On Imposing ESG Constraints of Portfolio Selection for Sustainable Investment and Comparing the Efficient Frontiers in the Weight Space

Sustainable investment is typically fulfilled by screening of environmental, social, and governance (ESG); the screening strategies are practical and expedite sustainable-investment development. However, the strategies typically build portfolios by a list of good stocks and ignore portfolio completeness. Moreover, there has been limited literature to study the portfolio weights of sustainable investment in the weight space. In such an area, this article contributes to the literature as follows: We extend a conventional portfolio-selection model and impose ESG constraints. We analytically solve our model by computing the efficient frontier and prove that the frontier’s portfolio weights all lie on a ray (half line). By the ray structure, we prove that portfolio selection for sustainable investment and conventional portfolio selection fundamentally possess highly different portfolio weights. Overall, our aim is comparing the portfolio weights of sustainable portfolio selection and of conventional portfolio selection; the comparison result has been unknown until now. The result is important for sustainable investment because portfolio weights are the foundation of portfolio selection and investments. We sample the component stocks of Dow Jones Industrial Average Index from 2004 to 2013 and find that our efficient frontier and the conventional efficient frontier are quite similar. Therefore, in plain financial language, investors can still obtain risk-return performance similar to conventional portfolio selection after imposing strong ESG requirements, although the portfolio weights can be totally different. The result is both an endorsement and a reminder for sustainable investment.

PISA Performance of Natives and Immigrants: Selection versus Efficiency

In most countries, immigrant and native students perform differently in the Programme for International Student Assessment (PISA) due to two main reasons: different immigration regimes and differences in their home-country educational systems. While there is sophisticated literature on the reasons for these performance gaps, it is barely considered in the educational efficiency research. Our approach distinguishes between selection effects caused by immigration policies, and the efficiency of educational systems in integrating immigrant students, given their socio–economic background. Accordingly, we split our sample, which consists of 153,374 students in 20 countries, calculate various different efficient frontiers, and ultimately decompose and interpret the resulting efficiency values. We find large differences in educational system efficiency, when controlling for negative selection effects caused by immigration regimes.

How to use fuzzy screening system and data envelopment analysis for clustering sustainable suppliers? A case study in Iran

PurposeThe aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering.Design/methodology/approachFirst, using fuzzy screening system, the authors identify and remove the unqualified suppliers. Then, the authors run their proposed clustering method. This paper proposes a data envelopment analysis (DEA) algorithm to cluster suppliers.FindingsThis paper presents a two-aspect DEA-based algorithm for clustering suppliers into clusters. The first aspect applied DEA to consider efficient frontiers and the second aspect applied DEA to consider inefficient frontiers. The authors examine their proposed clustering approach by a numerical example. The results confirmed that their method can cluster DMUs into clusters.Originality/valueThe main contributions of this paper are as follows: This paper develops a new clustering algorithm based on DEA models. This paper presents a new DEA model in inefficiency aspect. For the first time, the authors’ proposed algorithm uses fuzzy screening system and DEA to select suppliers. Our proposed method clusters suppliers of MPASR based on sustainability factors.

Selecting the Most Desirable IT Portfolio Under Various Risk Tolerance Levels

To better assist decision-makers (e.g., enterprise executives) in selecting the most desirable IT portfolio, this study proposes a new IT Portfolio Efficient Frontier model that incorporates the decision-maker's risk tolerance levels. The proposed model, built on portfolio optimization along with experimental design and simulation data, considers three IT portfolio scenarios: even distribution-based IT portfolios, uneven distribution-based IT portfolios, and dominant IT portfolios. Our findings show that the IT portfolio efficient frontiers derived from both an even distribution-based IT portfolio and an uneven distribution-based IT portfolio have a relatively positive relationship between IT portfolio risk and return. Our findings also indicate that if IT investments are part of a dominant IT portfolio, an inflection point of the IT portfolio efficient frontier appears under the decision-maker's medium risk tolerance level, and the most desirable IT portfolio is generated when a decision maker's risk tolerance level is medium or higher.