of COVID-19. Data were collected early during the pandemic. Among our most notable results is that participants who are more oriented toward social dominance and are more skeptical of scientists’ credibility have (1) more supportive attitudes toward risk information avoidance and (2) feel social pressure to avoid risk information. The findings of this study highlight how the role of skepticism in science and intergroup ideologies, such as social dominance, can have important implications for how people learn about health-related information, even in times of heightened crisis.     

A STOCHASTIC DOMINANCE ORDERING OF SCHEDULING RULES

This paper applies stochastic dominance (SD) preference-ordering criteria to job shop scheduling rules. A simulation model of a hypothetical dual-constrained job shop is used to derive several measures of shop performance for a number of dispatching/due-date scheduling policies. The results presented suggest that previous research conclusions concerning the relative performance of dispatching scheduling rules may need to be reconsidered if production schedulers are risk-averse utility maximizers.     

Dominance intensity measure within fuzzy weight oriented MAUT: An application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.     

Decision making with stochastic dominance: An expository review

This paper surveys the use of stochastic dominance to decision making under uncertainty. The first part presents the relevant definitions and some properties of distributions satisfying one of the stochastic dominance conditions. These properties include restrictions on moments, an invariance property, and properties of random variables related by an exact formula.The second part contains some applications of the stochastic dominance method and especially the problem of selecting optimal portfolios. Most of the results in this section deal with conditions that make diversification an optimal strategy.     

Learning‐by‐Doing,Organizational Forgetting,and Industry Dynamics

Learning‐by‐doing and organizational forgetting are empirically important in a variety of industrial settings. This paper provides a general model of dynamic competition that accounts for these fundamentals and shows how they shape industry structure and dynamics. We show that forgetting does not simply negate learning. Rather, they are distinct economic forces that interact in subtle ways to produce a great variety of pricing behaviors and industry dynamics. In particular, a model with learning and forgetting can give rise to aggressive pricing behavior, varying degrees of long‐run industry concentration ranging from moderate leadership to absolute dominance, and multiple equilibria.     

A STOCHASTIC DOMINANCE ALGORITHM USING PIECEWISE LINEAR APPROXIMATIONS

Current stochastic dominance algorithms use step functions to approximate the cumulative distributions of the alternatives, even when the underlying random variables are known to be continuous. Since stochastic dominance tests require repeated integration of the cumulative distribution functions, a compounding of errors may result from this type of approximation. This article introduces a new stochastic dominance algorithm that approximates the cumulative distribution function by piecewise linear approximations. Comparisons between the new and old algorithms are performed for normally distributed alternatives. In about 95 percent of all cases, the two algorithms produce the same result.     

Probabilistic dominance criteria for comparing uncertain alternatives: A tutorial

This paper is a tutorial which demonstrates the current state-of-the-art methods for incorporating risk into project selection decision making. The projects under consideration might be R&D, IT, or other capital expenditure programs. We will show six decision making methods: 1. mean-variance (MV), 2. mean-semivariance, 3. mean-critical probability, 4. stochastic dominance, 5. almost stochastic dominance (ASD), and 6. mean-Gini. We will also describe the assumptions about the risk attitudes of the decision maker which are associated with each of the techniques. While all these methods have been previously applied elsewhere, this is the first paper which shows all of their applications in the project selection context, together with their interrelationships, strengths and weaknesses. We have applied all six techniques to the same group of five hypothetical projects and evaluated the resulting nondominated sets. Among the methods reviewed here, stochastic dominance is recommended because it requires the least restrictive assumptions. ASD and mean-Gini are recommended when stochastic dominance is not practical or when it does not yield definitive choices. MV, mean-semivariance, and mean-critical probability are shown to be flawed.     

一个非对称风险度量模型及组合证券投资分析

在分析Jia&Dyer的风险-价值理论基础上,给出了一个基于预先给定的目标收益的非对称风险函数。该风险函数是低于参考点的离差和高于参考点的离差的加权和,它利用一阶"上偏矩"来修正二阶下偏矩,进一步建立了在此非对称风险函数下的二次规划组合证券投资模型;并证明了该模型与三阶随机占优准则的一致性;最后通过上海证券市场的实际数据验证了该模型的有效性和实用性。     

Selecting a Portfolio of Technologies: An Application of Decision Analysis

The Department of Energy is faced with the critical and complex decision of selecting technologies for waste site remediation. This research focuses on developing a decision support tool which assists the decision maker to find an optimal portfolio. A portfolio consists of selecting the appropriate processes for a remediation site and, subsequently, selecting a technology for each process so that the decision maker's objectives are achieved. The measures supporting the objectives are risk, life-cycle cost, and time required for remediation. The model uses exponential attribute utility functions with an additive objective function. The model provides the decision maker with estimates of the cost and time distributions, and their associated utility. Cumulative frequency distributions illustrate the dominance of technology choices and the variance in the results. The model permits sensitivity analysis in the form of rainbow and tornado diagrams to display the effects of changes in the values of the input variables. Overall, the model provides a generic technology selection tool that can be used to make better informed decisions and may be easily manipulated to reflect changes in the remediation process.     

The Chimera of Sustainable Labour–Management Partnership

The paper advances a threefold theoretical contribution using a system, society and dominance (SSD) effects framework to show how and why sustainable management–labour workplace partnerships are a chimera. First, managers (employers) find it increasingly difficult to keep workplace bargains with employees (unions) owing to increasingly neoliberal ‘system’ effects associated with capitalism as a globalized accumulation model. Second, workplace mutuality will be rare because of ‘societal’ level effects under voluntarism. Third, ‘dominance’ effects arising from the power of dominant economies and their multinational corporations can inhibit workplace mutuality. Drawing on empirical case study data from Ireland, the future prognosis of management–labour collaboration under neoliberal work regimes is discussed.     

知识的分类及其管理

知识管理是一个寻求数据和信息处理能力与员工的创造和革新能力协作组合的组织过程,其目的是为了提高企业应付外界环境变化的适应、生存和竞争能力。但是,由于知识具有多样性、复杂性和动态性等特征,试图通过一种模式来实施对知识的有效管理是不现实的,也是不可能的。企业要有效地管理知识,应在对企业知识进行分类的基础上,根据企业的经营目标,采取相应的管理策略,因此归纳了5种分类方法显性知识和隐性知识、内部知识和外部知识、个人知识和组织知识、实体知识和过程知识、核心知识和非核心知识,并时各种分类提出了相应的管理策略。     

Impacts of demand uncertainty on retailer's dominance and manufacturer-retailer supply chain cooperation

Recent studies in marketing and distribution channels have shown that the balance of power between manufacturers and retailers is shifting. Based on this observation, we investigate a two-echelon supply chain with a manufacturer and a retailer in this paper. We first develop retailer-dominant non-cooperative game models by introducing a sensitivity of retailer's order quantity to manufacturer's wholesale price; then we analyze two cooperative scenarios, in which the Nash bargaining model is utilized to implement profit sharing between the manufacturer and the retailer. Under the assumption that the manufacturer and the retailer are risk-neutral, we find that the manufacturer and the retailer can bargain to cooperate at any level of retail-market demand uncertainty with exogenous retail price. However, the cooperation is conditional on retail-market demand uncertainty with endogenous retail price: it can be implemented if the fluctuation of retail-market demand is relatively small, and the measure of retail-market demand uncertainty does not exceed an upper bound. Theoretical and numerical analyses show that the retailer's dominance over the manufacturer increases with the increase in the sensitivity of retailer's order quantity to manufacturer's wholesale price under a limitation of retail-market demand uncertainty. Numerical analyses also show that the retailer's dominance decreases with the increase in retail-market demand uncertainty.     

Managing a Low-Incidence Risk: The Example of Toxic Shock Syndrome

This article demonstrates a methodology that allows individuals to reach a personal decision on the use of products which carry very small risks to health and life but also offer considerable benefits. A combination of the principles of dominance, extended dominance, and various methods of direct risk-benefit tradeoffs are shown to reduce the number of possible decisions regarding product use to the one optimal for the value structure of a particular individual. An historical examination of toxic-shock syndrome identifies tampons as a product with risks too small to warrant public intervention but too sizeable to be ignored. The methodology described here can be applied for all such products.     

Risk Averse Decisions in Business Planning

Second-order stochastic dominance is used to determine preferences among various investments for any risk-averse decision maker. On the other hand, when faced with choosing between different insurance policies or disaster plans, a risk-averse decision maker should use a type of stochastic dominance called variability ordering. In this situation, second-order stochastic dominance has been used in previous research and is incorrect.     

基于在线评论和随机占优准则的生鲜电商顾客满意度测评

生鲜电商被认为是电子商务领域的下一片蓝海，吸引着各类资本、平台竞相追逐，但目前生鲜电商仍处于发展探索阶段，如何及时准确地把握顾客需求和有效地提升顾客满意度是当前面临的重要问题。本文提出一种基于在线评论和随机占优准则的生鲜电商顾客满意度测评方法：首先，利用生鲜电商存在的大量在线评论数据信息，基于LDA模型提取出在线评论中的主题，作为顾客对生鲜电商满意度的影响因素；其次，构建生鲜电商顾客需求的情感词典，计算在线评论中顾客的情感倾向得分，作为判断顾客满意度的依据；最后，利用随机占优准则，构建不同商品类别中影响因素的随机占优程度矩阵，并应用PROMETHEE-Ⅱ方法给出不同商品类别中影响因素的排序结果。通过爬取天猫网站中不同类别的生鲜商品在线评论信息进行顾客满意度评估的案例分析，验证本文提出的方法的可行性和有效性。结果显示，不同生鲜商品类别中顾客满意度影响因素的重要度排序是不同的。值得注意的是，所提方法也为其他产品或服务的顾客满意度评估问题提供了参考和支撑。     

Decision theory,linear partial information and statistical dominance

The paper deals with decision making under conditions of linear partial information, i.e. when probabilities of states of nature are not known precisely, but are subject to linear constraints. Conditions ensuring strict and weak statistical dominance of one strategy over another are derived. It is also shown that weak dominance in terms of payoffs is equivalent to weak dominance in terms of regrets. The new results are more general than those obtained by Fishburn and by Kmietowicz and Pearman for weak and strict ranking of probabilities, and include them as special cases. The new results can be employed in practical decision making in several ways.     

Single machine scheduling: A comparison of two solution procedures

Recent research on the single machine scheduling problem has focused on the treatment of multiple scheduling objectives. Most works have used some combination of mean flowtime, maximum tardiness, or total tardiness as scheduling criteria. Previous research has largely ignored earliness as a scheduling criterion. This paper presents a model that employs the criteria of flowtime as a measure of work-in-process (WIP) inventory and total job earliness to represent finished goods inventory. Total tardiness is used to represent customer satisfaction. The three criteria are used to form a single, weighted-sum objective function for guiding the choice of the best processing sequence. Two procedures are presented that might be used to solve this problem. The first is an enumeration scheme using bounding and dominance criteria that have been developed to aid efficient solution, and the second is a mixed integer linear programming (LP) formulation. Computational experience with the two models is also presented.