ESG分歧下的投资组合选择:通过直接指数定制可持续性

P. Ehling, Stig Roar Haukø Lundeby, L. Sørensen
{"title":"ESG分歧下的投资组合选择:通过直接指数定制可持续性","authors":"P. Ehling, Stig Roar Haukø Lundeby, L. Sørensen","doi":"10.3905/jbis.2023.1.041","DOIUrl":null,"url":null,"abstract":"There is strong demand for sustainable investing in direct indexing strategies. We examine implications of disagreement about environmental, social, and governance (ESG) ratings for portfolio choice by maximizing ESG scores subject to a tracking error constraint. Varying the ESG score we optimize on results in portfolios with substantial differences. Correlations between active weights of the ESG-optimized portfolios are even lower than correlations between ESG scores. Optimal portfolios have positive (negative) active weights in stocks with high (low) ESG scores, as expected, but in both cases a small market capitalization or high specific risk pulls the active weight toward zero. To attenuate ESG disagreement, we propose an optimal portfolio that maximizes the average ESG score across vendors and explicitly manages ESG disagreement by penalizing stocks with high ESG uncertainty. Increasing ESG uncertainty aversion thus means investing less in stocks with high ESG disagreement. Our solution is well suited for direct indexing clients wanting to express their sustainability beliefs.","PeriodicalId":284314,"journal":{"name":"The Journal of Beta Investment Strategies","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Portfolio Choice with ESG Disagreement: Customizing Sustainability through Direct Indexing\",\"authors\":\"P. Ehling, Stig Roar Haukø Lundeby, L. Sørensen\",\"doi\":\"10.3905/jbis.2023.1.041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is strong demand for sustainable investing in direct indexing strategies. We examine implications of disagreement about environmental, social, and governance (ESG) ratings for portfolio choice by maximizing ESG scores subject to a tracking error constraint. Varying the ESG score we optimize on results in portfolios with substantial differences. Correlations between active weights of the ESG-optimized portfolios are even lower than correlations between ESG scores. Optimal portfolios have positive (negative) active weights in stocks with high (low) ESG scores, as expected, but in both cases a small market capitalization or high specific risk pulls the active weight toward zero. To attenuate ESG disagreement, we propose an optimal portfolio that maximizes the average ESG score across vendors and explicitly manages ESG disagreement by penalizing stocks with high ESG uncertainty. Increasing ESG uncertainty aversion thus means investing less in stocks with high ESG disagreement. Our solution is well suited for direct indexing clients wanting to express their sustainability beliefs.\",\"PeriodicalId\":284314,\"journal\":{\"name\":\"The Journal of Beta Investment Strategies\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Beta Investment Strategies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3905/jbis.2023.1.041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Beta Investment Strategies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jbis.2023.1.041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

对直接指数策略的可持续投资需求强劲。我们通过在跟踪误差约束下最大化ESG分数来研究关于环境、社会和治理(ESG)评级对投资组合选择的影响。通过改变ESG得分,我们对投资组合的结果进行了优化,结果存在显著差异。ESG优化投资组合的主动权重之间的相关性甚至低于ESG得分之间的相关性。正如预期的那样,最优投资组合在ESG得分高(低)的股票中具有正(负)主动权重,但在这两种情况下,市值小或特定风险高都会使主动权重趋近于零。为了减轻ESG分歧,我们提出了一个最优投资组合,使供应商的ESG平均得分最大化,并通过惩罚ESG不确定性高的股票来明确管理ESG分歧。因此,增加对ESG不确定性的厌恶意味着减少对ESG分歧程度高的股票的投资。我们的解决方案非常适合想要表达其可持续性信念的直接指数客户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Portfolio Choice with ESG Disagreement: Customizing Sustainability through Direct Indexing
There is strong demand for sustainable investing in direct indexing strategies. We examine implications of disagreement about environmental, social, and governance (ESG) ratings for portfolio choice by maximizing ESG scores subject to a tracking error constraint. Varying the ESG score we optimize on results in portfolios with substantial differences. Correlations between active weights of the ESG-optimized portfolios are even lower than correlations between ESG scores. Optimal portfolios have positive (negative) active weights in stocks with high (low) ESG scores, as expected, but in both cases a small market capitalization or high specific risk pulls the active weight toward zero. To attenuate ESG disagreement, we propose an optimal portfolio that maximizes the average ESG score across vendors and explicitly manages ESG disagreement by penalizing stocks with high ESG uncertainty. Increasing ESG uncertainty aversion thus means investing less in stocks with high ESG disagreement. Our solution is well suited for direct indexing clients wanting to express their sustainability beliefs.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信