CFA Institute

Investing in the Era of Climate Change. 2022. Bruce Usher. Columbia University Press. The scientific consensus is that climate change is real, occurring now, and potentially catastrophic. As a result, most countries have committed to reductions in greenhouse gas emissions with the aim of “net zero” emissions by the middle of the 21st century. To achieve the reductions, innovation and investment are needed on a large scale. Bruce Usher of Columbia Business School approaches the issue from the perspective of the investor, and in Investing in the Era of Climate Change, he identifies both what the implications of climate change are for the investment community and how investment capital allows us “to save us from ourselves.” The role of investors, he says, is no less than “financing the world’s future.” Early in the book, Usher gives an account of technological developments that can mitigate the effects of climate change — renewable power, electric vehicles, battery storage, green hydrogen, and carbon removal. This discussion serves as a valuable introduction to later sections that deal with the implications of such climate solutions for the investment community. One section identifies the alternative strategies that the investor can use: Risk Mitigation Divestment Environmental, Social, and Governance (ESG) Investing Thematic Impact Investing (to finance businesses that address a specific environmental or social challenge, such as climate change) Impact First Investing (in which investors focus on solving social and environmental problems and are willing to accept a below-market financial return in exchange for greater impact) Each of these strategies is suitable for a particular kind of investor. University endowments may opt for Divestment, large fund managers for ESG, specialist fund managers for Thematic Impact Investing, and philanthropists for Impact First Investing. Some approaches help to control risks; others (according to Usher) can improve returns. Asserting that “all investors should understand the opportunities and risks of investing in real assets that offer climate solutions,” the author then looks at both financial and real assets. Real assets include renewable energy projects, real estate, and forestry and agriculture. His analysis examines the valuation issues relevant to large-scale renewables projects, along with insights into government incentives and prospective returns (internal rates of return of 6%–8% for solar and wind projects and potentially more return for higher risk investments in battery energy storage systems). The discussion of real estate is brief but includes such considerations as the risks from flooding and wildfires as well as the benefits of energy upgrades — the Empire State Building is an interesting example. The importance of carbon markets is illustrated by the chapter on forestry and agriculture. The author’s analysis of financial assets includes chapters on venture capital, private equity, public equity, equity funds, and fixed income. We are given interesting examples of successful and unsuccessful investments, along with the following approaches to assessing investments in the era of climate change: Is a company minimizing risk by reducing its emissions, both direct and indirect? What would be the impact of a price on carbon? Is the company an incumbent in an industry or a disruptor? If a disruptor, how likely is it to succeed? The chapter on equity funds identifies many types of currently available climate-focused funds and exchange-traded funds (ETFs). The analysis covers the differences among low-carbon funds, fossil-fuel-free funds, and climate transition funds. The author notes that some of these funds are particularly large and successful: “BlackRock’s Carbon Transition Readiness ETF pulled in $1.3 billion on its first day of trading, making it the biggest launch in the ETF industry’s three-decade history.” A successful fund launch is one example of how investing in climate solutions has become mainstream. So too is the establishment of such bodies as the Glasgow Financial Alliance for Net Zero — “a global coalition of 450 financial firms managing assets of more than $130 trillion that are committed to reducing greenhouse gas emissions to zero.” The author believes that the fixed-income markets will be the most important for the funding of climate solutions. Part of the reason is their scale, and part is because many projects, with steady cash flows over long periods of time, lend themselves to debt financing. An important area is that of “green bonds,” the market for which is described as “red hot.” In 2021, $500 billion of green bonds were issued. Other innovations in fixed-income investing include the securitization of solar leases and loans. Several times throughout this book, we read estimates of the costs of necessary climate solutions. The various numbers can be confusing, but all are broadly consistent with a Boston Consulting Group estimate of what is required: $3 trillion to $5 trillion per year. This enormous level of investment is a huge step up from where we are today (spending of circa $600 billion a year, according to Usher). The investment is necessary, however, especially because other possible responses to climate change can be convincingly rejected. (These alternatives include adaptation and the control of population growth.) A welcome aspect is that the general tone of the book is upbeat, with a focus on solutions rather than resorting to despair. At times, however, this approach means glossing over certain risks to climate targets. For example, livestock make a material contribution to greenhouse gases (in the form of methane), but apart from references to the success of Beyond Meat, the author offers us few solutions to the issue of livestock. Similarly, he says little about how to mitigate emissions caused by the production of cement. Furthermore, although he does write that “perhaps the greatest challenge to reaching net zero is the inability by countries to cooperate,” he says little about how dependent we are on fragile global supply chains for solutions, such as battery storage systems. The author makes clear, however, that his goal is not to describe every possible solution to the climate crisis but to focus on the implications of climate change for investors. Investing in the Era of Climate Change draws from a wide variety of sources and is

I recently sat down with Jason Hsu, founder of Rayliant Global Advisors and chief economist of East West Bank, to discuss the evolution of factor investing, the challenges facing the asset management industry, and the opportunities offered by modern technologies and approaches. This interview is part of the Conversations with Frank Fabozzi, CFA series, sponsored by the Research and Policy Center. The series aims to bring leading experts in finance and economics into dialogue to explore critical issues shaping the industry’s future. Hsu is a recognized leader in quantitative asset management and co-founder of Research Affiliates. You can register for my upcoming conversation with Lori Heinel, CFA, EVP and global chief investment officer at State Street Global Advisors here. Hsu’s reflections in this session underscore the shifts in investment paradigms, the growing pressures on asset managers to differentiate themselves, and the critical role of governance, innovation, and long-term thinking in navigating an increasingly competitive and complex environment. Expanding the Factor Universe Hsu begins by tracing the origins and evolution of factor-based strategies. Initially rooted in academic finance, these strategies have become staples in institutional and retail investing. Traditional factors, such as value, momentum, and size, continue to play a significant role, but Hsu highlights a growing appetite for expanding the factor universe. Today, asset managers are increasingly incorporating macroeconomic signals, such as interest rate changes or inflation dynamics, alongside behavioral factors driven by market psychology. This broadening of the factor toolkit reflects both a response to market commoditization and a recognition that traditional factors, while still valuable, cannot alone address the complexities of modern financial markets. One of Hsu’s key points is the importance of grounding factor-based strategies in clear economic rationale. He warns against over-reliance on historical data or data-mining approaches that lack theoretical justification. While backtesting can yield impressive results, strategies derived without a solid understanding of their underlying drivers risk failing in real-world conditions. Hsu argues that robust factor strategies should be built upon empirical evidence and an intuitive understanding of how and why certain relationships persist across different market environments. This combination ensures that factors remain relevant and effective even as market dynamics evolve. The commoditization of basic factor strategies is a central theme of Hsu’s discussion. As quantitative tools and techniques have become more accessible, the barriers to implementing traditional factor models have diminished. This has led to declining fees and heightened competition among asset managers, pressuring firms to differentiate themselves through innovation. Hsu notes that differentiation often entails exploring new or custom factors, but it also requires maintaining transparency and aligning with client expectations. Firms must balance pushing the boundaries of innovation and delivering strategies that investors can understand and trust. Structural Challenges in Asset Management Hsu also addresses the structural challenges within the asset management industry, particularly those related to governance and incentives. He critiques the pervasive short-termism that dominates many investment decisions, arguing that this mindset often misaligns with the long-term goals of institutional and retail investors. The pressure to deliver quarterly results frequently leads to strategies prioritizing immediate performance over sustainable value creation. Hsu advocates for governance structures that reward long-term thinking and encourage asset managers to focus on delivering outcomes that align with their clients’ broader objectives. The role of technology in reshaping asset management is another critical focus of the interview. Hsu acknowledges the transformative potential of machine learning and artificial intelligence in modern portfolio management. These technologies enable asset managers to uncover complex patterns, process vast datasets, and develop more sophisticated models. Hsu cautions against the indiscriminate use of technology, highlighting the risks of overfitting and the lack of interpretability in many machine learning models. In finance, where decisions often have significant consequences, the inability to explain how a model arrived at its conclusions can undermine its practical value. Hsu argues for a balanced approach to integrating machine learning (ML) with traditional financial and economic theory. Rather than replacing established methodologies, ML should complement them by enhancing the understanding of complex relationships and providing new insights. This integration ensures that models remain robust and interpretable, enabling portfolio managers to leverage the strengths of advanced analytics without sacrificing transparency or trust. Rigorous, Data-Driven Approaches to ESG Needed The increasing prominence of environmental, social, and governance (ESG) investing forms another key theme in my conversation with Hsu. He observes that demand for sustainable investment strategies has grown significantly, driven by both institutional mandates and shifting societal expectations. However, incorporating ESG considerations into investment processes presents unique challenges, particularly in quantifying ESG impact and integrating it into traditional portfolio frameworks. Hsu emphasizes the need for rigorous, data-driven approaches to ESG investing to ensure that it goes beyond superficial claims or “greenwashing.” By aligning ESG metrics with broader financial goals, asset managers can develop strategies that are both impactful and economically viable. Diversity within investment teams is another area where Hsu sees significant opportunities for improvement. He argues that fostering intellectual diversity and encouraging collaboration are essential for success in the evolving asset management landscape. Diverse teams bring varied perspectives and approaches to problem-solving, which can enhance creativity and adaptability. In an industry where market conditions and client demands constantly change, the ability to think critically and adapt quickly is invaluable. One of the most compelling aspects of my conversation with Hsu is his discussion of the challenges and opportunities in implementing factor-based strategies in real-world market dynamics. He notes that value and momentum are not static but evolve as markets change. This evolution requires constant re-evaluation and adaptation of strategies to ensure their continued relevance. Hsu highlights the importance of stress-testing factor models under different scenarios to assess their robustness and potential vulnerabilities. Customization is Key Hsu also reflects on the growing role of customization in asset management. As clients demand more tailored solutions, firms must develop strategies that address specific needs and objectives. This customization often involves creating unique factor combinations or integrating non-traditional data sources, such as alternative datasets, to enhance predictive accuracy. By aligning strategies with client-specific

In his keynote speech at the Ben Graham Centre’s 2024 Value Investing Conference in Toronto, Jason Zweig, a veteran columnist for The Wall Street Journal, asked, rhetorically: “What cannot be ETF’d?” Active investors are competing with Mr. Market, a.k.a. passive exchange traded funds, he stated. To generate meaningful alpha, portfolio managers must develop expertise in what cannot be packaged into an exchange traded fund, Zweig advised.   The target universe for active managers is what Zweig called “left tail things” like size, liquidity, marketability, and popularity factors. These are the factors inherent in small-cap companies. The spring is coiled tight in the small-cap space, and we view it as highly favorable for generating alpha. While small-cap companies are ETF’d, passive investing in this group is a sub-optimal strategy for the creation of alpha over the long term. Portfolio managers must develop expertise in this market segment. In the United States, small- and micro-cap stocks have lagged large- and mega-cap stocks for nearly a decade, based on price returns from the Russell 2000 and the S&P 500. Over the same period, the small-cap effect remained intact in the UK, Japan, Europe, and the emerging markets. What accounts for the outlier status of the United States? Institutional allocations have shifted toward private equity and away from public markets. Global private equity AUM is expected to grow to US$8.5 trillion by 2028, and American firms are leading the charge with a CAGR of 11.3%, according to Prequin. Today, fast-growing smaller companies have financing options they did not have previously. They can stay private much longer, living and growing inside the gated community of private equity. Some of these companies may never join the Russell 2000. If they grow to a sufficient size, they may jump directly to the S&P 500 or be sold to another large private equity fund.  Spotlight on Canada In Canada, the small- and micro-cap space has been in a bear market. Active small-cap-focused funds have seen outflows for the past 10 years, M&A activity is tepid, and IPO activity is weak. The total public capital raise for tech in Canada last year was down 88% from 2022 levels and 98% from 2021 levels. This has created a negative feedback loop in Canada of fleeing capital and underperformance in this sector. During the first quarter of 2024, we saw the first glimmers of change with the S&P TSX Small Cap Index (7.9%) outperforming the S&P TSX Composite Index (6.6%). Outlook for North America Market valuations rose in 2023, which should entice some private companies to go public this year or next. Any improvement in IPO and M&A activity would be a positive tailwind for small caps, which are undervalued on both an absolute and relative basis. We see a target-rich environment in small caps. The lack of research and capital has left the field wide open for astute investors. Potential catalysts for a re-rating will be improved balance sheets, increased cash flow metrics, and increased M&A and IPO activity. Tailwinds include the inflection point on rising interest rates, quality companies continuing to compound business value and clean up their balance sheets, accelerating M&A activity to take advantage of discounted valuations, and mean reversion to historical valuations and sentiment levels. The small-cap sector is best approached through an active investment strategy where expertise and a deep understanding of the individual businesses and their risk-and-reward characteristics are necessary for success. Every investor who strives for outperformance must take on potential risks, however, one of which could be periods of painful unpopularity and underperformance like we have endured in the small-cap sector since 2016. As the Norwegian chess master Magnus Carlsen has said, “Not being willing to take risks is an extremely risky strategy.”  If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images/Hanis Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

The Economics of the Stock Market. 2022. Andrew Smithers. Oxford University Press. Judging by the behavior of the stock market, we are living in challenging times for mainstream finance. Under the hypothesis that markets are efficient and investors are rational, neoclassical theory assumes away the problem of financial bubbles and the linkages between equity returns and the rest of the macro variables. After a decade of unconventional monetary policies, massive fiscal deficits, and the return of inflation, however, equity market behavior in recent years has been nothing short of perplexing, leaving most practitioners struggling to understand the vagaries of stock markets. Today, the workhorse neoclassical model requires a thorough review of its assumptions (and conclusions). Now, more than ever, we urgently need a comprehensive alternative. Andrew Smithers attempts to fill in this gap with his latest book, The Economics of the Stock Market, which offers an alternative theory of how stock markets work. The book builds on a small and obscure tradition of growth models, pioneered by Nicholas Kaldor more than 50 years ago, which dealt with distributional issues in a Harrod–Domar-type framework. One of these iterations showed that in a closed economy with two sectors (households and firms) and no government activity, equity valuation multiples are determined solely by macroeconomic variables — crucially, by the equilibrium between aggregate savings and aggregate investment. Kaldor’s framework was quite novel in that stock market valuations integrated seamlessly into the macroeconomy and were responsible for balancing saving and investment, in contrast to the Keynesian and neoclassical traditions in which the equilibrium process works through quantities (unemployment rate) and prices, respectively. Although Kaldor never intended his model to be a framework for understanding stock markets, Smithers draws on this setup to articulate a theoretical alternative. Smithers is also very “Kaldorian” in the way he constructs his framework, for two reasons. First, he is primarily interested in the long-run behavior of the system, or steady-state solutions. Second, he relies on several “stylized facts” about stock markets to inform his assumptions. In particular, four variables have historically been mean-reverting to a constant, and any model should take these into consideration: Equity returns in real terms The shares of profits (after depreciation) and labor in total output The ratio of interest payments to profits The ratio of the value of fixed capital to output (a Leontief-type production function) The first stylized fact has particular relevance to the mechanics of the overall model. For Smithers, equity returns (in real terms) are mean-reverting and tend toward a constant in the long run, at about 6.7% per annum. According to the author, this long-run constant results from capital owners’ risk aversion rather than from the marginal productivity of capital or from households’ consumption decisions. As we shall see, this dynamic has profound implications for determining returns in other asset classes. This novelty is not the only one in Smithers’s framework. His model varies from the neoclassical framework in at least three other ways. First, at the heart of Smithers’s proposal is the firm as a separate entity from households. This distinction is important because firms behave significantly differently from households. For firms, decisions on investment, dividend policy, share issuance, and leverage are made by managers whose motivation (keeping their jobs) differs substantially from that of the neoclassical utility-maximizing consumer. In Smithers’s framework, firms do not seek to maximize profits, because if they did, they would vary their investments with the cost of capital — as in investment models based on the Q ratio. Casual empirical observation appears to confirm this point — as Smithers explains, “Rises in the stock market would be constrained by a growing flood of new issues as share prices rise and their falls would be limited by their absence in weak markets. Smaller fluctuations in the stock market would seem naturally to follow.” In this respect, any model should also consider the contrasting behavior of listed and unlisted companies. According to Smithers, one consequence of more companies being listed is that the corporate sector as a whole becomes less responsive to the cost of equity (Q models). This dynamic occurs because when it comes to investment decisions, management teams’ behavior is constrained by the possibility of a hostile takeover and job loss. In other words, “managements are concerned with the price of their companies’ shares, rather than the overall level of the stock market.” One macroeconomic implication of the absence of a link between valuations and investment is that the stock market plays an important role in economic growth, by preventing fluctuations in the cost of capital from affecting the level of investment — and ultimately output. Second, the returns among asset classes are derived in an independent fashion and are not codetermined. In Smithers’s framework, a firm’s balance sheet is assumed to consist of short-term debt (which can be thought of as very liquid instruments), long-term bonds, and equity. These instruments’ returns are derived independently, and their influences on the system work through different mechanisms. Savings and investment are equated by movements in the short-term interest rate. Corporate leverage is balanced with the preferences of the owners of financial assets through variations in bond yields. Finally, as explained earlier, equity returns are stationary. Consequently, the difference in returns among asset classes — that is, the equity risk premium — is not mean reverting, it has not historically had a stable average, and its level cannot provide any information about future returns for either equities or bonds. For Smithers, the equity risk premium is a residual and bears little relationship to the role it plays in mainstream finance. Finally, for Smithers the cost of capital varies with leverage at the macroeconomic level. This conclusion diametrically opposes the 1958 Miller–Modigliani Theorem (M&M), which states that the value of a firm is independent of its capital structure. According to M&M, a firm’s risk increases with its financial leverage, so the required return on equity increases with it, leaving the overall cost of capital unchanged because debt is

As corporate collapses continue to catch stakeholders off guard, analysts face growing pressure to dig deeper than traditional audits allow. The limitations of standard financial reporting — especially in identifying “going concern” risks — have exposed systemic blind spots in evaluating a company’s true financial stability. For those involved in mergers and acquisitions (M&A), private equity (PE), or strategic planning, Quality of Earnings (QofE) analysis has become an indispensable tool. It helps surface red flags, validate financial performance, and provide a more reliable foundation for investment decisions. In this post, I will highlight why this topic is important and detail the components of QofE analysis. Why Is Quality of Earnings (QofE) Analysis Critical? Research from the Audit Reform Lab at the University of Sheffield found that auditors failed to identify material uncertainties related to going concern in 75% of significant corporate failures in the UK from 2010 to 2022. The Big Four auditing firms – Ernst & Young (EY), PricewaterhouseCoopers (PwC), Deloitte & Touche, and KPMG — provided going-concern warnings in less than 40% of situations, while smaller firms had an even more disappointing warning rate of 17%. Several high-profile cases have highlighted audit failures which reveal significant deficiencies in the auditing industry. For example, KPMG came under scrutiny for its audits of Carillion, a UK construction and facilities management company that collapsed in 2018. The Financial Reporting Council (FRC) imposed a £21million fine on KPMG for its role in the audit failures, citing serious shortcomings in the firm’s work. Similarly, EY has faced investigations related to its audits of Wirecard, a German payment processing company that fell into a massive fraud scandal. PwC has also encountered several major controversies, including a six-month ban in China for audit failures linked to the collapse of Evergrande.  While an audit report confirms that historical financial statements adhere to generally accepted accounting principles (GAAP), it does not always accurately reflect a business’s true earnings capacity. The QofE process goes beyond GAAP by adjusting for non-recurring items, normalizing revenue streams, and establishing a reliable baseline for projections and valuations. Image Source: Author Analysis While the scope of a QofE report is not strictly defined, and determining the quality of earnings can be challenging, there are three key factors that should be addressed in any QofE analysis. They are: Financial performance analysis, Proof of cash (PoC), and Net working capital (NWC) Financial Performance Analysis The revenue mix in the QofE report can sometimes highlight customer concentration as a significant risk factor. A high reliance on only a few key customers exposes the business to revenue volatility if those customers decrease their demand or terminate contracts. This concentration can lead to scenarios where the financial health of the business is heavily tied to the performance and longevity of a limited number of clients.  Furthermore, the geographical distribution of the customer base introduces different levels of risk. For example, global customers are influenced by a range of factors, including local supply and demand dynamics, economic conditions, political stability, regulatory changes, and exchange rate fluctuations. These external forces can greatly impact customers’ purchasing behavior, which, in turn, affects the company’s revenue stability.  Other areas of investigation include: Image Source: Author Analysis Proof of Cash The proof of cash (PoC) test is a critical factor in QofE analysis, offering a detailed reconciliation of cash inflows and outflows to ensure the integrity of reported financial performance. This test links the company’s reported cash transactions to its bank statements, thereby validating that the financial data aligns with actual cash movements. It helps detect discrepancies that could indicate errors, fraudulent activity, or mismanagement. The PoC test ensures the accuracy of key financial metrics like revenue, expenses, and EBITDA, which are central to a transaction’s valuation. By reconciling transactions, the test verifies that: Revenue is not overstated (e.g., uncollected sales not reflected in cash inflows). Expenses are complete and accurate and have proper cash documentation. There are no unrecorded liabilities or unusual cash activities like large transfers to related parties. The PoC test relies on three primary data sources: Bank statements: Detailed records of all cash inflows and outflows over a specific period, typically covering several months or years. General ledger entries: The company’s official record of transactions, used to match reported figures with actual cash movements. Source documents: Supporting documentation for major transactions including invoices, receipts, contracts, and payment confirmations. Net Working Capital Net working capital (NWC) is an important aspect of QofE analysis because it indicates a business’s liquidity and operational efficiency. In a QofE assessment, NWC is evaluated to ensure that the company maintains sustainable working capital levels that enable it to support ongoing operations and meet its short-term obligations without relying on external financing. NWC is calculated as the difference between current assets (receivables, inventory, etc. ) and current liabilities (payables, accrued expenses, etc.). NWC is important for QofE for many reasons including: Sustainability of operations: By analyzing trends in NWC, analysts can assess whether a company’s operational cash flow is stable and sufficient to support normal business activities after a transaction. Adjustment of purchase price:NWC is crucial for establishing what constitutes a “normal” level of working capital for the business. Deviations from this standard may lead to adjustments in the purchase price during M&A transactions, ensuring that neither party assumes undue risk. A thorough review of NWC can reveal several risks, including these: Volatility in working capital fluctuations may indicate operational inefficiencies, seasonal patterns, or poor cash flow management. Revenue recognition risks: Unusually high accounts receivable might suggest overly aggressive revenue recognition practices. Inventory concerns: Excessive or obsolete inventory may artificially inflate current assets. Liability mismatches: Large, unrecorded, or unusual current liabilities can indicate hidden risks or mismanagement. Operational insights: Analyzing NWC often uncovers underlying issues such as customer concentration risks, supplier payment delays, or inventory turnover trends. These factors can significantly affect a company’s valuation and operational viability. While evaluating NWC is crucial, it is equally important to estimate the cash requirements needed to support working capital for the first 30

The Ongoing Influence of Fed Intervention The markets responded immediately when the US Federal Reserve announced it would intervene in corporate credit markets to bolster the economy amid the pandemic outbreak. Swift central bank action combined with fiscal stimulus drove an incredible economic rebound and a massive rally in risk assets that sent credit spreads back to pre-COVID-19 levels by year-end 2020. Still, the low spreads in late 2020 and throughout much of 2021 were not unprecedented. Similar spreads preceded both the pandemic and the global financial crisis (GFC) without COVID-19-levels of monetary and fiscal support. Spread volatility tells a similar story. As the figure below demonstrates, spread volatility in the United States decreased significantly from its peak during the March 2020 selloff. But the low volatility post-pandemic was well within historical norms and did not signal a regime change. Post-Pandemic Spreads Are Not Unprecedented As of 31 December 2021Source: ICE data Unlike their European counterparts, US investment-grade month-end spreads widened to within 20 basis points (bps) of the fair value model’s estimates in March 2020. By late March 2020, the Fed had announced its corporate bond purchases and the market had begun to recoup its losses. To be sure, any model that anticipates something as complicated as compensation for credit risk should be treated with caution. Yet even as the European Central Bank (ECB) reactivated its corporate sector purchase programme (CSPP) before the pandemic, European credit spreads did not follow the model like their US counterparts. And Neither Are Volatility Spreads As of 31 December 2022Sources: ICE data and MacKay Shields Credit Spread Model Suggests Credit Is Fairly Priced As of 30 June 2022Source: UBS But what about the options markets? Do they offer any insight into the existence of a “Fed put” in US credit markets? After all, if investors anticipate less volatility in the future and smaller losses during stress events, then downside protection in options markets should be cheaper. The following figures visualize the implied spread widening from CDX IG 3m 25d Payer swaptions compared with periods when actual CDX spreads increased by more than 50 bps. As credit spreads grew, the cost of protection rose. Since the last major credit market drawdown in 2020, volatility and the cost of protection had both stabilized. That is, until recently. Indeed, we may be on the cusp of a major stress event. The macro picture is evolving, inflation remains a concern, and some indicators suggest an approaching recession. As credit spreads widen, the coming months may reveal quite a bit about market expectations around central bank interventions. “Fed Put” Not Yet Reflected in the Cost of Insurance As of 29 July 2022.Shaded area represents widening of spreads.Sources: Bloomberg, Goldman Sachs, and MacKay Shields. Legal and Political Context The Federal Reserve Act defines what lending activities the central bank can engage in, and in Section 14 it outlines what sorts of financial assets it can buy. Corporate bonds are not among the securities Federal Reserve banks are allowed to purchase in the secondary market. But the Fed has worked around this by applying its broader lending powers. Specifically, the Fed can lend to a facility that it creates, which can then purchase assets with those funds. The Fed used this technique during the GFC, including for the Commercial Paper Funding Facility (CPFF). All the Fed’s lending activities must be “secured to [its] satisfaction,” and the assets in the facility should, in theory, serve as collateral. But since the facility will only fail to return loaned funds to the Fed if the assets do not perform, they do not constitute adequate collateral. Thus, in each of the two pandemic response facilities — the Primary Market Corporate Credit Facility (PMCCF) and the Secondary Market Corporate Credit Facility (SMCCF) — funds provided by Congress under the CARES Act served as a first-loss equity investment. In protecting the Fed from losses, these investments ensured the central bank was secured to its satisfaction. Since the Fed established the two corporate credit facilities shortly before the CARES Act became law, the 23 March 2020 announcement noted that Treasury would use funds from the Exchange Stabilization Fund (ESF) to provide equity for the facilities. In contrast to these explicit first-loss investments in Federal Reserve facilities, the Treasury backstop of the CPFF during the GFC was less formal. Under the time pressure of the Lehman Brothers default and the subsequent run on money funds, and absent clear precedent, the Treasury simply announced a deposit at the Fed with money from the ESF as an implicit first-loss contribution to the CPFF. Section 13, Paragraph 3, of the Federal Reserve Act limits Fed lending to “unusual and exigent circumstances,” or during financial market crises and other periods of stress. These conditions applied to the PMCCF, which was intended as an alternative source of funds for corporations that couldn’t borrow from banks or in credit markets. These conditions include: A prohibition on lending to a single entity, so lending must be conducted through a program with broad-based eligibility. Program participants must demonstrate they can’t secure adequate credit from other sources. Participants may not be insolvent. The program or facility may not be structured “to remove assets from the balance sheet of a single and specific company, or . . . for the purpose of assisting a single and specific company avoid bankruptcy.” A stronger oversight role for Congress via detailed and timely reporting requirements. Prior approval of the Treasury Secretary for establishing an emergency lending facility. With the Dodd–Frank Act of 2010, Congress added these conditions to the Federal Reserve Act as a way of keeping the Fed from acting unilaterally in future crises. For example, these conditions would preclude an AIG-style bailout. In addition, the Treasury Secretary approval requirement would help ensure that elected officials, working with a congressionally confirmed cabinet member, could influence and oversee the creation and design of any emergency lending facilities. The 2020 pandemic suggests the Dodd–Frank Act may have strengthened the Fed’s policy response. Treasury Secretary Steven Mnuchin’s formal approval

When someone hears I’m currently writing the authorized biography of William (Bill) Sharpe, the most frequent question I get is, “Is he still alive?” Sharpe is the 1990 recipient of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, commonly known as the Nobel Prize in Economics. And, yes, in September 2024, he is still alive and well. He lives in Carmel-by-the-Sea in California. Every Thursday morning, he meets with his coffee klatch. He can often be seen walking his bichon-poodle near Carmel Bay. In June 2024, he celebrated his 90th birthday. And September 2024 was another Sharpe milestone: the 60th anniversary of his seminal capital asset pricing model (CAPM) paper in The Journal of Finance. It is extremely rare for research to remain relevant after a decade let alone six. I’ll explain what the paper is about, how it impacted the investment industry, most likely including your own portfolio, and why it still matters. Photo by Stephen R. Foerster The C-A-P-M Let’s talk about the model’s name, common acronym, and what it’s really about. First, Sharpe never called it the “capital asset pricing model.” As the title of his seminal article indicates, it’s about “capital asset prices.” Later researchers referred to it as a model, adding the M. Second, once it became known as the capital asset pricing model, it was referred to by the acronym CAPM, pronounced “cap-em.” Virtually every finance professor and student refer to it as “cap-em” — everyone except Sharpe himself. He always uses the initialism C-A-P-M. (So, if you want to honor the creator of the model, you can refer to it as the C-A-P-M!) Third, the focus isn’t really about prices of assets, but rather their expected returns. One of the key insights of the CAPM is that it answers an important investment question: “What is the expected return if I purchase security XYZ?” Key Assumptions Sharpe had written a paper published in 1963, “A Simplified Model for Portfolio Analysis,” that presented some of the same key concepts as in the seminal 1964 paper. There is an important difference between the two papers. As Sharpe later described it, in the 1963 paper, he carefully “put the rabbit in the hat” before pulling it out. The 1963 paper also answered that key question, “What is the expected return if I purchase security XYZ?” But the rabbit he put in the hat was a preordained relationship between a security and the overall market — what I’ll describe later as beta. Andrew Lo and I interviewed Sharpe for our book, In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest. “So, I spent several months trying to figure out how to do it without putting the rabbit in the hat,” he said. “Was there a way to pull the rabbit out of the hat without putting it in to begin with? I figured out yes, there was.” In the 1964 article, Sharpe didn’t put a rabbit in the hat but rather he derived a market equilibrium based on theory. With any theory, you need to make assumptions, to simplify what happens in the real world, so that you can get traction with the theoretical model. That’s what Sharpe did. He assumed that all that investors care about are expected returns and risk. He assumed investors were rational and well-diversified. And he assumed investors could borrow and lend and the same rate. When Sharpe initially submitted the paper for publication in The Journal of Finance, it was rejected, mainly because of Sharpe’s assumptions. The anonymous referee concluded that the assumptions Sharpe had made were so “preposterous” that all subsequent conclusions were “uninteresting.” Undeterred, two years later Sharpe made some paper tweaks, found a new editor, and the paper was published. The rest, as they say, is history. The CAPM in Pictures Much of Sharpe’s classic paper focuses on nine figures or graphs. The first seven are in two-dimensional space, with risk — as measured by the standard deviation of expected returns — on the vertical axis and expected return on the horizontal axis. (Any finance student will quickly note that the now-common practice is to flip axes, which is represent risk on the horizontal axis and expected return on the vertical axis.) On his horizontal axis, Sharpe began with the return on a special security that he called the “pure interest rate” or P. Today, we would refer to that special rate as the Treasury Bill return, or the risk-free rate, commonly represented as Rf. The curve igg’ is Harry Markowitz’s efficient frontier: the “optimal” combination of risky securities such that each portfolio on the curve has the highest expected return for a given level of risk, and also the lowest risk for a given level of expected return. Sharpe’s model essentially looked for combinations of the risk-free security, P, with each portfolio on the curve igg’ that would provide the optimal risk-expected return. It is clear from the graph that the optimal mix is formed by a line from P that is tangent to curve igg’ — in other words, the mix that combines the risk-free asset P and portfolio g. In Sharpe’s world, we can think of the investor as essentially having three choices. She can invest all of her money in risky portfolio g. If that’s too much risk for her, she can divide her portfolio between combinations of risk-free P and risky g. Or, if she wants even more risk she can borrow at the risk-free rate and invest more than 100% of her wealth in risky g, essentially moving along the line toward Z. The line PgZ is Sharpe’s famous Capital Market Line, showing the optimal combination of risk-free and risky investments, including either lending (buying a Treasury Bill) or borrowing (at the Treasury Bill rate). The Footnote that Won a Nobel Prize After presenting a series of graphs, Sharpe showed how this could lead to “a relatively

The cannabis sector is slowly emerging from its long period of prohibition, and the investment opportunities are turning heads. Retail investors believe in the industry’s future and want to participate before regulations change. The institutions covering the sector are keeping a close eye on it even if most have yet to dip their toes in. The cannabis industry constitutes a new frontier in investing and is ripe with growth opportunities. The hype and speculative froth of 2018 and early 2021 has burned off, and the market is right sizing: Valuations are more reflective of actual profitability, as cannabis companies suffer from the same dearth of capital as other areas of the private markets even as more US states legalize cannabis use. So, How Did We Get Here?  This is not the first time US consumers have had access to legal weed. In the colonial era, governments encouraged cannabis cultivation. The Virginia Assembly required farmers to grow hemp, a non-psychoactive cannabis variety used in the production of sails, ropes, and other textiles, and George Washington and Thomas Jefferson, among others, produced the crop. By the late 19th century, consumers could buy psychoactive cannabis at their local pharmacy.  The US government made its first foray into this otherwise free market in 1906 when it required that cannabis-infused products be labeled as such. But the real change in the perception and regulation of cannabis came with the Marihuana Tax Act of 1937, which ushered in the Reefer Madness era. Spearheaded by Harry Anslinger, commissioner of the Federal Bureau of Narcotics (FBN), a precursor to the Drug Enforcement Agency (DEA), the law sought to criminalize the sale and possession of cannabis. As the years progressed, cannabis became associated with the countercultural movements and anti-war protests of the 1950s, 1960s, and 1970s, and new laws imposed ever more severe penalties. But in the last few decades, amid a slow change in sentiment, the pendulum has begun to swing back, and prohibition has given way to pre-Anslinger acquiescence if not acceptance. California became the first state to legalize medical cannabis in 1996, and Colorado and Washington became the first to legalize recreational use in 2012. Today, recreational cannabis is legal in 23 states and its medical use in many more. Still, psychoactive cannabis remains illegal at the federal level. Today’s Fragmented Landscape  But as more states legalize cannabis, more Americans favor federal legalization. Young people are drinking less alcohol and consuming more marijuana. The stigma associated with cannabis use has dissipated. Among older cohorts, the market for cannabis wellness products shows great growth potential. The federal government last year removed a big hurdle in this regard. It withdrew the prohibition of federal funding for medical cannabis research and allowed doctors to discuss cannabis with their patients. Still, as a drug, cannabis retains the highest risk classification, along with heroin, LSD, and ecstasy, and is considered to have no proven medical benefit. According to these ratings, cocaine, methamphetamine, and fentanyl have a lower risk of abuse than cannabis. With more research into its medical benefits and lower potential for abuse, the pressure to reclassify cannabis will increase. Cannabis investing encompasses not only plant-touching companies — the growers, edible and joint manufacturers, and dispensaries — but also companies that provide services to cannabis firms, from technology to fertilizers. Plant-touching companies incur the federal government’s punitive cannabis tax structure. Because cannabis is still classified as an illicit substance, cannabis companies can deduct expenses only for cost of goods sold (COGS). This leaves a high effective tax rate that hits dispensaries, with their large staffing costs, especially hard.  That is why the prospect of federal legalization and relief from such tax treatment so excites investors. But their optimism is likely misplaced: They shouldn’t hold their breath. Much of the investment capital in the cannabis space continues to flow to non-plant-touching companies. This sell-shovels-to-gold-miners approach has obvious appeal. Businesses can avoid punitive taxation and potentially achieve greater profitability with less legal risk. Where Is the Money? Since it is illegal at the federal level, cannabis cannot be transported across state lines, nor can any capital associated with it be transmitted through the federal financial wire system. What this means in practice is that each state has its own microcosm of brands, products, plant types, and financial arrangements. The landscape for cannabis investors in Arkansas looks much different from what it does in California. This ecosystem of small players in small markets exists parallel to that of so-called multi-state operators. Such organizations set up individual companies in different states under the same name and can thus claim a cohesive multi-state operation, even if they can only sell their wares in the state where they were grown and manufactured. Multi-state operators have attracted most of the related investment capital. Their valuations shot to the moon amid the social isolation associated with the COVID-19 pandemic, the concomitant increase in recreational drug use, and expectations of potential federal legalization under a new Democratic administration. Needless to say, the hype going into 2021 was just that — a Green Rush — and cannabis valuations soon fell back to earth. Historical prices of MSOS, the first US focused cannabis exchange-traded fund (ETF), reflect this trajectory. AdvisorShares US Pure Cannabis ETF (MSOS) Performance2 September 2020 to 18 October 2023 Source: Bloomberg  Multi-state operators are now focused on consolidation and cost cutting. Smaller operators are either finding their competitive niches or shutting down. And a host of burned investors are vowing never to put money into cannabis. In other words, there is lots of blood on the cannabis sector’s streets. Many cannabis-focused investment shops opened during the bubble, when investors were throwing money at anything that smelled like marijuana. Several have lost more than 60% of their initial value and have conjured cannabis-market benchmarks to rationalize this massive wealth destruction.  While raising money for cannabis investments is much harder today, investors are still interested in the opportunities this nascent industry offers. Without reliable benchmarks or historical averages on

Faced with rampant inflation, central banks worldwide are raising interest rates. In June, the US Federal Reserve announced its largest hike since 1994. The previous month, the Bank of England (BOE) had pushed UK rates to a 13-year high. The central banks of Brazil, Canada, and Australia have also hiked, and the European Central Bank (ECB) plans to follow suit later this month. Such rate increases not only create turmoil in risk markets; they also can threaten a company’s financial stability. The devil is in the details when quantifying how these hikes will influence a firm’s bottom line. Beyond the obvious implications on financing costs, capturing the impact on economic value requires a more strategic and holistic approach. As we demonstrate here, the effect differs according to how heavy and active the company’s assets and liabilities are. The calculation becomes even more complex for finance or investment firms that juggle multiple balance sheets at once. Yet financial risk management and market risk hedging are critical to every firm’s prosperity, so analysts need to understand the available tools. Economic Value of Equity (EVE) Economic value of equity (EVE), or net worth, defines the difference between assets and liabilities according to their respective market values. EVE represents the income or loss a firm faces during the chosen horizon or time bucket. Hence, EVE reflects how assets and liabilities would react to changes in interest rates. EVE is a popular metric used in the interest rate risk in banking book (IRRBB) calculations, and banks commonly measure IRRBB with it. But EVE can also help companies — and the analysts who cover them — calculate the risk to their dynamic assets and liabilities. The metric looks at the cash flow calculation that results from netting the present value of the expected cash flows on liabilities, or the market value of liabilities (MVL), from the present value of all expected asset cash flows, or the market value of assets (MVA). While EVE, as a static number, is crucial, what also matters to a company’s health is how EVE would change for every unit of interest rate movement. So, to calculate the change in EVE, we take the delta (Δ) of market values for both assets and liabilities. That is, ΔEVE = ΔMVA – ΔMVL. The beauty of this measure is that it quantifies the ΔEVE for any chosen time bucket and allows us to create as many different buckets as we require. The following table tracks the changes of a hypothetical company’s EVE assuming a 1 basis point parallel increase in interest rates. Bucket ΔMVA ΔMVL ΔEVE 1-month -$13,889 $35,195 $21,306 2-month -$27,376 $9,757 -$17,620 3-month -$39,017 $16,811 -$22,205 6-month -$180,995 $72,449 -$108,546 1-year -$551,149 $750,815 $199,667 3-year -$3,119,273 $1,428,251 -$1,691,023 5-year -$1,529,402 $115,490 -$1,413,912 More than 5-year -$264 $403 $139  Net Change -$5,461,364 $2,429,170 -$3,032,194 What Is an Acceptable EVE? Economic intuition tells us that long-term assets and liabilities are more vulnerable to interest rate changes because of their stickiness, so they are not subject to re-fixing in the short term. In the chart above, the net change in EVE is -$3,032,194 for every basis point increase across the interest rate curve, and we have the necessary granularity to determine the buckets where the company is most vulnerable. How can a firm bridge this gap? What is the optimal allocation between the duration/amounts of assets and liabilities? First, every institution has its own optimal allocation. One size does not fit all. Each firm’s risk profile and pre-set risk appetite will drive the optimal EVE. Asset and liability management (ALM) is doubtless an art: it helps translate the company’s risk profile into reality. Since EVE is primarily a long-term metric, it can be volatile when the interest rate changes. This necessitates applying market best practices when following a stressing technique, such as value at risk (VaR), that helps to understand and anticipate future interest rate movements. On and Off the Balance Sheet A company can manage the EVE gap between assets and liabilities — and the related risk-mitigation practices — either on the balance sheet or off it. An example of on-balance-sheet hedging is when a firm simply obtains fixed interest rate financing, rather than linking it to a floating index, such as US LIBOR, or issuing a fixed bond to normalize the duration gap between assets and liabilities. Off-balance-sheet hedging maintains the mismatch in the assets and liabilities but uses financial derivatives to create the desired outcome synthetically. In this approach, many firms use vanilla interest rate swaps (IRS) or interest rate cap derivative instruments. Details of the balance sheet gap are not always available for examination when reviewing the financial statements. However, decision makers and investors must pay attention to it and be vigilant because the EVE metric captures the market value of the cumulative cash flows over the coming years. And as we’ve shown above, calculating it is simple. A Safety Valve for an Uncertain Future With a little due diligence, we can better understand how a company manages its interest rate exposure and associated ALM processes. Although banks and large financial institutions make ample use of the EVE indicator, other companies ought to as well. And so should analysts. When a firm sets limits for risks, monitors them, and understands the accompanying changes in value due to interest rate movements and how they will impact its financial position, it creates a safety valve that protects against market risks and an uncertain interest rate outlook. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images/Heiko Küverling Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

A version of this article originally appeared on the Research Affiliates website. The current economic environment is a confusing one. Job growth is strong, yet reports of layoffs at high-profile companies are ubiquitous. The yield curve is inverted, implying an imminent recession, but the stock market is at or near record highs. What can we make of these contradictory signals? Can the economy achieve the hoped-for soft landing of slower economic growth or a mild recession? Or is a hard landing and a regular or even severe recession inevitable? Provided the US Federal Reserve awakens from its slumber and certain other mitigating factors persist, I believe we can still stick the landing. But many pieces have to fall into place. The inverted yield curve casts a long shadow. I unveiled this economic growth and recession indicator in my dissertation many years ago. Since the 1960s, it has anticipated eight out of eight recessions and has yet to send a false signal. Measured as the difference between the yields of the 10-year Treasury bond yield and the three-month Treasury bill, the yield curve inverted in November 2022, leading many to expect a recession in 2023. When none materialized, some concluded that the yield curve had sent a false signal. That judgment was premature. Over the last four cycles, an inverted yield curve has given, on average, 13 months’ advance warning of a recession. The yield curve inverted only 16 months ago, which is not that far off the mean. Furthermore, over the last four cycles, short rates have fallen back to their “normal” position below long rates — that is, the yield curve “uninverts” — before the recession begins. That uninversion has yet to occur. Given the yield curve’s track record, we ignore it at great peril. It now indicates growth will substantially slow in 2024 and may or may not lead to recession. Even in a soft-landing scenario, a minor recession is possible. That has happened twice before, in 2001 and from 1990 to 1991, with GDP drawdowns around 1%, as shown in the following chart. The key is to avoid a deep recession like the one associated with the global financial crisis (GFC). Total GDP Decline in Recession, Peak to Trough The US economy delivered 2.5% real GDP growth in 2023 and expanded at a 3.3% rate in the fourth quarter. I expect much slower growth in the first and second quarters in 2024 because of four headwinds in particular: Four Headwinds 1. Consumer Behavior Personal consumption expenditure is the most critical component of GDP, representing 68% of overall growth. Consumer spending drove much of the 2.5% year-over-year (YoY) expansion in real GDP in 2023. Combined personal consumption and government spending accounted for 87% of that growth. What explains this strength? During the pandemic, consumers amassed $2.1 trillion in excess savings, according to the Fed, so there was considerable pent-up demand as well as generous government support programs. Consumers have been drawing these savings down, which fueled their 2023 spending binge. Investment is another key aspect of GDP, and it did not benefit from such government support. In fact, with negative YoY investment in 2023, it may already be in a recessionary state. The leading indicators of consumer savings are important to watch. When savings run out, spending contracts. Consumer loan delinquencies, for example on autos and credit cards, is an intuitive metric. Consumers will only borrow on credit cards with rates in the 20% range when their savings have run dry. Delinquencies have been trending upward, signaling that consumers have depleted much of their savings. Other technical factors also come into play. In October 2023, the pandemic-era pause in student loan repayments ended, and roughly 40 million Americans had to begin repaying this debt directly out of their disposable income. 2. Credit Conditions The largest banks offer only a few basis points in annual interest on savings deposits. The average savings rate is about 0.5% and skewed by somewhat higher rates at small and regional banks. It may not receive much attention, but this indicates bank weakness and is bad news for the economy. Consumers can move their savings into money market mutual funds (MMMFs) and easily receive a 5% rate of return. Capital is flying from savings accounts to ultra-safe MMMFs. This has two implications: As assets move to MMMFs, banks have less to lend. While the effect is not immediate, credit conditions should tighten this year. That means lower spending by consumers and businesses and, as the cost of capital rises, reduced business investment. Many consumers will not transfer their assets to MMMFs. Some don’t know that their savings account interest rate is so low, and others have small balances that might not qualify for MMMFs or enhanced savings rates. These consumers suffer as the value of their modest assets erodes because their savings rates are so much lower than the current rate of inflation. Yield Disequilibrium 3. Commercial Real Estate (CRE) COVID-19 structurally changed the nature of work in the United States. We now live in the era of remote and hybrid work, of work from home (WFH). Public transportation use plummeted during the pandemic and then recovered somewhat but has yet to return to pre-COVID-19 levels. Indeed, the data are flattening out well beneath where they were in early 2020, which is consistent with a structural change. New York Metropolitan Transportation Authority (MTA): Daily Ridership Decline Relative to Pre-Pandemic Equivalent Day San Francisco, among other cities, has enormous office vacancy rates. The commercial real estate (CRE) market will be a big story in 2024. While the sector had problems in 2023, the media didn’t pay much attention — probably because the loans were not coming due — but they will soon. Refinancing will be necessary this year. This poses a risk to banks, CRE’s principal financiers. The recent plunge in the value of New York Community Bancorp is just one indication of the stress regional banks are under. 4. Interest Service Obligations on