 When trackers are aware of ESG: Do ESG ratings matter to tracking error portfolio performance?Aifan Ling, Junxue Li, Limin Wen and Yi Zhang Economic Modelling, 2023, vol. 125, issue C Abstract: With the increasing severity of the greenhouse effect and environmental pollution, environmental, social, and governance (ESG) investing has received much attention in recent years. This paper studies how ESG scores and investors’ ESG preferences affect the performance of tracking portfolios. We embed ESG information and the ESG preferences of investors into the mean–variance tracking error model, and then explicitly solve the new tracking portfolio model. The theoretical analysis shows that ESG information can improve the expected returns, information ratio (IR) and other performance metrics of tracking portfolios. The relationship between the ESG scores and IR of tracking portfolios is represented by an inverse U-type ESG-IR frontier. Consistent with theoretical predictions, numerical results with a real market benchmark show that ESG information and ESG investor preference have a positive impact on the realized returns, IR, net aggregate returns and cumulative returns of tracking portfolios. Our results provide investors with several valuable references about ESG awareness and preferences. Keywords: ESG-IR frontier; ESG investing; Tracking error portfolio; Information ratio; Mean–variance model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:125:y:2023:i:c:s026499932300158x DOI: 10.1016/j.econmod.2023.106346 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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