Sustainable Investing

The following sections are included:

• About the Contributors
• Contents
• Introduction

In this chapter, we argue that environmental, social, and governance (ESG)/sustainability is moving from being based primarily on ESG ratings and rankings, which has caused significant confusion, to being based on mandated disclosure and analysis of externalities. We briefly examine the basis of ESG ranking and rating confusion, concluding that the current methodologies of major providers result in neither significant change nor accurate disclosures by firms. Alternatively, we suggest that an integration of externality data will significantly modify Modern Portfolio Theory as it does not account for externality effects on “systems” (think market beta) or the interactive effects of firms’ actions on other firms in various types of portfolios, both directly and indirectly. These dynamics are qualitatively important given the growth and dominance of universal owner-type portfolios. Not accounting for externalities leads to sub-optimal economic system performance, reducing the financial return both absolutely and sometimes relatively. In turn, these dynamics redefine what financial “materiality” means. Finally, we place these concepts and developments into the context of global emerging regulatory standards and debates about them.

There are reams of legislative and regulatory frameworks in the United States (U.S.), Europe, and elsewhere addressing matters of environmental and social concern. But, in referring to Environmental, Social, and Governance (ESG) legal frameworks, the narrower sets require (or at least encourage) in-scope companies to either (i) make some disclosure about how those companies are addressing environmental or social issues or (ii) address how in-scope companies do that, including, for example, what terminology they use to signal where those companies stand on environmental or social issues. This chapter covers some of the most prominent examples of both sets of legal frameworks with discrete attention to those relevant to the financial sector. This chapter also covers some of the key tests on those frameworks and ESG more generally, including legislation aimed at prohibiting the use of ESG factors in the U.S.

There are reams of legislative and regulatory frameworks in the United States (U.S.), Europe, and elsewhere addressing matters of environmental and social concern. In fact, the challenge might be in identifying a legal regime that does not address one or both in some measure. But, in referring to Environmental, Social, and Governance (ESG) legal frameworks, the narrower sets do one of two things: The first set requires (or at least encourages) in-scope companies to make some disclosure about how those companies are addressing environmental or social issues. The second set addresses how in-scope companies do that, including, for example, what terminology they use to signal where those companies stand on environmental or social issues.

This section covers some of the most prominent examples of both sets of frameworks with discrete attention to those relevant to the financial sector. This includes frameworks already in place and others still pending as of the publication of this section. It bears emphasizing that there are a multitude of ESG frameworks beyond those noted here — frameworks in place, pending in other jurisdictions, and extending beyond those having singular relevance to the financial sector.

Overall, the body of ESG frameworks is evolving so quickly that any research should assume the information provided here is but a starting point for understanding those in place and what they require of companies generally or the financial sector especially. Note further that in an increasingly global market, frameworks can have extra-jurisdictional impact. In some instances, frameworks may require (either expressly or as a practical matter) that companies reach into their value and supply chains for disclosure data. They may also establish (again, either expressly or as a practical matter) an effective bar to market access in any given jurisdiction for any company that does not comply. Given that, it is advisable to consider frameworks beyond the bounds of a company’s home jurisdiction.

Private equity (PE) funds have become majority owners of hospitals, newspapers, schools, real estate, industrial manufacturers, extractive industries, consumer brands, and retail. Worldwide, approximately 10,000 PE firms enjoy ownership rights in 40,000 portfolio companies, which in turn manage 20 million employees. On that scale, PE has a significant influence on corporate behavior, especially when it has majority or controlling interests.

PE firm policies and approaches can create value for all stakeholders, including the environment, or extract value to the detriment of other stakeholders (and potentially reduce their own returns). Our research aims to identify how PE can avoid doing harm, as well as provide positive impact. We have undertaken a robust academic review of the state of PE in terms of its contribution to creating or extracting value and developed an accountability framework that provides insights into the various categories of PE impact, both positive and negative. The framework lays out the criteria that investors, civil society, regulators, and others can explore to assess the PE firm’s performance and includes human capital management, financial engineering, strategy and innovation, and societal impact, among other categories. This chapter will provide examples of positive and negative behavior through the lens of the accountability framework, as well as present insights into how sustainability can drive financial value in PE at the firm level.

New investment strategies call for new benchmarks. The evolution of sustainable investing over the past three decades has demonstrated the validity of this statement. To facilitate investment, indexes are used as the basis of investment vehicles by passive managers and as investment universes by active managers. As benchmarks, they provide an ongoing time series of return, risk, and financial fundamental data. For environmental, social, and governance (ESG), climate, and impact strategies, indexes also play an important role by defining and measuring sustainability standards and characteristics. As sustainable investing has grown in popularity and sustainable investing strategies have expanded beyond ESG analysis to encompass climate and impact, indexes serve a crucial function, establishing sustainability standards and measuring sustainability characteristics. This chapter shows how classical finance theory broadened the use cases of indexes; provides a brief history of sustainability indexes; and explains how sustainability indexes contributed to improvement of ESG research and advancement of sustainability strategies by answering critical questions about ESG risk and opportunity, carbon intensity, and net-zero pathways, in addition to measuring financial performance and risk. Situated at the intersection of the passive and sustainable investing trends, indexes are cornerstones of this maturing and increasingly influential set of investment practices.

Funds with “sustainable” labeling have taken an outsized share of global fund inflows in the 2020s to date. However, there is a lack of clarity on what they actually do, what role they play in investors’ portfolios, and whether it is a case of “sacrificing returns for the greater good.” Regulators globally are trying to fill the gaps by proposing prescriptive labeling and disclosure frameworks to ensure the investors know what they are buying. But, are the regulations built on the right premise? Are “sustainable” funds designed to drive global progress on issues like climate change and human rights or do they merely cater to investors’ ethical preferences on environmental and social topics? This chapter examines the status quo, the existing and proposed regulations aimed at addressing how asset managers treat sustainability themes, and how these regulations fit with the ongoing debate over the role of sustainable funds.

Global initiatives such as the Principles for Responsible Investment (PRI) or the UN Sustainable Development Goals (SDGs) are well poised to catalyze the transition toward climate justice, food security, and agricultural resilience. These initiatives motivate countries to develop frameworks for sustainability reporting to facilitate the transition economy. Globally, policymakers and regulators have proposed regulations to increase the transparency and uniformity of reporting surrounding climate change and corporate social responsibility. We investigate over 100 global documents related to regulatory developments in sustainable taxonomies, climate disclosures, and Environmental, Social, and Governance (ESG) fund requirements reported in the 2023 Sustainable Fitch Tracker of ESG Regulations and Reporting Standards. We propose a model utilizing the power of Artificial Intelligence and Large Language Models to analyze global regulatory documents to capture sustainability-related risks and opportunities defined by the Sustainable Accounting Standard Board (SASB). We compare the performance of keyword-based and ChatGPT-based models and find that the ChatGPT model successfully detects a greater number of global regulatory documents containing the SASB topics. Our results show that the European Union is the leader in having the largest amount of effective and mandatory regulatory coverage of SASB categories, followed by Nigeria and Saudi Arabia. The United States is the leader in effective and non-mandatory regulatory coverage, followed by Malaysia and Mexico.

Machine learning models, when applied to Environmental, Social, and Governance (ESG) data, can serve as an essential guide in assessing various aspects of sustainability for investing, financing, insurance, and even policymaking. They can be used for computing ESG thematic scores, carbon scores, water scores, etc. This chapter provides a “sneak peek” into some of the challenges related to the application of machine learning methods to compute an ESG thematic score based on a set of ESG parameters for a given entity. We start with a general presentation of how ESG thematic scores are computed, the data that we use, and the preprocessing steps that we suggest applying to the underlying data. Then, we explore how to generate ESG themes in an unsupervised manner via clustering algorithms and how to summarize the information contained in such a theme via dimensionality reduction techniques. Finally, we observe that traditional parametric models do not allow one to generalize a given ESG score to a large universe of entities. Our evaluation of these methodologies highlights the complexity of building ESG scores without prior supervision and the difficulty of generalizing available ESG scores to a broader universe.

In this chapter, we examine the challenges in extracting and analyzing Environmental, Social and Governance (ESG) data and their potential solutions. In particular, we focus on material ESG data relevant to companies and industries vs. a “one-size-fits-all” approach, highlighting examples where ESG has had a financial impact. We discuss how ESG metrics impact company performance, highlighting among others how ESG facets might impact risk, returns along with fundamentals. Furthermore, using the holdings of some of the largest US ESG funds, we discuss what characteristics drive ESG fund inclusion and what might be missed. Lastly, we discuss how ESG might not be that far removed from having a positive societal impact and discuss strategies that can drive this.

Net-zero portfolios (NZPs) aim to reduce their carbon footprint over time, typically until 2050, by mimicking scientific paths of decarbonization, and aggregate carbon budget, for the global economy. Their popularity among institutional investors has been growing over time, with more than $100 trillion of global assets under management currently covered by various net-zero (NZ) investing initiatives. The first part of the chapter provides a discussion of the construct of the NZP, its benefits, and its potential limitations for portfolio managers. The second part of the chapter outlines the role of the NZP in asset prices. The channels underlying the pricing are divestment and engagement. Contrary to common wisdom that focuses on divestment that is already happening, being associated with an NZP initiative does not necessarily imply that investors need to divest from high-emitting companies right away. It may also mean an expectation of such divestment in the future. Because the expectation of divestment allows for a dialogue between institutional investors and corporates, the framework is also a form of engagement.

Net-zero portfolios (NZPs) aim to reduce their exposure to carbon foot-print over time, typically until 2050, by mimicking scientific paths of decarbonization for the global economy. Even though NZPs by themselves do not guarantee the decarbonization of the global economy, they aim to provide incentives for companies to do so. Companies that undertake emissions reduction are rewarded by being included in NZPs, and companies that are behind the decarbonization curve are penalized by being excluded from NZPs. The popularity of net-zero investing among institutional investors has been rapidly growing, with more than $100 trillion of global assets under management currently covered by various net-zero investment initiatives. The NZP initiative has also shaped discussions surrounding sustainable finance, as is the case for the EU Low-Carbon Benchmark Regulation, which establishes uniform rules for low-carbon investment benchmark indexes and sets their required decarbonization trajectories.

In this chapter, I first provide details that govern the construction of NZPs, building on the early work of Bolton et al. (2022). Next, I discuss the properties of such portfolios relative to a standard market portfolio benchmark. Finally, I discuss how the NZP framework can be applied to construct measures of carbon transition risk at the firm level, which offer conceptual improvements over measures in prior work by Bolton and Kacperczyk (2023).

A company’s carbon impact extends across its entire value chain, both upstream and downstream. This is referred to as “Scope 3,” and it is essential to address climate change and provide true estimates of corporations’ carbon performance. However, the evaluation of Scope 3 emissions is a major challenge, because its calculation is poorly standardized and regulated. Publication trends vary widely across the globe and across sectors.

This chapter discusses the evolution of environmental practices over the last ten years across more than 6,000 listed companies based in 4 major regions of the world. In particular, we examine several determinants of Scope 3 disclosure, their links with environmental scores from environmental, social, and governance (ESG) data providers, and the disparities between regions, sizes, sectors, and other company characteristics.

We find that companies communicate strongly on value chain environmental policies both before and after Scope 3 publication. Disparities are very marked between regions of the world, particularly for less globalized and lower-capitalized companies. Moreover, companies publishing Scope 3 are generally those that already have a high environmental score and have been publishing Scope 1 data for several years.

This paper examines venture investments in Carbon Dioxide Removal (CDR) technologies. It analyzes the main trends, challenges, and opportunities that exist in this sector, with a focus on three key technologies: Bioenergy with Carbon Capture and Storage (BECCS), Direct Air Carbon Capture and Storage, and Enhanced Weathering (EW). According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), CDR is an integral component in scenarios aiming to limit warming to 2°C or below by 2100. While “traditional” or “conventional” CDR methods, based on the CO₂ uptake capacity of forests and soils, remain the most widely used, there are limitations to their scalability. This underscores the importance of developing and implementing new CDR methods, many of which are still at a low level of technological maturity. In this context, venture investments often play a crucial role in the successful development and commercial application of technologies in the early stages due to a high tolerance for risk and a long-term investment horizon.

This paper addresses the urgent challenge of climate risks amid escalating temperatures in 2023 and forthcoming projections for 2024. Focused on the intersection of climate risk mitigation, carbon trading, and the Karush–Kuhn–Tucker (KKT) optimization framework, we utilize advanced mathematical models to enhance emission reduction strategies within carbon trading systems. Our research emphasizes the dynamic interplay between production quantity, fuel prices, and the energy sector, aiming to contribute to both environmental impact and economic viability. The central exploration involves the application of the KKT model to navigate the intricate landscape of fuel production. Linear inverse demand functions are employed to quantify market demand and address relationships between fuel price and production quantity. The KKT model facilitates the definition and optimization of production quantities, balancing consumer needs, economic feasibility, and environmental impact mitigation. Integration of carbon trading mechanisms considers costs and benefits related to emissions reduction, achieving a delicate equilibrium between market demands and the carbon footprint of fuel production. A distinctive aspect of our approach is the direct inclusion of individual fuel producers into the optimization model, transforming profit objectives into refined KKT constraints for market equilibrium. This methodology signifies a substantial advancement in understanding and optimizing fuel production dynamics. Leveraging the KKT model, our research contributes valuable insights to sustainable energy practices, providing a theoretical foundation for academia and practical guidance for industry stakeholders navigating the delicate balance between economic prosperity and environmental responsibility.

In this chapter, we present a novel approach to produce Environmental, Social, and Governance (ESG) and Sustainable Development Goal (SDG) scores based on near-real-time news. Through the application of Natural Language Processing (NLP) techniques, we extract the relevant entities, topics, and likely effects of the news. The individual information is aggregated into scores on a regular time grid. Based on the scores, we build topic-oriented portfolios and compare them to a benchmark. The data have been provided in the AiData.green database that was co-developed by the authors of this chapter. In our studies, we cover mostly European and US markets. We find that substantial risk-adjusted outperformance of portfolios can be achieved by taking sustainability topics into account.

This chapter thoroughly examines eight long-only MSCI style factors, nine long-only sustainable theme factors, and four long–short sustainable theme factors. Backtests against the historic MSCI World benchmark from September 2019 to November 2023, using MSCI’s Barra Portfolio Manager, reveal that the low active risk and low turnover long-only portfolios performed in line with their MSCI World benchmark. Meanwhile, sustainable themes as well as the MSCI style factor ESG exhibited significantly higher sustainable performance. Testing the 17 long-only factors in a restricted universe, simulating the stringent 2023 Paris-aligned sustainability law of Baden-Württemberg, Germany, showed that stringent universe exclusions negatively impacted performance, increased portfolio size without lowering active risk but reducing emissions, and improved the overall Sustainable Development Goals (SDGs) scores. Remarkably, the long–short sustainable factors exhibit significant risk sustainability-adjusted outperformance compared to the MSCI World benchmark. These findings challenge the conventional notion that sustainability for investors depends mainly on universe exclusions. Moreover, they demonstrate that steering portfolios with sustainable factors not only broadens the universe and diversifies across industries but also reduces concentration risk without compromising performance. This approach seamlessly integrates with impact investing, enabling the pursuit of explicit positive objectives, such as advancing SDGs or facilitating the transition from Brown to Green, potentially serving as an engine for EU Sustainable Finance Disclosure Regulation (SFDR) Article 9 funds.

This chapter presents a three-dimensional investment framework that combines factor investing techniques and factorized sustainability data to enable investors to quantitatively connect the sustainability dimension to the risk-and-return dimensions when constructing sustainable investment portfolios. We demonstrate how the portfolio costs of sustainability objectives, in terms of risk-and-return implications, can be modeled, followed by insights into how sustainability can be approached in risk budget terms with an examination of the potential degree of diversification available when multiple sustainability outcomes are targeted.

This chapter provides a comprehensive guide to post-investment strategies for impact investing tailored for sustainable investment professionals. Engagement and stewardship are pivotal post-investment strategies to steer companies toward sustainable practices that align with investors’ environmental, social, and governance (ESG) goals. They encompass active dialogue with company management, exercising voting rights, and participating in collaborative initiatives. We also introduce tools and metrics for measuring ESG performance improvements, such as ESG ratings and monitoring of ESG controversies, and explore the use of advanced analytics to assess the real-world extra-financial impact of portfolio companies. We discuss the inherent risks and opportunities in post-investment strategies, including company resistance, resource constraints, and the potential for short-termism. Conversely, there are numerous opportunities in influencing corporate behavior, enhancing long-term value creation, and aligning investments with broader societal and environmental objectives. By effectively understanding and implementing these strategies, asset managers can contribute to the transition toward a more sustainable future while meeting their clients’ financial and extra-financial objectives.

Fixed income is the biggest asset class in global financial markets, spanning capital provision for all types of entities from sovereign to private corporates, and with a direct cost-of-capital effect through primary market capital supply. This article discusses a holistic perspective on applying climate and ESG-type investment preferences on fixed-income portfolios. We discuss how these types of strategies then can be implemented in a portfolio context to generate a well-diversified impact and risk/return profile. Due to the asymmetrical risk–return profile of fixed income, applying a multi-threaded, well-diversified approach is argued to be a fiduciary-aligned approach to managing any fixed-income portfolio.

The portfolio performance measure generally used in classical finance is based on the volatility risk-adjusted return (Sharpe ratio). Unfortunately, applying this measure in sustainable investing may yield some confusion since portfolios with higher environmental, social, and governance (ESG) ratings may not outperform their ESG-neutral peers. Moreover, correlations between the corporate ESG ratings and stock returns in some portfolios can be negative. Since the ESG factors represent non-pecuniary risks, it is suggested in this work that socially responsible investors should include the ESG metrics explicitly in the portfolio performance measures. This idea is closely related to deriving optimal ESG portfolios (OESGPs) that are simultaneously optimized in terms of their return, volatility risk, and ESG value. Another important issue discussed here is that investors may prefer ESG ratings customized according to their preferences rather than simple averages of the E, S, and G categories that are offered by various ratings agencies. In this work, both problems are addressed using OESGPs formed with the constituents of nine major US equity sector Exchange-Traded Funds (ETFs). It is found that the main OESGP holdings are not very sensitive to the ESG metrics and hence can be promising leads for future investments.

The following section is included:

• Index