CFA Institute

How many attractive stock ideas does Naomi, an institutional active equity fund manager, have at any one time? “Oh, I think between 10 and 20,” she told me. So, why did her fund hold so many more times that number of stocks? “To round out the portfolio,” she said. I have asked these same questions of many active equity managers and received similar responses each time. The implication, of course, is that these managers are drowning the superior performance potential of their best ideas in a sea of bad ones. Why would they hobble their returns in this way? After all, no expert chef would serve up their signature dish with generic supermarket bread. So, why do skilled stock pickers make such errors when constructing portfolios and what can we do about it? Are Professional Managers Skilled Stock Pickers? The general consensus is no; they are not. On average, active equity funds fail to meet their benchmarks, which suggests that investors should avoid them in favor of low-cost index funds. But what if managers like Naomi stuck to their 10 to 20 preferred stocks? Would their portfolios do better? Studies confirm that they would. In the most compelling of these, “Best Ideas,” Miguel Anton, Randolph B. Cohen, and Christopher Polk find that the top 10 stocks held by active equity mutual funds, as measured by portfolio weights relative to index weights, significantly exceed their benchmarks. As the relative weights decline, however, performance fades and at some point, probably around the 20th stock, falls below the benchmark. So, professional managers are superior stock pickers — if they stick with their 10 to 20 best ideas. But most mutual fund portfolios hold many more bad idea than best idea stocks. Collective Stock-Picking Skill Applying a variation of the “Best Ideas” relative weight methodology, my firm, AthenaInvest, rates stocks by the fraction held by the best active equity funds. We define the best funds as those that pursue a narrowly defined strategy and take high-conviction positions and update our objective fund and stock ratings based on monthly data. The best and worst idea stocks are, respectively, those most and least held by the best US active equity funds. We derive each stock’s rating from the collective stock-picking skill of active equity funds with distinct strategies. The following chart presents the annual net returns of best and bad idea stocks from 2013 to 2022 as distilled from more than 400,000 stock month observations. The two best ideas category stocks eclipse their benchmarks by 200 and 59 basis points (bps), respectively, as measured by the average stock return net of the equally weighted S&P 500. The bad idea stocks, by contrast, underperform. (These results would have been even more dramatic had we excluded large-cap stocks since stock-picking skill decreases as market cap increases: The smallest market-cap quintile best idea returns far outpace those of the large-cap top quintile best ideas.) Best Idea and Bad Idea Stocks Annual Net Returns, 2013 to 2022 Performance declines as the best funds hold less and less of a stock. Those stocks held by fewer than five best idea funds — the rightmost category — return –646 bps. The designations reflect AthenaInvest’s roughly normal distribution rating system. The two best idea categories comprise 24% of the market value held by funds, while the bad ideas account for 76% and so outnumber good ones by more than 3 to 1. The market-value-weighted average annual return of all stocks held by funds is –53 bps before fees. Yet had the funds invested only in best ideas, they would have exceeded their benchmark. By diversifying beyond their best ideas, stock pickers sacrificed performance to build bad idea funds and became, in effect, closet indexers. Investing in Bad Ideas Again, why would they do this? Reducing portfolio volatility could be one motivation. But that only goes so far. On average, a 10-stock portfolio has a 20% standard deviation, less than half a one-stock portfolio’s 45% volatility. Adding stocks within this range makes sense. But beyond it, not so much: A 20-stock portfolio yields only an 18% standard deviation, and so on. After a certain point, adding bad ideas only drags down returns without contributing much in the way of diversification. But if diversification cannot explain investing in bad ideas, what can? Emotional triggers are a key driver. Despite the evidence, many see holding a 10 to 20 stock portfolio as “risky.” But if stocks sit in a portfolio’s long-term growth bucket, then short-term volatility is not a true risk. In fact, holding only best ideas may be less risky since they should lead to greater long horizon wealth. Small portfolio skittishness is therefore an emotional reaction motivated by a desire to reduce risk rather than create wealth. Tracking error is another emotional trigger. With its small, unique set of stocks, a best idea portfolio will have periods of both under- and overperformance. Since investors often suffer from myopic loss aversion, they are prone to overreacting to short-term losses. To alleviate their sense of disappointment, they may sell low and buy high, trading an underperforming fund for an overperforming one. To minimize this business risk, funds may overdiversify to ensure their performance tracks their benchmark even at the expense of long-term returns. Since funds charge fees based on their assets under management (AUM) rather than performance, they are incentivized to grow ever larger and become closet indexers. In “Mutual Fund Flows and Performance in Rational Markets,” Jonathan B. Berk and Richard C. Green describe the economic rationale for such return-sabotaging behavior. Investment consultants and platform gatekeepers further reinforce these trends. They both apply standard deviation, tracking error, and the Sharpe ratio, among other tools of modern portfolio theory (MPT), to determine whether to include certain funds in a portfolio. Based on short-term volatility, each of these measures may encourage myopic loss aversion in investors. Instead of mitigating such performance-destroying behavior, they exacerbate it. This is especially true for the Sharpe ratio, which double discounts

A History of Financial Technology and Regulation: From American Incorporation to Cryptocurrency and Crowdfunding. 2022. Seth C. Oranburg. Cambridge University Press. In A History of Financial Technology and Regulation: From American Incorporation to Cryptocurrency and Crowdfunding, Seth C. Oranburg highlights recent changes to the world of finance by exploring the role of technology within it, including complex phenomena such as mutual funds, cryptocurrencies, and the stock market. The chapters begin with historical analogy and basic principles before describing complex digital-investment strategies and instruments. Readers will gain an understanding of key concepts in financial regulation, including how law and regulations prevented some financial crises while facilitating others. The author concludes with ideas about where finance is trending and how the law should respond. The book should appeal to both specialists and generalists who are interested in learning more about regulation, finance and economics, business, and law. Oranburg, a legal scholar and professor at the University of New Hampshire Franklin Pierce School of Law, provides a broad overview of policy initiatives and financial markets to address the problems inherent in markets as a result of regulation. In all of the book’s chapters, the author develops his view of how financial markets have developed and how investors and regulators have shaped these developments. A constant theme throughout the book is the division of US corporate finance history into three distinct eras. The First Era began with the ratification of the Constitution in the 1790s and ended with the Great Depression in the 1930s. The Second Era began with the Securities Act of 1933 and ended with the Great Recession of 2007–2009. Finally, the Third Era began with the emergence of bitcoin in 2008 and continues to this day. The author’s fundamental perspective is that throughout history, technical developments furthering financial opportunities have been channeled by “major players” — that is, wealthy investors and regulators — to benefit the few over the many. He describes recent developments such as the push toward investments in cryptocurrency as the consequence of smaller investors desperately searching for higher returns. This idea, however, ignores the wide range of investments already available to the public and does not elaborate on investors’ excessive risk taking in financial markets. The book describes the limited regulation of “bucket shops” in the latter half of the nineteenth century, where smaller investors driven by the innovation of ticker news gambled in the stock market. A bucket shop is a physical location, typically in an office building, designed to look like a high-end brokerage firm. These institutions, often run by fraudulent owners, put pressure on brokers’ fees and participation restrictions, contributing to a vast increase in stock ownership in the 1920s. This widening participation in stock speculation helped fuel the financial excesses of the 1920s. With the crash and harsh economic downturn that followed in the 1930s, regulation turned toward limiting the sources of such excesses and instability. The New Deal era regulations are presented as initiatives to disenfranchise investors, particularly small investors. This dynamic then set the stage for recent decades, in which markets are dominated by privileged investors, such as angels and startups. In summary, the author urges us to not always seek to create a new federal agency in response to whatever the next crisis will be but rather to think about alternatives that can protect investors without driving them away. In our current Third Era, where smaller investors can easily choose to invest in unregulatable assets, too much regulation can be dangerous — just as too little regulation can be. We should think creatively about alternative ways to design optimal regulations so that the future of financial technology leads to a safer economy with more balanced financial opportunities for all. 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. 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

This article is adapted from a version originally published in the fall issue of The Journal of Performance Measurement®. Overview Investment management is a three-part process: Set goals for risk and return Select investments Evaluate the results Often carried out in isolation by different, unconnected groups, these activities can lead to disappointment when expectations are not met. The portfolio construction process is the most common source of disappointment. Why? Because the set of funds selected to implement the asset allocation ends up altering the asset allocation. This leaves the client with a set of market exposures that differ from what they expected. This is a problem that receives little attention. Here we outline a process for identifying and evaluating this benchmark misfit risk using a portfolio of funds in a diversified global asset allocation. Asset Allocation: The First Step Our case study begins with a globally-diversified strategy that includes publicly traded investments: stocks, bonds, and alternatives as demonstrated in the following chart. Asset Allocation Portfolio Construction: Turning the Plan into a Portfolio An asset allocation becomes an investment portfolio when specific funds are selected. Each fund is expected to act like its benchmark with a comparable return pattern and level of risk. Hopefully, it earns a higher return after adjusting for both risk and fees. We evaluate active risk, or tracking error, by measuring how closely each fund’s return pattern aligns with its benchmark based on the correlation of the fund and that benchmark. But the square of the correlation is the more useful statistic. It answers the critical question: What percent of each fund’s return is driven by factors in its benchmark? Many investors assume that investment selection is the sole driver of tracking error. This is a mistake. Unfortunately, much of the portfolio’s tracking error is often determined by a different set of market exposures, with the source of this misfit risk produced within its funds. We must separate the effect of these structural differences. Only then can we calculate the true investment selection effect. Introducing the Portfolio’s Funds Our asset allocation includes 14 segments. These are organized by asset class (global equity, global bonds and alternatives); asset segment (US equity vs. non-US equity); and style (value vs. growth). We used net-of-fee returns for the funds in this analysis. Portfolio’s Funds: Performance over Five Years Note: Equity style is noted V vs. G, as in LCG = Large-Cap Growth; EAFEG = Non-US Growth. Determining Each Fund’s Effective Exposures Our first step was to derive the effective exposures for each of the portfolio’s funds. We conducted a regression analysis to determine the weightings of each of the portfolio’s segments so that the return of this effective fund index had the highest correlation to each fund. We then constructed a table of our results, expressing each fund in terms of its effective market segment weights. We applied these weights to the allocation for each fund; the result shows each fund’s contribution to the segment weightings for the overall portfolio. By summing these contributions across all funds, we determine the portfolio’s effective exposure to each market segment. Effective Exposures for Funds and for the Total Portfolio These results show how each fund behaves rather than what it looks like or calls itself. By subtracting the total portfolio exposures from the asset allocation target weights, we determine the effective active exposures for the portfolio. These produce a long-term allocation effect found in the portfolio’s performance-attribution analysis. These active weights are a key driver of the portfolio’s tracking error. Active Weights Traditional Review of Performance The portfolio outperformed its benchmark on an absolute and a risk-adjusted basis, with low tracking error relative to its excess return. Its information ratio of 1.7 is high enough to provide statistical confidence in this set of funds, and was more than three times that of its funds. Performance Results: A Very Good Story Relative Performance with Misfit BenchmarkDrivers of Portfolio Performance Without the insights from the portfolio’s effective exposures, we would believe that the funds’ investment selection process added substantial excess return with only a small increase in risk.  Performance with Effective Exposures (Misfit Benchmark) Cash Portfolio PolicyBenchmark EffectiveExposures Return 1.19 11.87 9.74 9.66 Risk 0.27 11.31 11.11 9.89 The inclusion of benchmark misfit on performance changes everything! Instead of issue selection driving a slight increase in risk with a tremendous increase in return, misfit lowered volatility with selection adding substantially to risk but only modestly to return. This changes the narrative completely. Attribution of Total Return and Total Risk Benchmark Misfit Selection Total Contribution to TotalReturn 9.74 -0.07 2.21 11.87 Contribution to TotalVolatility 11.05 -1.19 1.46 11.31 Correlation to PortfolioTotal Return 0.994 -0.86 0.87 Incorporating Misfit Risk into Active Return Attribution Analysis We apply the same principles to the portfolio’s excess returns, starting with the excess return and tracking error for each component. Active Results Misfit ExcessReturn SelectionExcess Return Total ExcessReturn Return -0.07 2.21 2.14 Volatility 1.38 1.69 1.24 Attribution of Active Return Misfit Selection Total Contribution to Excess Return -0.07 2.21 2.14 Contribution to PortfolioTracking Error 0.25 1.00 1.24 Correlation to PortfolioExcess Return 0.18 0.59 According to our data, misfit contributes only 25 bps (18%) of its own tracking error to the portfolio, while selection contributes 100 bps (almost 60%) of its own tracking error. These results were driven by their respective correlations to the portfolio’s excess return. A critical point: From the perspective of the total portfolio manager, misfit risk is an unmanaged aspect of the portfolio. It is reassuring to know that this does not dominate the portfolio’s active performance results. A Quick Look at the Funds We separated each fund’s active contributions to the portfolio’s total misfit risk and selection results. This is shown on a percent of total basis, where efficiency is measured in terms of equal contributions to risk and return. This clearly demonstrates that the deliberate investment selection process was more efficient than the unintended consequence of the benchmark misfit effect. Misfit and Selection Contributions by Fund Conclusions Contrary

Private credit has rapidly evolved from a niche asset class into a dominant force in the global lending ecosystem, now representing an estimated $2.5 trillion industry[1] rivaling traditional bank lending and public debt markets. For institutional investors navigating a shifting macroeconomic and regulatory landscape, the asset class presents both compelling opportunities and growing concerns. While private credit promises bespoke deal structures, superior yields, and diversification away from traditional fixed income, its accelerated growth — fueled by bank retrenchment and heightened investor appetite — raises critical questions about liquidity, transparency, and systemic risk. This transformation has been driven by structural shifts in the financial system. Chief among them: tighter post-2008 banking regulations, the persistent search for yield in low-interest-rate environments, and the growing demand from private equity for more flexible, non-traditional sources of financing. Drivers of Private Credit Growth Several key factors have contributed to the rise of private credit: Banking Regulation & Retrenchment: Post-2008 financial reforms, such as Basel III and Dodd-Frank, imposed stricter capital requirements on banks, limiting their ability to lend to middle-market firms[2]. Private credit funds stepped in to fill this gap. Investor Demand for Yield: In a low-interest-rate environment, institutional investors, including pension funds and insurers, sought higher returns through private credit investments.[3] Private Equity Expansion: The growth of private equity has fueled demand for direct lending, as firms prefer tailored financing solutions over traditional syndicated loans.[4] Flexibility & Speed: Private credit offers customized loan structures, faster execution, and less regulatory oversight, making it attractive to borrowers.[5] Implications for Financial Stability and Systemic Risk Despite its benefits, private credit introduces new vulnerabilities to the financial system: Liquidity Risks: Unlike banks, private credit funds lack access to central bank liquidity. Even though many funds restrict investor withdrawals to quarterly or annual redemption windows, during economic downturns when borrower defaults rise and secondary market liquidity dries up, investor redemption demands could trigger fire sales and market instability. Leverage & Concentration: Many private credit funds operate with high leverage, amplifying returns but also increasing fragility. Business Development Companies (BDCs), for example, were allowed to increase their leverage cap to 2:1 in 2018[6], raising concerns about systemic risk. Opaque Valuations: Private credit assets are not publicly traded, making valuations less transparent and potentially stale, which could mask underlying risks.[7] Interlinkages with Banks: While private credit operates outside traditional banking, its growing ties to bank funding could create contagion risks in a downturn.[8] Regulatory Outlook Regulators, including the Federal Reserve, the International Monetary Fund (IMF), and the Bank for International Settlements (BIS), are increasingly scrutinizing private credit’s role in financial markets. The IMF warns that private credit’s expansion could amplify economic shocks, particularly if underwriting standards deteriorate. The BIS highlights the need for greater transparency and risk monitoring, especially as retail investors gain exposure to the asset class. More to Think About For allocators and asset owners, private credit represents a strategic lever in pursuit of yield and portfolio diversification. But as capital continues to pour into the space, often outpacing risk infrastructure, the investment thesis must be continually reexamined through a risk-adjusted lens. With increasing scrutiny from global regulators and the growing complexity of credit markets, due diligence and scenario planning will be essential to avoid hidden vulnerabilities and ensure resilience in the next phase of the credit cycle. At the same time, policymakers are increasingly alert to the broader financial implications of private credit’s ascent. Global regulators including the Federal Reserve, IMF, and BIS have warned that unchecked growth in opaque, illiquid segments of credit markets could amplify shocks and create feedback loops across institutions. Notably, the growing accessibility of private credit products to retail investors, often via interval funds and public BDCs, raises further concerns about liquidity mismatches and valuation transparency. These dynamics are likely to draw heightened regulatory attention as retail participation expands. Striking the right balance between market innovation and systemic oversight will be crucial not just for regulators but for institutional investors who must navigate these crosscurrents with discipline and foresight. [1] Bank for International Settlements (BIS) Private Credit Market Overview, 2025. [2] Federal Reserve Report on Private Credit Characteristics and Risks, 2024. [3] IMF Global Financial Stability Report, April 2024. [4] IMF Blog on Private Credit Growth, 2024. [5] What is private credit, Brookings, 2024. [6] H.R.4267 – Small Business Credit Availability Act, 2018 [7] Federal Reserve Report on Private Credit Characteristics and Risks, 2024. [8] Bank Lending to Private Equity and Private Credit Funds: Insights from Regulatory Data, Fed Boston 2025 source

Even as the inclusion of sustainability targets in investment portfolios grows in popularity, the challenge of balancing this approach continues to perplex investors. But a Financial Analysts Journal study, “Bonds with Benefits: Impact Investing in Corporate Debt,” may offer encouragement. It finds that sustainability-oriented investors can meet their goals with corporate debt strategies and that profit-oriented factor investors can achieve a portfolio with a certain sustainability level at a low cost. I spoke with Desislava Vladimirova, who coauthored the study with Jieyan Fang-Klingler, for insights on the authors’ findings and to produce an In Practice summary of the study, which can be found on our CFA Institute Research and Policy Center. Below is a lightly edited and condensed transcript of our conversation, as well as a brief author video. The study analyzes some of the implications of sustainable investment in actively managed credit portfolios using carbon emissions, Sustainable Development Goals (SDGs), and green bonds and reveals a concave relationship between outperformance and sustainability. A nonlinear relationship between sustainability and factor investing is the salient finding, according to Vladimirova. CFA Institute Research and Policy Center: What does your research study have to tell bond investors? Desislava Vladimirova: What we are trying to say is that there are two types of investors—those who focus on returns and those whose investment beliefs include considering the environment and thus they also target sustainable companies. Because a focus on sustainable companies would limit the investable universe, investors intuitively expect returns to be reduced. We are trying to show with our research that this is not necessarily the case, and that depending on investors’ preferences regarding the level of sustainability they are seeking, there might be optimal combinations that would allow them to stay profitable and still have sustainability. Who should be interested in your research findings and why? Our findings are interesting to institutional investors with a focus on corporate debt. The study aims to draw the attention of credit investors who need to fulfill regulatory requirements in terms of sustainability as well as investors with a strong sustainability focus. Our research provides useful insights for all investors willing to integrate sustainable investing because we find that there is an optimal solution for investors with different green preferences. What motivated you to conduct this research and author this paper? Two reasons: one was the academic aspect—this was a niche that had not been filled in the literature. The second is we work for an asset management company, and we’re interested in whether this is feasible and achievable with profitable strategies—to see how plausible it is to achieve these two goals together. What is novel about your study? There has been no research on how to integrate sustainability into active credit strategies. We analyze measures that haven’t been discussed previously, such as Sustainable Development Goals (SDGs). We confirm our findings for three different sustainable measures — carbon footprint, SDGs, and green bonds — and we are consistent with our results. We show that these three measures can be integrated into active factor strategies. The factors are quantifiable, and the sustainable measures are quantifiable. What do you deem your study’s most important findings or key takeaways? Our study analyses the relationship between sustainability and factor investment. The most important finding is that this relationship is not a zero-sum game. We find that constructing optimized dual-target portfolios reveals a concave relationship between factor investment and sustainability, meaning that investors’ target trade-offs are not zero-sum in nature. This implies that factor investors willing to comply with minimum sustainability standards can do so with minor impact on performance. And investors with a strong sustainability focus can benefit from exposure to profit-oriented strategies, while still being predominantly invested in sustainable assets. What are the key practical applications of your research? We believe that our study can be applied to the portfolio construction process of factor strategies. We provide a dual objective optimization methodology that can consider various investors’ sustainability preferences and combine them with credit signals under plausible risk and turnover constraints. Our results exhibit robustness for different sustainability measures and factor definitions. And, as such, investors only need to decide on their optimal factor sustainability mix. We show that for a practitioner who wants to be profitable and wants to reduce carbon emissions, this is very easily achievable. But we also show that investors who want to participate in environmental projects and invest in green bonds can be profitable. We basically show that there is an optimal solution for everybody. If you liked this post, don’t forget to subscribe to Enterprising Investor and the CFA Institute Research and Policy Center. 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 / Olemedia 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

It’s often claimed that small-cap stocks are more interest-rate sensitive than their large-cap counterparts because of their reliance on outside financing. This seems plausible. But what do the data say? In this blog post, I explore the relationship between small- and large-cap stocks and interest-rate changes using the Stocks, Bonds, Bills and Inflation® (SBBI®) monthly dataset — which is available to CFA Institute members — and the Robert Shiller long-bond rate dataset. I use graphs and correlations (and a little regression). My main findings are: Small-stock monthly returns are no more sensitive to rate changes than large-stock returns. Small stocks fare no worse on average than large stocks during periods of Federal Reserve (Fed) interest-rate tightenings, where tightening periods are as defined by Alan Blinder in a recent paper. The relationship between stocks and rates isn’t stable. There are periods when equities are highly rate sensitive, and periods when they aren’t. The Federal Reserve Bank of Chicago’s (Chicago Fed’s) National Financial Conditions Index (NFCI) — a proxy for ease of overall access to capital — has about the same relationship with small-stock returns as with large.   R Code for calculations performed and charts rendered can be found in the online supplement to this post. Stocks and Rates: The Big Picture I start with the full period for the SBBI® dataset: January 1926 to April 2024. The left panel in Chart 1 shows the correlation between small-stock monthly returns and the long-government bond interest rate (hereafter, the “long rate” or just “rate”) from the inception of the SBBI® dataset in 1926 to April 2024, which is the last available month of SBBI® returns. The right panel in Chart 1 shows the correlation between large-stock monthly returns and the long rate during the same period. The correlation between large stocks and rate changes is modestly negative (-0.1) and significant at the 95% level. The correlation between small stocks and rate changes is not significant. These results are robust to lagging the rate change variable by one period and to restricting rate changes to positive values. That is, accounting for possible delayed effects and limiting rate changes to the potentially adverse doesn’t change the results. Chart 1. Monthly small- (left) and large-stock (right) returns versus long-rate changes, 1926 to April 2024. These correlations are suggestive, but obviously not conclusive. The long timeframe — nearly a century — could mask important shorter-term relationships. Table 1 therefore shows the same statistic but grouped, somewhat arbitrarily, by decade. Table 1. Large- and small-cap stock monthly return correlations with all long rate changes. When viewed this way, the data suggest that there could be meaningfully long periods when correlations differ from zero. I omit confidence intervals here, but they don’t include zero when correlations are relatively large in an absolute sense. Correlations are usually of the expected sign (negative). There doesn’t seem to be much difference in the way that small and large stocks respond to long-rate changes, with the possible exception of the last few years (the 2020s). These findings are robust to lagging the rate-change variable by one period. Restricting rate changes to positive observations changes both the sign of correlations and (significantly) their magnitude in some periods, as shown in Table 2. Nothing about Table 2’s results, however, suggests a difference in the reaction of small and large stocks to a rise in rates. Table 2. Large- and small-cap stock monthly return correlations with positive long-rate changes. But, as noted, decades are arbitrary periods. Chart 2 therefore shows the rolling 60-month correlation between the small-, large-, and long-rate change series for the length of the SBBI® dataset. Chart 2. Rolling 60-month correlations between small (left) and large (right) stocks and long-rate changes. Two features are noteworthy. One, the charts are nearly indistinguishable visually, vertical-axis values aside. Small and large stocks appear to exhibit similar behavior in response to rate changes. It’s hard to avoid the inference that small-cap stocks don’t respond differently to long-rate changes than large-cap stocks. And two, the stock-rate relationship varies, and can have the “wrong” sign for long periods. Removing Market Effects Could the observed similar response of large and small stocks to long-rate changes be due to the influence of “the market” (large-stock returns) on small stocks? It seems plausible that broad market effects could mask an adverse reaction of small stocks to rising borrowing costs. Removing them might give us a better sense of the effect of long-rate changes on small-stock returns. I do this by first regressing small-stock monthly returns on large-stock monthly returns (a proxy for “the market”). I then calculate partial correlation using the residuals from this regression, which reflect the non-market part of small-stock returns and long-rate changes.[1] Overall (1926 – April 2024), the partial correlation is again not different from zero. However, as shown in Chart 3, the rolling, 60-month partial correlation has been mostly (though not always) positive — the opposite of the expected sign — and sometimes large, particularly lately. Controlling for “market beta” therefore does seem to impact the relationship between small stocks and long rates. These results probably aren’t practically meaningful or useful, however. Chart 3. Rolling 60-month partial correlations between small stocks and rate changes. Monetary Policy and Returns Small-cap stocks could be more sensitive to shorter-term rates to which their borrowing costs are more closely linked. Table 3 therefore shows the average annualized performance (in decimals, so, e.g., 0.03 = 3%) of small and large stocks during the 12 Fed tightening episodes identified by Alan Blinder (listed in column 1) in his paper on “soft landings.” Table 3. Large- and small-stock performance during Blinder’s monetary tightenings. Before the early 1980s, a researcher might have concluded that small stocks performed better than large stocks when the Fed was hiking. The fourth column (“diff”), which shows the difference between small and large stock returns, was positive in all tightenings up to that time. Since then, small stocks have underperformed during tightenings more often than they’ve outperformed. But

What could a US sovereign wealth fund mean for markets and investors? It could alter the balance between state and private capital by de-risking strategic projects, legitimizing new asset classes, and attracting global co-investment into critical industries. Since President Donald Trump announced the establishment a US sovereign wealth fund (SWF) in February, it has fueled both expectations and controversies. Investors should pay attention because state-backed capital is no longer theoretical. It is being deployed in semiconductors, digital assets, and even major technology platforms. This week’s news that the US government is considering taking a 10% stake in Intel underscores how quickly the idea is moving from concept to concrete deals, raising urgent questions about how far state capital will reach into the private sector, and what that means for investors. Many experts are calling for a formal, legislatively grounded US sovereign wealth fund like Norway’s Norges Bank Investment Management (NBIM). But instead, the Administration has taken an ad-hoc path, using executive power to direct capital into strategic sectors. Can a country that runs persistent deficits really build one of the world’s biggest sovereign wealth funds? President Trump’s unconventional approach suggests yes. If successful, it could redefine the SWF model. How the US Is Redefining the Sovereign Wealth Fund To see why this approach is so unconventional, it helps to compare it with traditional sovereign wealth funds. A sovereign wealth fund is a state-owned investment fund that manages a country’s financial assets, typically derived from surplus reserves, natural resource revenues, or trade surpluses. These funds are generally managed by a country’s ministry of finance, a central bank, or a specialized government agency. But under President Trump’s executive order, America is carving an alternative SWF path, one that is distinctly bottom-up and industrial strategy-driven. Far from displacing private capital, it is increasingly proving to be a powerful “crowd in” catalyst for public-private investment partnerships. De-risking Projects and Crowding In Capital Nowhere is this more evident than in the Department of Defense’s (DoD) $400 million equity investment in MP Materials , the only rare earth producer in the United States. Under the Defense Production Act, the Pentagon is becoming MP Materials’ largest shareholder, with a potential 15% stake and long-term offtake agreements to buy 100% of the magnets made at the company’s new facility. This investment enables the United States to secure critical mineral flows, countering China’s dominance in this space. The DoD’s commitment has attracted $1 billion in private financing from JPMorgan Chase and Goldman Sachs to build MP’s new “10X” magnet manufacturing facility in Texas. Wall Street followed because the US investment de-risked the project with guaranteed procurement and revenue certainty. The same playbook is now being tested in the digital asset space. In March, the Administration announced the creation of a US strategic bitcoin (BTC) reserve, which was seeded with over $5 billion BTC seized in law enforcement actions and will be supplemented by budget-neutral acquisition strategies. Another case at the intersection of politics, technology, and capital markets is TikTok. Executive orders have granted TikTok a reprieve from a sell-or-ban order, and the administration has signaled interest in taking a stake through golden shares, granting veto power over key corporate decisions. Global Parallels and Key Differences Although these US moves may look novel, similar strategies have been used in other advanced economies, including Germany’s use of its sovereign fund KfW. For instance, the 50Hertz transaction in 2018 saw KfW orchestrated an investment to prevent State Grid Corporation of China from acquiring a stake in a critical utility infrastructure. Furthermore, it is the general practice of global sovereign wealth funds to seek both strategic industrial promotion and financial returns in their investments. The sovereign capital could avoid crowding out and unlock private capital when serving as a co-investment platform. What sets the United States approach apart is that the proposed sovereign wealth fund is a decentralized, transaction-driven model. With multiple agencies leading strategic investments, this federated approach departs from traditional SWF orthodoxy. Another distinguishing feature of the US approach is its reliance on foreign capital tied to tariff agreements. Foreign Capital and Tariff Revenue The bigger components of the US sovereign wealth fund are now coming from foreign capital as part of the tariff agreements with global nations. This week, the Administration announced a US-Japan Strategic Trade and Investment Agreement, and Japan has pledged to invest $550 billion to rebuild and expand core American industries, including semiconductor manufacturing, research, and pharmaceutical production. It could mark the beginning of co-investment partnerships with global sovereign fund peers. The United States has asked South Korea to help create a manufacturing cooperation enhancement fund to finance Korean firms expanding production in the United States. Finally, as part of the US-EU trade deal reached days ago, EU companies have expressed interest in investing at least $600 billion in various sectors in the United States by 2029, according to the European Commission’s explanation. The Road Ahead: Strategic Sectors and Risk Looking ahead, the central question is how this decentralized model will shape strategic sectors and market risk. It is emerging as a platform for co-investment in politically sensitive areas, guided by governance protocols. For investors, the test is whether it reduces risk and creates opportunity, or whether political involvement complicates capital allocation. Stargate, the $500 billion AI data infrastructure initiative led by OpenAI and SoftBank, could find the US sovereign wealth fund a crucial partner. The White House’s “Winning the AI Race” plan calls for fast-tracking permits for large-scale data centers and energy supply. Yet six months after its launch, Stargate is struggling to gain traction and may be scaled back, despite a $30 billion-a-year, 4.5 GW partnership with Oracle. Long-term US SWF support could reduce risk and attract private capital. Some AI chip-related funding is already being directed to the US sovereign wealth fund, and Washington may continue to draw on new revenue streams. In August, President Trump negotiated an agreement allowing Nvidia and AMD to resume certain semiconductor sales to China in exchange for

Looking for a way to “beat the market” in 2024 and beyond?  If so, you’ve probably heard about the market-beating potential of private equity investments. The most recent U.S. Private Equity Index from Cambridge Associates reports an average return of about 15% from June 2003 to June 2023, compared to 10% on the Russell 3000 Index. However, before diving into private equity investing, everyday investors should be aware of a few important considerations.  For almost 100 years, the world of private equity was largely “off limits” to Main Street investors. Legally speaking, only accredited investors were allowed to invest in private equity offerings. But thanks to the Jumpstart Our Business Startups (JOBS) Act — and an influx of new publicly listed private equity offerings — everyday investors are seeing a Cambrian explosion in access to private equity opportunities. How Private Equity Investing Has Changed in Recent Years It is worth noting that private investments such as private equity, hedge funds, and venture capital funds typically require individual investors to be accredited: they must have an income of more than $200,000 for an individual and $300,000 if married and filing jointly for two years prior to investing, or a net worth of $1 million, excluding a primary residence. In the early ’80s, only 1%-2% of households were considered accredited. However, because the financial thresholds to become an accredited investor have not been indexed to inflation, more than 13% of all American households now qualify. Despite this growing number of eligible households, private equity still operates like a private club. To get access to opportunities, you probably need to be a client of a name-brand financial institution. That’s not to mention the administrative challenges like 200-page subscription documents, underwriting, and complicated terms most people don’t understand. With that said, the biggest innovation in private equity has been the JOBS Act of 2012. Thanks to this landmark piece of legislation, two important things happened.  The first was lifting the ban on “general solicitation” and advertising for specific types of private market deals. Before this ban was lifted, the only way to get into a private deal was to “know a guy,” as it was otherwise illegal for them to advertise the opportunity. However, those offerings — called Rule 506(c) of Regulation D — were still restricted to accredited investors only.  Then, in 2016 Title III of the JOBS Act went into effect, introducing a new framework that allowed both accredited and nonaccredited investors to invest in private market deals. More commonly known as Regulation Crowdfunding, this framework created a new pathway for companies seeking investments to raise capital from anyone over the age of 18, regardless of income or net worth. There’s no doubt the JOBS Act transformed investment banking and capital markets as we know it. but the looser regulatory and disclosure requirements carry risks and may open the door for increased fraud. The Biggest Risks of Private Equity Investing One of the most common questions asked by people considering private equity is some version of, “How much can I make?” and “How fast can I make it?” While there is a potential to make significant returns in a short period, there is also plenty of risk that comes with it.  Outright fraud is always a concern when it comes to early-stage investing. But outside of that, the key risks are the same fundamental risks that are present in any investment:  Valuation Risk: Are you investing at a good price? If the goal is to make money as an investor, you don’t want to hurt your chances by overpaying. Execution Risk: Can the management team execute on the business plan they’ve presented? If not, the returns likely won’t be what you expect. Market Risk: Could forces outside of the management team’s control damage the company? It happens all the time, and that’s just part of the risks you’re signing up for as an investor. However, most retail investors cannot accurately evaluate these risks and, therefore, have difficulty understanding the exact risks they are taking at the price and terms being offered.  What Are the Tax Implications? Unless you’re investing into a fund structure — or otherwise receiving income reporting on a K-1 or 1099 — there really are no tax implications outside of normal due course. If you’re investing in private credit or cash-flowing real estate deals, taxes will be a consideration. Otherwise, for most private equity plays, it’s a three- to five-year hold, at least.  The only time you would incur tax liability would be on the asset’s sale (or disposal). This means you would be taxed at the long-term capital gains rate, just like any other investment you’ve held for more than 12 months. 5 Strategies for Investing in Private Equity as an Everyday Investor With all the nuances, it can be difficult to navigate private equity investing. Here are five steps for everyday investors to incorporate private equity investments into their portfolios while balancing risk with potential returns: 1. Develop a comprehensive financial plan. Before making any investment decisions, it’s crucial to have a well-defined financial plan that aligns with your personal financial goals. This plan should encompass budget management, cash flow, expenses, and essential recordkeeping, as these factors contribute significantly to achieving financial objectives. 2. Create an Investment Policy Statement. Establish an investment policy statement — a written document that outlines your portfolio allocation, target returns, and rules for rebalancing. It’s essential to base your investment strategy on reasonable forecasted returns, typically in the 6%-10% per year range. Avoid the temptation to pursue excessively high returns, as this can lead to taking on unnecessary risk. 3. Focus on Downside Protection and Liquidity. For retail investors managing their money, prioritize downside protection and liquidity, especially in the current late-stage market environment. While taking calculated risks is important, ensure that you can hold quality positions through market downturns and avoid being forced to sell assets at a discount due to short-term cash flow needs. 4. Seek Professional Advice. Consider getting help

Private credit in Europe’s lower mid-market offers something increasingly rare: structural inefficiency that favors investors. While the United States dominates private credit by scale, Europe’s reliance on banks, smaller fund sizes, and regional fragmentation leave a persistent financing gap for firms too small for global capital markets but too large to depend solely on local banks. This creates a compelling, and likely durable opportunity for private credit funds with local market expertise. Despite lower base rates, borrowers in Europe are paying higher spreads and fees as the all-in yields in Europe and the US are broadly similar. Further, bank retrenchment and concentrated fundraising among the largest funds have left the fragmented lower mid-market less competitive. For investors, that means an attractive entry point today. Structural inefficiencies continue to preserve pricing power, making partnership with the right managers critical. Access to debt financing is critical for the growth of small- and medium-sized enterprises (SMEs), which form the backbone of the European economy. According to the European Commission, SMEs represent more than 99% of the European Union’s 32.3 million enterprises. The lower mid-market — firms with 250 to 5,000 employees — comprise roughly 8% of EU businesses, or about 2.6 million companies. Historically, SMEs have relied heavily on banks, particularly in continental Europe. Stricter capital requirements imposed on banks post-financial crisis have constrained bank lending, in turn hitting the lower mid-market especially hard, particularly outside major financial hubs such as London or Frankfurt[1]. Private credit has stepped in to partially fill this gap, but capital is increasingly concentrated. In 2024, 94% of all private credit capital raised globally went to the largest 50 funds, up from 81.5% a year earlier[2]. As a result, terms and pricing in the upper mid-market (typically EBITDA > €25–30 million) have largely converged between the United States and Europe, with borrowers enjoying ample access to credit. In contrast, the lower mid-market remains fragmented and less intermediated, creating a structural opportunity for non-bank lenders and offering greater degree of transaction control and pricing power. Recent research by Aksia supports this conclusion[3]. Quantifying the Opportunity To compare the European and US lower mid-market landscapes, we gathered data on direct lending funds in both regions from various data sources[4]. In total, we considered approximately 20 senior secured loan funds in each region.  While not statistically exhaustive, the analysis reveals several consistent patterns. All-in yields in Europe are slightly higher than they are in the United States, despite lower base rates. This has been the case since mid-2022, the start of the Federal Reserve and European Central Bank rate hikes. As of September 1, 3-month SOFR stood at approximately 4.03% versus 3-month Euribor at roughly 2.07%. While difficult to measure empirically, this suggests that borrowers in Europe face higher spreads, higher upfront fees, or both.   More importantly, we observe more conservative deal structuring and risk profiles in Europe, particularly in terms of leverage. In cash flow-based loans, leverage (Debt/EBITDA) tends to be lower in Europe: our sample suggests a difference of approximately 0.5x. From our own market observations, debt-to-ARR multiples in the software sector peaked at around 2x in Europe and have since fallen to below 1x, compared to current US levels of 2x, and as high as 3x at the peak. Why the Gap Persists The attractive risk-reward profile in European lower mid-market private credit reflects a combination of structural inefficiencies and cyclical dynamics. While market conditions may evolve, many of the underlying drivers point to a lasting transatlantic gap. Cyclical factors include interest rate and currency differentials, which affect base rates and hedging costs. Europe’s weaker recent macro backdrop including slower growth, geopolitical uncertainty, and energy shocks, has tempered lending appetite. In contrast, parts of the US market have shown signs of exuberance, with tighter spreads and looser structures. Structural differences like a shallower institutional capital pool, bank dominance, and borrower conservatives are more enduring. The European private credit market remains less developed than the US market.  In 2024, North America–focused private credit funds captured ~72% of global capital raised[5].  Since 2008, ~70% of private credit capital has been raised in North America and ~25% in Europe, according to the RBA summary of IMF/PitchBook work. While capital flows might be shifting, the depth and dynamism of the US market means near-term convergence is unlikely. As of December 2024, European direct lending dry powder stood at approximately $80 billion, down from nearly $95 billion a year earlier, whereas North America hit a record $167 billion in December 2024, up 17% year-on-year[6]. In addition, the more advanced private credit landscape in the United States also gives North American managers the ability to employ scale-enhancing tools such as fund-level leverage and co-investments more readily. This disparity illustrates the depth and efficiency advantages in the US market. At the smaller end of the spectrum, the gap widens. Since 2023, 453 North America-focused direct lending funds below $2 billion have been raised, compared to just 185 funds in Europe[7]. Investor preferences reinforce this divide. European LPs, typically more risk-averse, have limited appetite for niche strategies. Instead, they have favored large, plain-vanilla direct lending funds offered by the biggest US managers. On the demand side, European borrowers remain more conservative, with smaller deal sizes, slower decision-making, and less familiarity with structured credit. Such cultural and behavioral factors reduce transaction velocity but also limit lender competition and support more conservative structures with arguably superior risk dynamics. Bank reliance, especially in DACH (Germany, Austria, and Switzerland), and Southern Europe, further entrenches the gap. While non-bank lenders have grown market share in sponsor-led transactions — accounting for 56% in Germany in 2024 and 20–40% in Spain over the past two years — most SMEs still lack access to tailored credit.  Combined with Europe’s legal, cultural, and regulatory fragmentation, and the need for local presence across multiple jurisdictions, these structural factors make near-term convergence unlikely, particularly in the lower mid-market. Implications for Investors Europe’s private credit market has progressed just as investor sentiment towards the asset class has shifted. Borrowers in the upper mid-market have

“We don’t think we were wrong. We think we were early.” A cringe-worthy answer that rings alarm bells for investment consultants. Higher inflation, increased market volatility, and more variable nominal interest rates are significant opportunities for active managers who can demonstrate their value with differentiated, customer-centric products. But with active management under ongoing scrutiny, investment managers are being caught off guard by tougher questions from an increasingly sophisticated allocator market. Are you prepared for your next beauty parade? The Changing Conversation Between Allocators and Managers I recently sat down with manager selection experts Evan Frazier and Joe Wiggins. During our conversation, they shared the tough questions that investment consultants and asset allocators are now asking prospective managers. Frazier, CFA, CAIA, is a senior research analyst at Marquette Associates in Chicago and Wiggins is director of research at St. James’s Place in London and author of a popular blog about investor behavior. The following are four of the most productive and challenging questions, as well as the motivation behind them. If you were to run your strategy systematically as an algorithm, how would you do it? Wiggins looks at three main aspects when evaluating a portfolio manager: The manager’s beliefs about markets and their competitive advantage, The manager’s decision-making process and its consistency with their beliefs, and The outcomes generated by those beliefs and processes. This question focuses on the manager’s process. The manager’s answer reveals the extent to which they have thought through the best use of their human energy, and the extent to which they have embraced technology to do the things that can be done systematically. What are some mistakes you’ve made throughout the strategy’s history or your tenure? How have you reacted? “Every PM loves to talk about — and can talk about — the winners that they’ve had,” Frazier notes. “But I think it’s helpful to get a sense of when things may not have worked out.” Allocators want to hear, and ideally see evidence, that the manager has reflected on their mistakes without just blaming bad luck. They are interested in understanding what lessons were learned and how those insights are being applied to achieve better outcomes in the future. Demonstrating humility, accountability, and objectivity goes a long way with sophisticated investors in this day and age. Assuming recent performance is not necessarily a good indicator of your actual skill level, how do you measure the success of your decision-making? This is one of Wiggins’ preferred questions from an outcomes perspective. He’s not looking for a specific answer. He wants to know if the fund manager has thought about this question because it provides insight into the philosophy and approach behind their strategy. “If they were taking a view that headline performance was all you needed to know to assess whether someone had skill or not, I would be incredibly skeptical,” he says. This gets to the heart of our Behavioral Alpha Benchmark: It looks beyond the historical returns and the effects of luck to measure a portfolio manager’s demonstrated skill across a range of investment decision types. How has your investment process evolved over time? Frazier and Wiggins agree on this one. Investors want to see that the manager is consistently making decisions that are aligned with the fund’s philosophy, but they also expect the investment process to evolve as technology advances. “Clearly no investor has got an unimpeachable or perfect process,” Wiggins remarks, but he cautions that a change to process should not be based solely on a single, painful example. “You really want to build up an evidence base and recognize patterns in your process and decision-making about where you can potentially make enhancements.” More and more, active managers are realizing that there’s no longer a competitive advantage to being smarter than everyone else or even to having access to better information. As I’ve discussed previously, what’s left is “behavioral alpha” — the excess returns that can be generated by “knowing thyself” and being more focused on self-improvement than the next person. And that starts with asking yourself hard questions. It’s clear that the landscape of active fund management is shifting. Transparency is increasing, data is more accessible and cheaper alternatives abound. Managers who are caught off guard by the tougher questions being asked by the sophisticated end of the allocator market are at an avoidable disadvantage. The good news is that a new generation of both allocators and fund managers is more committed than ever to continuous improvement, fostering true partnerships and doing their best for end investors. source