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How can investors determine whether the transition to a low-carbon economy will impact the performance of the companies in their portfolios? Osman Ali, co-head of Equity Alpha Strategies within GS Asset Management’s Quantitative Investment Strategies (QIS) platform, discusses the integration of environmental, social and governance (ESG) objectives into quantitatively-oriented investment strategies.
Transition to a Low-Carbon Economy
Whether driven by regulation, consumer demand, technological innovation, or some combination of all three, the world is moving toward a lower-carbon economy, and we think this will create a foundational, structural shift in our economic landscape.
We believe capturing the implications of these changes is important to the return-generating potential of our portfolios. That’s why we recently introduced new explicit climate transition considerations into our investment process that seek to reduce each portfolio's carbon footprint by at least 25% relative to its respective benchmark index.
As an active manger, we believe it’s imperative to understand how the transition to a low-carbon economy may impact companies differently, and we’ve spent nearly five years researching just that. By minimizing the footprint in our portfolios of companies that may be disproportionately hurt by the transition to a low-carbon economy, we believe we can generate relative outperformance over time.
But what’s the best way to go about this? It’s relatively easy to look at a company's current carbon emissions and penalize high emitters. We decided, however, to take a more forward-looking approach, incorporating both current emissions and future emissions. We also look at where a company sits along the carbon supply chain, which we believe affects its ability to adapt its business model to a lower-carbon economy. In our view, companies that are less able to adapt may find the road ahead more challenging.
Integrating ESG and Quant Investing
Looking beyond climate, our dedicated team of ESG researchers have found that in certain instances, social and governance factors can also be potential sources of excess returns.
We have spent over 30 years conducting research on company management-related activities, and have developed a number of governance-related alpha signals that we believe can help forecast the future returns of a company. These signals help us to investigate the investment activities and decisions of a company’s management team.
We’ve also been focused in recent years on capturing social sentiment, which we see as a combination of both external sentiment, whether it be consumers that interact with a specific company or a community in which the company operates, as well as internal sentiment -- gauging the satisfaction from a company’s own employees. While certain text-based data, such as news articles, press releases, and company reports, can contain this information, it is not trivial to extract the necessary insights that are able to inform investment decisions. We’ve built a large library of text processing algorithms that allows us to analyze these types of documents, enabling us to derive more socially-based insights.
We believe the future of ESG and quant investing will be driven by technology and alternative data sources, which can help us go well beyond official corporate disclosures.