By Alex Cheema-Fox, Bridget R. LaPerla, George Serafeim, David Turkington, and Hui (Stacie) Wang.
Published in the Financial Analysts Journal, May 2021
In the era of climate change, investment managers are grappling with how to make sense of different approaches to climate data to improve portfolio outcomes.
In our research with Professor George Serafeim at Harvard Business School, we start by testing the circumstances in which three types of qualitative and quantitative measures of carbon risk, including upstream and downstream characteristics, add value to portfolio construction. We discovered a clear way to identify which data matters the most for a given industry. The metrics that vary widely across firms in an industry are effective at predicting returns. This dispersion is calculated through the “coefficient of variation” for each metric in each industry. These (and other) insights for determining the merit and applicability of climate data can then be applied in rules-based trading models.
Our rule is a systematic process of choosing a different type of climate metric across industries. Playing to the strengths of various types of climate data can help investors design strategies to manage climate risk while increasing risk-adjusted returns. By using more sophisticated rules, we suspect investors could produce even better results.
