CFA Institute

People who are extremely successful in business or investing tend to think of themselves as more skilled and hard working than the average person. No doubt they are on some level, but the more extreme their success, the greater the role luck plays in achieving it. Luck is so critical to extreme success, in fact, that those who attain it do so almost entirely due to luck. No offense intended to any readers, it’s just a matter of math. Let me explain. We are all enthralled by the most successful people in the world. Jeff Bezos and Bill Gates are inspirations to many aspiring business leaders, and Elon Musk has become a rock star thanks to both his enormous business achievements and his personal antics. In the investment world, we look up to all-time legends like Warren Buffett as well as star fund managers with a string of good returns like Cathie Wood in 2020. We all know that a combination of luck and skill determines the performance of investors and business leaders alike. But what we don’t realize is that even if luck plays a minor role in general, it dominates at the extreme tails of the distribution. To see how this works, I simulated the performance of 10,000 investors, with their skill randomly distributed between 0% and 100%. At the same time, these investors had varying degrees of luck, with that attribute also randomly distributed between 0% and 100%. Overall, total success in this model is driven 95% by skill and just 5% by luck. If luck plays such a minor role in success, becoming a top investor should mostly be a matter of skill. But it isn’t. The chart below illustrates the average luck score of our 10,000 investors as their performance moves upward from the mean to greater and greater success. Average Luck of Investors as Their Performance Improves, When Luck = 5% of Performance Source: Liberum Of course, the average luck for all investors is 50%. Those who end up in the top quartile or in the top 10% tend to have slightly better luck than average. But the investors who end up in the top 1% or 0.1% have an awful lot of luck. Even though luck plays only a 5% role in determining success, to end up in the top 1% or top 0.1%, investors have to be very lucky indeed. That also implies that the common approach of emulating the most successful investors or business leaders likely means following less-skilled individuals. The following graphic inverts the process and explores the likelihood that those in the top 25% really have top 25% skill. Among the top quartile investors in our simple model, 97% have top quartile skill, while 94% of top 10% performers have top 10% skill. However, only half of the top 1% performers truly have top 1% skill, and out of the top 0.1% performers, only one in 10 truly has top 0.1% skill. Share of Investors with Skill Corresponding to Performance, When Luck = 5% of Performance Source: Liberum And again, these numbers are based on a model in which skill accounts for 95% of success. In real life, or at least in the investment world, I suspect luck plays a much larger role, probably somewhere close to 50%. The chart below shows the share of investors with skill corresponding to their performance when skill accounts for 55% of total performance and luck for 45%. Only six out of 10 top quartile managers truly have top quartile skills. And only one of seven top 1% investors truly have top 1% skills. Oh, and on average, none of the top 0.1% investors have top 0.1% skills. They are all there because they got very, very lucky. Share of Investors with Skill Corresponding to Performance, When Luck = 45% of Performance Source: Liberum And now remember that most, if not all, of the people who read this are in the top 1% of some sort. If you earn more than £50,000 a year, you are in the top 1% of global income. If you live in the United Kingdom and earn more than £58,300 a year (before taxes), you are in the top 10% in the UK, and if you earn more than £180,000 a year, you are in the top 1%. That is, you are in the top 1% of a country in the top 10% of all countries. And whatever that is, it’s probably more the result of luck than skill. For more from Joachim Klement, CFA, don’t miss Risk Profiling and Tolerance and 7 Mistakes Every Investor Makes (and How to Avoid Them) and sign up for his regular commentary at Klement on Investing. 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/RomoloTavani 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

ESG investing was built for a world that mostly behaved. The idea was simple: channel capital to climate-conscious companies, inclusive workplaces, and ethical supply chains, and the planet — not just your portfolio — would benefit. And for a while, it worked. ESG scores became a badge of honor. Funds slapped leaves on their logos. Boardrooms started sounding like climate summits. Everyone relaxed, like we had found the formula for saving the world and feeling good about our quarterly reports. This is not a rejection of ESG but a recognition that good intentions need backup plans. The world has reminded us that cooperation isn’t a constant; it’s a convenience. And lately, it’s been anything but convenient. Supply chains have broken down like cheap umbrellas. Ransomware attacks have shut off pipelines and exposed just how vulnerable critical infrastructure is. Energy supplies have turned into geopolitical poker chips. Semiconductors have sold out faster than an IPO with “AI” somewhere in the name. It has become clear that volatility isn’t the exception; it is the architecture. So, the question for asset managers and analysts is no longer just: Does this company have a solid climate pledge? It is now: Can this company still function if its cloud provider ends up on a sanctions list? Can it keep delivering products if its key supplier sits on the wrong side of a border dispute? What happens when the grid fails or data leaks? When “free trade” starts to unravel enough to make David Ricardo roll over in his grave? In short, the market has stopped applauding good intentions and started testing whether companies can withstand the world’s mess. From Virtue to Viability That shift — from idealism to viability — makes it clear that we need a new approach. So, I’m proposing ARMOR, which is short for Allocation for Resilient Markets and Operational Readiness. It borrows from how the US government frames national security objectives — not just as military defense, but as economic resilience, supply chain security, and infrastructure continuity. ARMOR gives institutional investors a practical way to evaluate ESG. It doesn’t reject ESG, it extends it. ESG asks if a company is sustainable in principle. ARMOR pushes further, asking if it’s built to survive in practice. Resilience Isn’t an Appendix Item That’s how ARMOR shifts the conversation. In this framework, resilience isn’t about having a perfunctory mention of cybersecurity buried in an appendix — the place where essential topics are acknowledged, then quickly forgotten. It’s about whether operations continue when energy is rationed. It’s about whether a company’s data are stored in a jurisdiction that might suddenly become adversarial, or whether its suppliers are all parked along a trade route that turns into a geopolitical flashpoint. ARMOR asks those questions up front, not after the fact. When Models Miss the Real Risk Value-at-Risk doesn’t blink when global tensions rise. Sharpe ratios don’t care if a company ends up on a sanctions list. A company might look great on paper — low beta, smooth returns, maybe even a shiny ESG report — and still get blindsided by a geopolitical punch it didn’t see coming. That’s the blind spot ARMOR is designed to fill. It doesn’t just ask whether a company is financially healthy or ethically branded, it asks whether the lights stay on when the grid flickers, whether a business can still access its cloud provider if legal jurisdictions shift, and whether it has a plan B when trade routes turn into flashpoints or critical suppliers end up on a watchlist. Building Portfolios That Survive the Mess ARMOR blends portfolio strategy with geopolitical foresight. It’s not a vibe check — it’s a real-world stress test. Instead of optimizing for sunny days, it prepares for storms. And let’s be clear: this isn’t just about dodging risk for safety. It’s about staying in the game. Because when fragility hits, the companies that survive — not just look good surviving — are the ones that end up leading. That’s not just resilience. That’s performance with staying power. In this world, real diversification isn’t just spreading across sectors or regions. It’s about asking deeper questions. Are all your holdings relying on the same chip supply? The same cloud jurisdiction? The same energy corridor? If so, your “diversification” might be an illusion waiting to crack. ARMOR flips the script. It says to stop measuring what looks efficient and start measuring what endures. That doesn’t mean throwing away Sharpe ratios or ESG filters. It means adding a layer that checks for durability when the rules of the game change, and lately, they have changed fast. ARMOR won’t appear on your Bloomberg terminal yet. It’s a mindset — and increasingly, a toolkit — for navigating an asset management future where geopolitical shockwaves, infrastructure bottlenecks, and cross-border data fights aren’t rare. They’re becoming regular fixtures in headlines, earnings calls, and risk memos. Resilience Is the Future of Performance The world in which investors operate has changed, and the playbook needs updating. ARMOR is a step in that direction — not as a replacement for ESG or traditional models — but as a necessary add-on for a world where supply chains tangle, cloud access can vanish overnight, and resilience isn’t a luxury, it’s a survival strategy. In an era when stability can’t be assumed, asset managers must look beyond performance metrics and ask more complex questions about continuity, jurisdiction, and control. This new reality is not just about which companies perform but which ones endure. source

“Every individual . . . intends only his own gain; and he is in this . . . led by an invisible hand to promote an end which was no part of his intention . . . By pursuing his own interest, he frequently promotes that of the society more effectually than when he really intends to promote it.” — Adam Smith, The Wealth of Nations In a book nearly 400,000-words long, the above quote is Adam Smith’s sole reference to the “invisible hand.” Nevertheless, his metaphor inspired the belief, particularly over the last half century, that laissez-faireism fosters economic development. But contrary to the orthodoxies of classical and neoliberal economics, free markets do not, and never did, create perfect competition. Indeed, perfect competition is an urban legend that is easily debunked. Demystifying the Theory What assumptions underlie a perfectly competitive landscape? 1. Products and services are homogeneous, substitutable, and interchangeable. Oddly, if true, this argument would justify market concentration, because product standardization increases the potential for economies of scale. A few major players often dominate industries with broadly indistinguishable products. The four ABCD firms — Archer Daniels Midland (ADM), Bunge, Cargill, and (Louis) Dreyfus — largely direct the global grain trade, and four major players exert a similar influence over the palm oil sector. 2. Firms cannot set their own prices. “The price of monopoly is upon every occasion the highest which can be got,” Smith explains. “The natural price, or the price of free competition, on the contrary, is the lowest which can be taken, not upon every occasion indeed, but for any considerable time together.” Yet many firms proactively influence prices. In retail distribution, supermarkets counterbalance the pricing power of Coors, Heinz, and other large brands by making access to consumers conditional. Even when circumstances may not favor price-setting, market participants may still try to set them illegitimately. For example, energy trader Marc Rich + Co cornered the world aluminum market in 1988 and attempted to repeat the feat with zinc four years later. 3. The market is fragmented. On the contrary, extreme concentration is common. Sectors as diverse as grocery stores, digital operating systems, social media, automotive, and audit all have only a few major players. Even consolidation-averse creative industries are far from immune: The five largest advertising agencies account for the bulk of the global market. 4. Consumers and producers have perfect information about products, substitutes, and prices. We may know where in our neighborhoods to purchase cheaper bread or movie tickets, but in a digital and global economy with increasingly diverse sources of supply, there is simply too much data for us to sift through and too many variables for us to consider. Comparison websites can help us bridge the gap, but they only operate in utilities and such commoditized services as energy, travel, and insurance. 5. Barriers and costs to market entry and exit are low. For perfect competition, suppliers must have easy access to an industry as well as an easy out. But such conditions are rarely met. Think of sectors that require heavy capital commitments, such as semiconductors and aerospace — Airbus and Boeing; those that benefit from network effects, including social platforms; or those where a strong brand is nurtured over several decades of advertising spend, which gave us Coke and Apple. Opening Up to Competition The economist Léon Walras formulated the concepts of perfect competition and market equilibrium a full century after the publication of The Wealth of Nations. Smith himself never framed his treatise in those terms, even if his views inspired many to do so in his name. His reference point was drastically different. The 18th-century marketplace was organized locally around farming communities and controlled by individual landlords as well as small textile and machine tool concerns established by craftsmen, alongside monopolies of artisans and merchants sometimes still operating as guilds. The Industrial Revolution was in its infancy and hardly noticeable — the phrase would first be recorded in 1799. Corporations were government-backed agencies such as British East India Company and its European counterparts. State policies sought to guarantee domestic supply. In 1665, France’s first Minister of State Jean-Baptiste Colbert established a factory to manufacture mirrors, a popular luxury item of the day. That national monopoly would later become Saint Gobain. In short, free markets did not exist in Smith’s time. But by the time Walras had enhanced the theory, they were meant to evolve, somewhat magically, towards an equilibrium with a set price for a given quantity of goods. Market Equilibrium under Perfect Competition Visible Sleight of Hand According to modern economic theory, in an unregulated landscape, many buyers meet many sellers, and neither side of a transaction can unduly affect the price discovery process. “Although Adam Smith could never prove his theory, he did have a point. Modern economists now know that there is a sense in which people’s selfish actions are led as if by an invisible hand toward a harmonious final result,” Paul Samuelson and William Nordhaus observe in Economics. “[A]n economy driven by perfect competition leads to an efficient level and allocation of inputs and outputs.” But such an economy has never existed. In the 19th century, telegraphy, railroads, and other emerging industries quickly consolidated as small and local operators gave way to national juggernauts. Indeed, by 1900, seven railway companies controlled the US market, and Western Union had monopolized telegraphy, bypassing the postal monopoly. In a free market, even corporations that have been broken up because of their monopolistic positions tend to reconsolidate. AT&T dominated the telecom industry in the United States for most of the 20th century. US regulators split it into seven independent regional operators, the “Baby Bells,” in the 1980s. Four decades later, after further market liberalization, the sector reconcentrated around three players: Verizon, T-Mobile, and AT&T, which had re-aggregated several Baby Bells. It is a standard progression: Dismantled monopolies often reconstitute themselves. After the 1911 dissolution of Standard Oil into 34 separate companies, the surviving entities

Rebalancing is a fundamental strategy for maintaining portfolio diversification, but it comes with a hidden cost that can significantly impact returns. Predictable rebalancing policies expose large pension funds to front-running, resulting in billions of dollars in annual losses. Rebalancing ensures consistent diversification in equity and fixed-income portfolios. Without it, a traditional 60-40 portfolio wouldn’t stay 60-40 for long. In a bull market, for example, the equity would eventually overwhelm the portfolio. But a rebalanced 60-40 portfolio is still an active strategy that buys losers and sells winners. As my previous research shows, such rule-based rebalancing policies can increase portfolio drawdowns. Portfolio rebalancing has a much larger issue, however, one that costs investors an estimated $16 billion a year, according to my new working paper, “The Unintended Consequences of Rebalancing,” co-authored with Alessandro Melone at The Ohio State University and Michele Mazzoleni at Capital Group. About $20 trillion in pension funds and target date funds (TDFs) are subject to fixed-target rebalancing policies. While US equity and bond markets are relatively efficient, the sheer size of these funds means rebalancing pressures move prices, even if the price impact is temporary. Large trades should not be preannounced, but since most funds are transparent about their rebalancing policies, often their rebalancing trades are effectively public knowledge well in advance. This exposes them to front-running. Threshold and Calendar Rebalancing Here’s how it works. There are two main rebalancing methods: threshold and calendar. In the latter, funds rebalance on a specific date, usually at the end of a month or quarter, and in the former, they rebalance after the portfolio breaches a certain threshold. For example, a 60-40 portfolio with a 5% percent threshold would rebalance at 55-45 if stocks were falling and at 65-35 if they were rising. Whatever the method, rebalancing is predictable and anything predictable appeals to front-runners. They know that the rebalancing trade will involve a market-moving amount of money and that a buy order will increase prices. So, they anticipate the rebalancing and make an easy profit. My analysis with Melone and Mazzoleni conservatively estimates that rebalancing costs add up to 8 basis points (bps) per year, or about $16 billion. So, if a fund that is rebalancing needs to buy equities and the price is $100, frontrunners will drive it up to $100.08. Although 8 bps may strike some as nothing more than a rounding error, given how much total capital pensions and TDFs manage, that 8 bps may, in fact, exceed their annual trading costs. Moreover, our estimate may be understating the true impact. Indeed, our paper shows that when stocks are overweight in a portfolio, at 65-35, for example, funds will sell stocks and buy bonds, leading to a 17 bps decrease in returns over the next day. Here is another way to put it: The average pension fund or TDF investor loses $200 per year due to these rebalancing policies. That could be the equivalent of a month’s worth of contributions. Over a 24-year horizon, it could add up to two years’ worth. Our results also indicate that this effect has strengthened over time. This makes sense. Given the rapid growth of pensions and TDFs, their trading is more likely to affect prices. Pension Managers: “We Know about This.” When we discovered that rebalancing costs might exceed the total transactions costs of trading, we were naturally skeptical. As a reality check, in June 2024, we presented our results to a private roundtable of senior pension managers who collectively represent about $2 trillion in assets. To our astonishment, their reaction was, “We know about this.” We delved deeper. If you know about this, why not change your policies and reduce this cost? They told us that that they would need to go through their investment committees and the bureaucratic impediments were too steep. One CIO who acknowledged the procedural difficulty said it was easier to “Send the signal to our alpha desk.” I paused. “Does this mean you are frontrunning your own rebalancing and other pension funds’ rebalancing?” I asked. The answer was “Yes.” Our paper describes the magnitude of this problem. While we do not propose a specific solution, end-of-month and end-of-quarter rebalancing need to stop. Pensions should be less predictable in their rebalancing. Too much retirement money is being left on the table and then being skimmed off by front-runners. On May 13, Alessandro and I will be discussing our paper in a webinar hosted by CFA Society United Kingdom. Join us as we identify hidden costs in traditional rebalancing strategies, explore methods to minimize market impact while maintaining disciplined asset allocation, and discuss innovative approaches to protect institutional portfolios from front-running activities.  source

Investing in U.S. Financial History: Understanding the Past to Forecast the Future. 2024. Mark J. Higgins, CFA, CFP. Greenleaf Book Group Press. Chronicling the United States’ entire financial history from the 18th century onward is a highly ambitious but essential undertaking. The most recent such effort, prior to the book under review, was Jerry W. Markham’s multi-volume Financial History of the United States series. Other century-spanning histories appeared much earlier and consequently do not capitalize on the experience and scholarship of the last several decades. These include Paul Studenski and Herman Edward Krooss’s Financial History of the United States and Margaret Good Myers’s A Financial History of the United States. In taking on this formidable task, Mark J. Higgins, CFA, CFP, strives not only to tick off key events dating back to Alexander Hamilton’s time but to demonstrate that learning from them has helped decision makers address new crises as they have arisen. For instance, he maintains that fresh memories of the Panic of 1907 preconditioned government officials and Wall Street leaders to respond swiftly and aggressively to the first sign of panic that followed the 1914 outbreak of World War I. In that instance, the appropriate response turned out to be shutting down the New York Stock Exchange, a step specifically avoided by J. Pierpont Morgan seven years earlier. Clearly, historical precedents require some interpretation, but as Higgins writes, “By applying lessons from the Great Depression over the last ninety years, U.S. fiscal and monetary authorities have avoided a repetition of the catastrophe.”  The author sets the record straight on some popular misconceptions about financial history. For instance, he rightly says that the 29 October 1929 stock market crash did not trigger the Great Depression. According to the National Bureau of Economic Research, the economic contraction began in September 1929. The crash was a less important contributor to the severity and duration of the downturn than monetary and fiscal policy errors.  Even well-informed practitioners stand to gain new insights from Higgins’s painstaking research. For example, it will be news to many of them that today’s closed-end funds represent a revival of a product that, on average, suffered a staggering 98% loss of value between July 1929 and June 1932.  On a different topic, just a couple of years ago, a Barron’s headline read, “The Culprits of the 1987 Market Crash Remain a Mystery,” but Higgins lists six specific causes of the Dow Jones Industrial Average’s record 22.61% plunge on 19 October 1987. He also debunks the notion, propagated by the real estate profession prior to the 2008 bust, that property prices could not possibly fall on a nationwide basis because it had never happened before. Higgins cites precedents that accompanied economic depressions of the 1820s and 1840s.  The author’s heroic, 585-page work is all the more impressive by virtue of his background. Higgins is not an academic historian but, rather, an institutional investment consultant. His practitioner-oriented book includes a section on the origin of the securities analyst profession and a tribute to the CFA charter. This orientation makes Higgins’s treatment particularly useful to investors and money managers. He has applied to his day job the knowledge he amassed through his voracious reading of financial history during the course of writing the book. By his account, his clients have benefited in the form of lower fees and improved performance. The book’s title, Investing in U.S. Financial History, crystalizes Higgins’s notion that studying the past can be much more than a pleasurable intellectual exercise. Still, the book contains hints of an attraction to history for its own sake in such digressions as a more than 25-page discussion of the leadup to World War II, followed by more than 14 pages on the war itself. That is surely more detail on the strategies and battles than extracting the relevant financial lessons requires. Bond specialists will question Higgins’s assertion that because of their complexity, structured mortgage products of the early 2000s “were well beyond the competency of ratings analysts — or any human being whatsoever in many cases.” Famously, Goldman Sachs had no difficulty identifying, on behalf of a major client who wanted to sell short, mortgage pools that were exceptionally susceptible to defaults. Credit ratings of mortgage-backed securities (MBSs) that proved to be far too lenient were instead a function of a rating agency conflict of interest — that is, the issuer-pay model, which was more successfully controlled in the corporate asset class. In corporates, unlike the MBS market at the time, investors demanded that issues be rated by both leading agencies. That prevented issuers from dangling the prospect of fees to play one agency off against the other. Another difference was that no single corporate issuer represented a large enough percentage of the agencies’ revenues to tempt them to sacrifice their reputations by putting a thumb on the scale to help the issuer lower its borrowing cost. In MBSs, by contrast, a few investment banks dominated deal origination and disbursement of rating fees. Some readers may scratch their heads when they see a graph that accompanies Higgins’s discussion of Moore’s law. Intel cofounder Gordon Moore predicted in 1965 that the number of transistors per chip — and, therefore, the chip’s power — would double roughly every two years. Intended to illustrate the accuracy of his prediction, the graph shows the number of transistors per CPU declining in 1965, 1967, 1969, and 1970. In a future edition, the author could clear up possible confusion by expanding on his statement that the graph “uses data from Fairchild Semiconductor and Intel Corporation to show the average number of transistors on silicon chips produced from 1960 to 1971.” Older-model, less densely packed semiconductors do not cease to be produced as soon as engineers achieve a new high in transistors per chip. The mix of older and newer chips that the companies manufacture varies from year to year, so the average density per chip may fall in a given year, even though the density of

Despite the headlines proclaiming its demise, active investment management is not going extinct — it’s evolving. The traditional mutual fund may be fading, but active decision-making now shines through new channels: model portfolios, direct indexing, and self-service apps. Whether it’s a retail investor fine-tuning a separately managed account (SMA), an advisor allocating across ETFs, or an endowment selecting specialty managers to meet diverse investment policy requirements, the index is no longer the boundary between passive and active — it’s the starting point for active decision-making. Investment management is, after all, decision-making as a service. What’s changing is who (or what) is making which decisions, what tools are being used to make them, and how those decisions — and their results — are being delivered to end clients. While traditional active mutual funds have indeed seen significant outflows — $432 billion in the 12 months to 31 March 2025 — those dollars haven’t vanished from the market. According to Morningstar’s US Fund Flows research, they’ve largely rotated into passive vehicles, which took in $568 billion over the same period. On the surface, that shift supports the “passive takeover” narrative. But it actually reflects a reconfiguration of where and how active choices are being expressed. Beneath the surface, active decision-making is more widespread, more diversified, and more structurally embedded in the investment landscape than ever before. Beneath the Surface The packaging of active decision-making has evolved beyond the traditional mutual fund. Compelling trading apps combined with near-zero transaction costs have led to a boom in self-directed investing that, as Broadridge’s 2024 US Investor Pulse study points out, spans all generational cohorts. These self-directed investors increasingly focus on ETFs and direct equities rather than mutual funds. Meanwhile, as of June 2024, 79% of US equity investors maintained an investment relationship with a financial advisor. These advised assets are also shifting from mutual funds to ETFs and direct equities, facilitated by the proliferation of SMAs and unified managed accounts (UMAs). SMAs, in particular, offer individual investors unprecedented levels of access, transparency, and tax efficiency through strategies like tax-loss harvesting. In other countries, the trend is the same: self-service and personalization of investment solutions at scale. Source: Broadridge U.S. Investor Pulse Study – June 2024 Either way, someone — or something — is making active decisions. The self-directed investor wants hands-on control. They are active by definition, but are not willing to pay a third party for the decision-making. Implicitly, they either believe they can outperform professionals, they value the entertainment of market participation enough not to care, or both. The advice-channel investor, conversely, has outsourced decision-making to their financial advisor, trusting that a professional will deliver better outcomes. Financial advisors have never been more scalable as a business, partly because they can easily outsource the actual investment decisions to an expanding universe of model portfolios, ranging from strategic asset allocation models to tactical thematic strategies to risk-targeted solutions. These portfolios contain the same active decision-making found in mutual funds, just without the trade execution services. Institutional allocators continue to value alpha and will pay for it. As indexes have become increasingly concentrated, these sophisticated investors are turning back to active managers for diversification. But today’s allocators are less easily seduced by past performance; they demand evidence of skill. The industry is responding to these changes. Active equity portfolio managers, driven by cost-cutting imperatives, are reevaluating the division of labor within their investment teams. Product strategists are increasingly evaluating quant and fundamental strategies side-by-side, applying fresh eyes to the consolidation of multi-brand product ranges. In leading firms, formerly siloed investment teams are being integrated to foster collaboration and cross-pollination of ideas. This approach emphasizes decision-making quality, regardless of whether the signal originates from human insight or an algorithm. Key Takeaway Surface-level data suggests that active fund management is an industry in retreat: dollars flowing out of active funds and into passive alternatives. But under the surface, active decision-making is more widespread, more diversified, and more structurally embedded in the investment landscape than ever before. The imperative for active managers is no longer preservation, but adaptation. In a marketplace that demands personalization, transparency, and demonstrable value, relevance depends on embracing new delivery mechanisms and decision-making frameworks. The future of active investing will be shaped by those who evolve with it — quietly, strategically, and decisively. More to Think About from CFA Institute Research and Policy Center Smart Beta, Direct Indexing, and Index-Based Investment Strategies Beyond Active and Passive Investing: The Customization of Finance Future State of the Investment Industry source

Scope 3 disclosures are complex, and Category 15 (Investments) is an obscure segment intended to cover emissions that arise from one company having a stake in another (i.e., financial transactions). For most companies, this represents a proverbial footnote in their overall emissions profile. Indeed, given Category 15’s unique set of conceptual and data challenges, it is not a coincidence that it sits at the tail end of the Scope 3 catalogue. For financial institutions, however, financial transactions are the business, making Category 15 emissions a critical component of their overall emissions disclosures. Compared to other industries, financial institutions typically produce low Scope 1 and 2 emissions, which mostly come from offices and electricity use. Financial institutions produce limited emissions from most Scope 3 categories, and these emissions are linked mostly to their purchased goods and services and business travel. In contrast, their Category 15 emissions are exceptionally large. On average, more than 99% of a financial institution’s overall emissions footprint comes from Category 15 emissions. Financed and Facilitated Emissions Financial institutions’ Category 15 emissions include financed emissions and facilitated emissions. Financed emissions are on-balance-sheet emissions from direct lending and investment activities. These include the emissions from a company that a bank provides a loan to or in which an asset manager holds shares. Facilitated emissions are off-balance-sheet emissions from enabling capital market services and transactions. An example is the emissions from a company that an investment bank helps to issue debt or equity securities or for which it facilitates a loan through syndication. Financed and facilitated emissions are key to understanding the climate risk exposure of financial institutions. This could be substantial, for example, for a bank with a large lending book focused on airlines or an insurance firm specialized in oil and gas operations. So, it is not surprising that various stakeholders have been advocating for more disclosures. These include the Partnership for Carbon Accounting Financials (PCAF), the Principles for Responsible Investing (PRI), the Glasgow Financial Alliance for Net Zero (GFANZ), the Science Based Targets Initiative (SBTi), CDP, and the Transition Pathway Initiative (TPI). As Scope 3 disclosures are becoming mandatory in several jurisdictions, this takes on even greater urgency for the finance industry. The European Union’s Corporate Sustainability Reporting Directive, for example, requires all large companies listed on its regulated markets to report their Scope 3 emissions, and similar requirements are emerging in other jurisdictions around the world. While disclosure regulations usually don’t prescribe which Scope 3 emissions categories should be included in disclosures, they typically ask for material categories to be covered, making it difficult for financial institutions to argue against disclosing their financed and facilitated emissions. This poses a considerable challenge. Exhibit 1 shows that financial institutions’ Scope 3 reporting rates are among the highest across all industries. Only a third disclose their financed emissions, and they often only cover parts of their portfolios. To date, only a handful have attempted to disclose their facilitated emissions. A recent report from the TPI examining the climate disclosures of 26 global banks shows that none have fully disclosed their financed and facilitated emissions. Three Key Challenges Financial institutions need to overcome three key challenges in disclosing their financed and facilitated emissions to improve corporate reporting rates. First, in contrast to other Scope 3 categories, the rulebook for reporting on financed emissions and facilitated emissions is in many ways still nascent and incomplete. Accounting rules for financed emissions were only finalized by PCAF and endorsed by the Greenhouse Gas (GHG) Protocol — the global standard setter for GHG accounting — in 2020. These codify the accounting rules for banks, asset managers, asset owners and insurance firms. Rules for facilitated emissions followed in 2023, covering large investment banks and brokerage services. Those for reinsurance portfolios are currently pending the approval of the GHG Protocol, while rules for many other types of financial institution (not least exchanges and data providers like us) currently don’t exist. Exhibit 1. Source: LSEG, CDP. Companies reporting material and other Scope 3 vs non-reporting companies, in 2022 FTSE All-World Index, by Industry Second, there are significant challenges around acquiring client emissions data. In principle, financed and facilitated emissions calculations are quite simple. They require two main inputs: the Scope 1, 2, and 3 emissions generated from a client’s business and an attribution factor that determines the share of a client’s emissions that a reporting financial institution has exposure to or is responsible for. In practice, financial institutions often lack robust emissions data for large parts of their diverse client base. Such data is often available for large, listed companies, but rarely available for privately held companies or SMEs that commonly make up large shares of financial institutions’ client books. This can lead to huge data gaps in the emissions data inventory of financial institutions. Exhibit 2.  Features of PCAF’s Financed and Facilitated emissions standards5,6 Third, there are complexities around attribution factors. For financed emissions, this is the ratio of investments and/or outstanding loan balance to the client’s company value. However, market fluctuations of share prices complicate this picture and can result in swings in financed emissions that are not linked to the actual emissions profile of client companies. The same problem persists for facilitated emissions, but worse. Determining appropriate attribution factors is often conceptually difficult due to the myriad different ways that financial institutions facilitate financial transactions, from issuing securities to underwriting syndicated loans. As the Chief Sustainability Officer of HSBC recently explained, “This stuff sometimes is hours or days or weeks on our books. In the same way that the corporate lawyer is involved in that transaction, or one other big four accounting firms is involved…they are facilitating the transaction. This is not actually our financing.” Next Steps? Given these complexities and the significant reporting burden, financed and facilitated emissions are likely to remain a headache for reporting companies, investors, and regulators alike for some time to come. Meanwhile, proxy data and estimates are likely to play an important role in plugging disclosure gaps.

Hedge fund performance fees, I believe, are a rip-off for clients. Few phenomena illustrate this better than “round-tripping” stocks. These are stocks that, over the course of several years, for whatever reason, see enormous price gains only to fall back to about where they started. During the COVID-19 era, many companies have experienced such round-trip trajectories. That is not to say they were bad investments or their shares were overpriced: Stocks go up and down for reasons that are not always tied to fundamentals. But the degree to which hedge funds profit from these round trips at the expense of their investors is astounding. Consider the performance of the online used car retailer Carvana. Carvana generated 87% annualized returns between 1 January 2018 and year-end 2021 (1112% cumulative returns), boosting its market cap from $2.8 billion to $40 billion across that span. But 2022 has not been so kind. After peaking at $41 billion in 2021, Carvana’s market cap fell to $3.6 billion, with its shares down 91% for the calendar year as of 1 July. That means the stock returned a cumulative 9.7% since 1 January 2018 and has essentially “round tripped” . Carvana’s 4.5-Year Round Trip So, what would this mean for hedge funds and their limited partners (LPs)? Near Carvana’s Q2 2021 peak, using data from WhaleWisdom, we estimate that hedge funds owned about 21% of the company’s stock. These include such well-respected outfits as 683 Capital, Tiger Global, D1 Capital, Lone Pine, Whale Rock, Sands Capital, and many others with excellent long-term track records. Let’s assume that over the 4.5 years in question, hedge funds owned on average 20% of the outstanding shares of Carvana and charged a 20% annual performance fee over a 0% hurdle rate. How much would hedge funds have generated from clients by owning Carvana over the time frame? According to our calculations, they would have crystalized $1.2 billion in fees in the three years between 2018 and 2020. This is simply stunning. Between 1 January 2018 and 1 July 2022, Carvana’s market cap went from $2.8 billion to $3.6 billion. Yet hedge funds would have crystalized 150% of that market cap gain in fees. This constitutes a pure wealth transfer from the hands of allocators into those of hedge fund managers. 2018 2019 2020 2021 2022 Cum. Current Carvana SharePrice Return 71.1% 181.4% 160.2% –3.2% –91.0% 9.7% Carvana MarketCap, as of1 January (Billions) $2.8 $5.4 $12.0 $45.0 $40.1 $3.6 Percentage Owned byHedge Funds 20% 20% 20% 20% 20% Hedge FundPerformance Fee 20% 20% 20% 20% 20% Implied Hedge FundPerformance Fees(Millions) $79 $392 $771 $0 $0 $1,242 Note: 2022 returns through 1 July. Share price and market cap do not add up perfectly as Carvana issued equity most years. To be sure, this is only an estimate and may overstate the performance fees generated by this stock. For example, negative-returning stocks held by hedge funds mitigate the performance fees from positive-returning stocks like Carvana. Moreover, different hedge funds have various performance fee crystalization requirements, such as high-water marks, hurdles, etc. Nevertheless, ours is not an unreasonable approximation, and it actually understates the overall impact given the sheer number of stocks that have round-tripped. Oh Snap! Another Round-Tripper* Note: Snap performance as of 22 July 2022. Indeed, Carvana’s performance is hardly an outlier. Over the last several years, shares of Facebook, Roku, Sea Limited, Shopify, Snapchat, and Zoom, among many others, have experienced similar “round trips.” The takeaway is simply that the annualized performance fees paid to hedge funds lead to absurd outcomes that always come at the expense and to the detriment of LPs. Snap back to reality, ope there goes gravity pic.twitter.com/813RLGbgxs — Bucco Capital (@buccocapital) July 21, 2022 Why Wouldn’t Hedge Funds Do It This Way? Hedge fund managers are incentivized to act in their own self-interest and maximize their own wealth. They would be behaving rationally if they signed up for $1.2 billion in performance fees in exchange for delivering –5.6% in annualized net returns to clients. It’s a supremely attractive revenue stream for them, albeit an awfully poor one for their LPs. 2018 2019 2020 2021 2022 Cum. Ann. CarvanaShare Price Return 71.1% 181.4% 160.2% –3.2% –91.0% 9.7% 2.0% Carvana as aHedge Fund Net Return 56.9% 145.1% 128.2% –3.2% –91.0% –23.2% –5.6% S&P 500 TR –4.4% 31.5% 18.4% 28.7% –19.8% 53.6% 9.8% Carvana Hedge FundExcess Return 61.2% 113.6% 109.8% –31.9% –71.1% –76.8% –15.4% Note: 2022 returns through 1 July. Carvana hedge fund net returns assume a 20% performance fee over a 0% hurdle rate and that Carvana is the only hedge fund investment. While extreme, our example demonstrates how performance fees can create perverse incentives for hedge fund managers. Far from better aligning their interests, allocators that insist on paying for performance may be making a bad situation worse. With stocks like Carvana, hedge funds received a round-trip ticket over the last 4.5 years, with all expenses paid — by their LPs. 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/BogdanV 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

In Abidjan, Côte d’Ivoire this May, as delegates at the African Development Bank’s (AfDB) Annual Meetings debated economic futures, a new consensus emerged: Africa’s next growth wave will be capitalized not by aid, but by capital markets. New research from CFA Institute Research & Policy Center that was released at the meeting examines the case for mobilizing private capital to support the structural investment needs of sub-Saharan Africa. The research identifies and analyses existing barriers to the development of capital markets. It offers a series of recommendations for regulators, policymakers, the investment industry, and international institutions active in the region. The report’s country-level contributors, many of them CFA charterholders, bring deep local expertise to the report’s insights. “Their work, spanning 11 jurisdictions, helped ensure the recommendations reflect both regional diversity and shared structural needs,” according to Olivier Fines, CFA, Head of Advocacy for EMEA at CFA Institute. “Ultimately, the report aims to spark dialogue and coordination between those who shape policy and those who allocate capital,”  adds Fines, co-editor of the new research with Phoebe Chan, Capital Markets Policy Research Specialist, EMEA Advocacy, CFA Institute. Key Takeaways for Global Investors Africa is young, fast-growing, and under-capitalized: Development and integration of capital markets in the region is essential. Small- and medium-sized enterprises (SME) are the backbone of the economy, yet struggle to access efficient forms of capital: We think these challenges are solvable. Private market channels may provide the flexible capital structure required for the new economy, largely based on intellectual property and technology. Policy reforms and partnerships are already under way: Coordination between governments, regulators and the investment industry will be of the essence in order to build trust and predictability. Back capacity building,  not emergency solutions: Channel capital into skills, data, and infrastructure that power long-term development. Africa Isn’t Waiting—Investors Shouldn’t Either Africa is one of the fastest-growing regions in the world, and the optimism on the ground is real, Fines reports. “But investment strategies must be grounded in the region’s realities — its legal structures, data environments, and human capacity. That’s why our report focuses on actionable insights.” Fines was impressed with the level of optimism at the AfDB meeting. “It seemed to me like people were in general moving away from emergency discussions to the concept of capacity building. Can we move now to the next stage of this development? Can we focus on human capital development? Can we focus on research, on data aggregation to provide the market with the data that it needs to invest with confidence in what is likely to be one of the fastest growing regions in the world?” Why Private Capital, Why Now? Africa’s demographic and economic story is compelling. It’s the youngest, fastest-urbanizing region in the world, with rising consumer demand and entrepreneurial energy. However, traditional public market funding — and even donor-led models — have fallen short in meeting the region’s capital needs, Fines explains. “How do we fund, how do we help those entrepreneurs, is very much what we would like to solve through capital markets and provide innovative solutions through the concept of private markets, or private-public partnerships.” The report makes a focused case for private markets including private equity, venture capital, and private credit as critical engines of capital formation. “These markets offer flexibility, innovation, and faster deployment of funding, especially for SMEs that drive job creation and local economic growth,” Fines argues. But for these private channels to succeed, investors need predictable legal frameworks, transparent corporate governance, robust financial infrastructure, and skilled local talent, he adds. Barriers—or Opportunities in Disguise? In both the report and AfDB discussions, key barriers to capital market development were identified. “For global investors, these aren’t just red flags — they’re indicators of where smart policy action and collaborative investment can unlock long-term value,” Fines advises. These barriers include: Human capital gaps: Africa’s young population presents huge potential, but the region needs more financial professionals, market experts, and entrepreneurs trained in investment fundamentals. Data and information asymmetries: Investors face major obstacles in accessing reliable, comparable financial data across countries and sectors. Regulatory uncertainty: Inconsistent or opaque rules deter both local and foreign investment, especially in private assets. Weak public-private coordination: New policies often lack buy-in from the private sector, reducing effectiveness. Limited access to SME financing: Banks often underserve high-growth businesses due to risk constraints or lack of tailored financing tools. Key Policy Recommendations The report emphasizes that a thriving private capital market depends on a well-functioning ecosystem. It advocates for a cohesive package of reforms, including clearer and more consistent cross-border regulations to enhance investor confidence, stronger corporate governance to improve transparency and accountability, and broader access to education and training to build local financial expertise. It also highlights the need for more effective public-private collaboration to channel investment into strategic sectors and infrastructure, as well as greater efforts to educate retail and institutional investors to foster trust and encourage wider market participation. “By embracing these reforms, African countries can create an environment where private capital flows more freely, and where both economic development and investor confidence thrive,” according to Fines. AfDB Meeting: A Strategic Launch Point The African Development Bank’s Annual Meetings in Abidjan, where the report was launched, was an event that underscored growing momentum to mobilize private capital across the continent. As Fine notes, “The main theme of the African Development Bank this year was ‘Make Africa’s capital work better for Africa.’” That message closely aligned with the goals of the report, which was developed to inform regional policy direction and strengthen coordination between the public and private sectors. The timing was also significant. With a leadership transition at the AfDB and renewed interest in long-term development financing, the meeting provided a strategic platform to elevate market-based solutions. For global investors, the signal is clear: Africa’s moment is here. The only question is, will you be part of building it? To learn more, check out our AfDB Meetings Hub — complete with the full report, Capital Formation in Africa: A Case

This quarter’s top reads reveal what’s capturing the attention of investment professionals: overreliance on traditional valuation models, the performance of real assets during inflationary shocks, AI-driven strategy development, and heightened tensions in private markets. From debates on discounted cash flow (DCF) and hedge fund value to bank liquidity risks and career opportunities in wealth management, these standout blogs reflect some of the most pressing questions shaping today’s investment landscape. 1. The Discounted Cash Flow Dilemma: A Tool for Theorists or Practitioners? Is the discounted cash flow (DCF) model a relic of financial theory, or a practical tool for today’s investors? Sandeep Srinivas, CFA, explores the ongoing debate surrounding the DCF model, examining its relevance and application in modern investment analysis. His post delves into the strengths and limitations of DCF, providing insights for both theorists and practitioners. 2. Did Real Assets Provide an Inflation Hedge When Investors Needed it Most? In times of rising inflation, do real assets truly offer the protection investors seek? Marc Fandetti, CFA, investigates how real assets performed as an inflation hedge during the 2021–2023 COVID-era surge. He analyzes index-level data and finds that most real asset categories underperformed as hedges, with only commodities offering modest protection against inflationary pressures.​ 3. What Lies Beneath a Buyout: The Complex Mechanics of Private Equity Deals Private equity deals are often shrouded in mystery. What really happens behind the scenes? Paul Lavery, PhD, uncovers the intricate mechanics of private equity buyouts, shedding light on the financial structures and strategies employed. His post offers a detailed look at the roles of acquisition vehicles and the impact on portfolio company performance. 4. The Endowment Syndrome: Why Elite Funds Are Falling Behind Elite endowments have long been seen as the gold standard in investment. So why are they underperforming? Richard M. Ennis, CFA, delivers a sharp critique of elite endowment performance, arguing that heavy allocations to alternative investments have consistently eroded returns. Drawing on years of data, he reveals that the more institutions invest in alts, the worse they perform — challenging the very foundation of the endowment model. 5. Volatility Laundering: Public Pension Funds and the Impact of NAV Adjustments Are public pension funds masking their true performance through NAV adjustments? Richard M. Ennis, CFA, delves into the practice of volatility laundering, where public pension funds adjust net asset values (NAVs) to smooth returns. He explores the implications of this practice on fund transparency and investor trust. 6. Six Reasons to Avoid Hedge Funds Hedge funds promise high returns, but are they worth the risk? Raymond Kerzérho, CFA, outlines six compelling reasons why investors might want to steer clear of hedge funds. From high fees to lackluster performance, his post provides a critical analysis of the hedge fund industry and its impact on institutional investors. 7. Using ChatGPT to Generate NLP-Driven Investment Strategies Can artificial intelligence revolutionize investment strategies? ChatGPT might just be the key. Baptiste Lefort, Eric Benhamou, PhD, Jean-Jacques Ohana, CFA, Béatrice Guez, David Saltiel and Thomas Jacquot, CFA, highlight the potential of AI to analyze financial data and predict market trends, offering a glimpse into the future of investment management. They homed in on a popular LLM, ChatGPT, to analyze Bloomberg Market Wrap news using a two-step method to extract and analyze global market headlines.  8. Beyond Bank Runs: How Bank Liquidity Risks Shape Financial Stability Liquidity risk is more than just a buzzword. It’s a critical factor in financial stability. William W. Hahn, CFA, examines the role of liquidity risk in the banking sector, using recent high-profile failures as case studies. He emphasizes the importance of robust liquidity risk management in maintaining financial stability and preventing crises. 9. Bank Runs and Liquidity Crises: Insights from the Diamond-Dybvig Model The Diamond-Dybvig model offers timeless insights into bank runs and liquidity crises. William W. Hahn, CFA, revisits the classic Diamond-Dybvig model to provide a deeper understanding of bank runs and liquidity crises. He discusses the model’s relevance in today’s financial landscape and its implications for policymakers and investors. 10. 2025 Wealth Management Outlook: Spotlight on Investment Careers What does the future hold for investment careers in 2025? April J. Rudin offers a comprehensive outlook on the wealth management industry, focusing on emerging trends and career opportunities. She provides valuable insights for professionals looking to navigate the evolving landscape of investment careers. source