ESG for All? The Impact of ESG Screening on Return, Risk, and Diversification. Issue 2 (June 2016)

• Record Type: Journal Article
• Authors: Verheyden, Tim; Eccles, Robert G.; Feiner, Andreas
• Is Part Of: Journal of applied corporate finance. Volume 28:Issue 2(2016)
• Page Start: 47
• Page End: 55
• Publication Date: 2016-06
• Subjects: Corporations -- Finance -- Periodicals; Capital investments -- Periodicals; Business planning -- Periodicals; Corporate governance -- Periodicals; 338.6041
• DOI: 10.1111/jacf.12174
• Languages: English
• ISSNs: 1936-8216

Abstract

Abstract : A large body of research has documented a positive relationship between different measures of sustainability—such as indicators of employee satisfaction and effective corporate governance—and corporate financial performance. Nevertheless, many investors still struggle to quantify the value of ESG to investment performance. To address this issue, the authors tested the effects of using different ESG filters on an investable universe that serves as the starting point for a fund manager. In this way, they attempted to determine the extent to which ESG data can add value to any investment approach, regardless of preferences towards sustainable investing. The authors report "an unequivocally positive" contribution to risk‐adjusted returns when using a 10% best‐in‐class ESG screening approach (one that effectively removes companies with the lowest 10% of ESG rankings), both on a global and a developed markets universe. More specifically, as a result of such screening, both the global and developed markets portfolios show higher returns, lower (tail) risk, and no significant reduction of diversification potential despite the reduction in the number of companies. Use of a 25% screening filter was also found to add value, especially by reducing tail risks, but with a larger deviation from the unscreened universe. Overall, then, the authors' finding is that the incorporation of ESG information contributes to better decision‐making in every investment approach, with the optimal configuration depending on a fund manager's preferences and willingness to deviate from an unscreened benchmark.