CFA Institute

Saudi Arabia’s economy is surging. The debt market tells the story: Banks in the Kingdom have extended more than SAR 2.2 trillion — that’s $587 billion in US dollars — in credit facilities to the private sector, with half of those credit facilities long-term, as of December 2022. These are record numbers and reveal the momentum behind Saud Arabia’s exceptional growth story. Public-private partnership (PPP) transactions and the wider project finance industry are core to that momentum. Indeed, such projects are expanding at an accelerated pace, supported by infrastructure projects prioritized by the government as well as mega and giga projects across the country. Yet this remarkable growth comes with risks — interest rate risk, in particular. The three-month Saudi Arabian Interbank Offer Rate (SAIBOR) over the last 10 years shows a recent surge and rising volatility. Compared with just 0.52% for the first five years, the daily standard deviation has more than doubled to 1.21% over the last five. Three-Month SAIBOR Historical Curve This raises questions about how interest rate risk should be allocated between the two primary stakeholders in any project finance transaction: the project company and the beneficiary entity. The former is a special purpose entity created to deliver the project and whose only asset is the project, while the latter, also called the off-taker or the procurer, pays the project company to deliver the agreed scope. So, how can these two stakeholders best split the interest rate risk? The Local Market Brief The allocation of interest rate risk differs by project, but the conventional approach in Saudi Arabia puts the onus on off-takers. These beneficiary entities assume the interest rate risk as outlined in the winning bidder’s initial financial model through the hedge execution date. The bidder’s profitability is shielded from any interest rate volatility until the hedge execution. If the interest rate rises above the assumed rate at the execution date, the financial model is adjusted to maintain the profitability metrics, with the off-taker paying for the interest rate deviation. If the interest rate falls, however, the benefits go to the off-taker. To balance this equation, the stakeholders need to agree on an optimal hedging strategy and understand from the outset how the interest rate risk is allocated. Here’s what needs to be done at the four key stages of the project finance process to achieve these outcomes. 1. The Pre-Bid Stage The project company must devise and articulate a hedging strategy that specifies the hedge duration, optimal hedging quantum, and the instrument under consideration, among other critical factors. A smooth close-out requires buy-in from the lenders and hedge providers. The project company’s goal is a successful close. As such, it should focus on securing the financing and executing the relevant documents as soon as possible. If the hedging element isn’t well planned, it could create delays and saddle the project company with unfavorable economic terms. To establish the financial model and forecast, the project company must calculate the interest rate risk allocation before submitting its bid. For instance, if the planned financing is long term and the financing currency is not liquid enough for the whole hedge tenor, the project company should quantify the impact and build it into the project economics. Will the off-taker continue to compensate the project company for the interest rate risk of the unhedged portion after hedge execution? That must be clear early on. Will the off-taker participate in the subsequent gains but not the losses? If so, the project company needs to make an assessment. Any margin the hedge providers make is usually excluded from the off-taker compensation plan since the project company bears the cost. That’s why the project company needs to plan and discuss the hedging credit spread with the hedge providers. 2. The Post-Bid Pre-Financial Close Stage This is the key juncture in project finance, and its success or failure hinges on the project company’s grasp of the pre-bid stage agreement. The project company might prefer that all parties agree on a hedge credit spread or that the spread be uniform across the lenders or hedge providers. But sometimes a credit spread based on the risks carried by the lenders may make sense. At other times, the project company may favor credit spread competition among the hedge providers. In that case, every lender has a right to match according to the debt size on a prorated basis. The downside of this approach is that it might cost the lender an opportunity to participate in an income-generating trade, which could make the transactions less profitable than forecast.  If there is a minimum mandatory hedging requirement for long-term financing, the project company could obtain a tighter credit spread for the subsequent tranches. However, lower risk during the project completion or operation periods could mean this spread is better than the first tranche. Without an open dialogue at the outset, the project company accepts — by default — the initial credit spread for the subsequent hedges. A hedging protocol should be drafted early and align with the agreed hedging strategy. The party that assumes the interest rate risk typically has more flexibility to design the protocol to ensure fairness, prudence, and transparency. A dry run (rehearsal) of the hedge helps test the protocol’s reliability. But that requires an independent bench marker to validate the lowest competitive rate. The lowest rate is not always the best. Project finance transactions involve complex financial modeling, and the cash flows change based on the hedge rate. Therefore, coordinating timely turnarounds with the updated cash flow is crucial. The financial/hedge adviser must administer the process according to how the hedging protocol defines it. Some project companies and off-takers may put an acceptable deviation limit between the assumed floating curve and the actual market rates, but each party must understand what’s at stake and set appropriate thresholds. The International Swaps and Derivatives Association (ISDA) Agreement and schedule specify the terms of the derivative dealings. The schedule is customized and negotiated on both commercial and legal

The financial markets are among the most effective tools we have to fight climate change, and the net zero transition will require trillions of dollars in annual investment between now and 2050, according to analysts. While that’s certainly an impressive number, given specific climate exposure-related mandates, investors at this stage want to understand the risk and return dynamics reflected in a company’s environmental score. So, how can investors assess climate transition risk in their portfolios? Both to answer this question and to better understand the relationship between stock returns and a company’s carbon emissions., I conducted a comprehensive analysis of MSCI Europe returns from 2007 to 2022 that incorporates supply-chain related Scope 3 emissions. The study revealed two intriguing findings. 1. Time Frames Matter Simply adding one or two years to a sample period can dramatically change the results. Many previous climate finance studies only covered bullish market cycles. Sustainable investments in Europe performed well between 2010 and 2021, for example. But if we extend the time frame to year-end 2022, thus incorporating the energy crisis that followed Russia’s invasion of Ukraine, that “green” alpha evaporates. Even before the pandemic, amid disappointing energy sector returns, investors had redirected their capital from old economy stocks to their new economy counterparts. Then, several years of insufficient CapEx investment contributed to an energy supply deficit that only manifested itself as the global economy transitioned into the post-pandemic recovery phase. The war in Ukraine further exacerbated this effect, causing a huge spike in energy prices. Following the global financial crisis (GFC), monetary policy dominated the financial landscape. Low and negative interest rates and quantitative easing (QE) helped create bubbles in certain assets. The lower-for-longer interest rate environment pushed growth stocks — with their longer-term cash flow horizons relative to value stocks — to overshoot. Glamour stocks — think Tesla — soared as old economy stalwarts, with their tendency to generate higher emissions, sputtered. To put this in perspective, long-term cash flows are now discounted at over 5%. Before 2020, the norm was below 1%. One possible explanation for this is that other variables correlate with the GreenMinusBrown (GMB) factor. According to my analysis, the High Minus Low (HML) factor has a moderately negative correlation to the GMB factor. Since the HML factor’s style is more value than growth, the GMB factor may have more of a correlation with growth stocks. This makes intuitive sense: After all, green portfolios tend to be a combination of technology and health care stocks. Such stocks will often outperform when interest rates are low, as they were from 2010 to 2021, for example, when growth outpaced value. 2. Emissions = Perceived Risks There is also evidence of a positive relationship between a company’s greenhouse emissions and the perceived risk associated with that company. Brown portfolios are always more volatile than their green peers, and their level of absolute risk grows when Scope 3 emissions are included. Indeed, the Scope 1, 2, 3 Intensity emissions ranked portfolios demonstrate the largest volatility spread. This means that the higher returns that brown companies generate reflect their higher risk. In Europe, green portfolios have been slightly less volatile on average than brown over the past 15 years. This is in line with CAPM predictions and with research exploring how green investments can help hedge client portfolios. In theory, if green assets provide a hedge against climate risk, among other benefits, and are perceived as less risky because of their climate-resilient nature and other positive social impacts, investors may be willing to accept lower expected returns to hold them.  Returns on Green and Brown Portfolios on Scope 1, 2, 3 Intensity This figure plots the green and brown portfolios’ cumulative returns for the MSCI Europe from 2007 to 2022. The Scope 3 Emissions Effect is essential to understanding green exposure. The regression analysis exhibits the greatest explanatory power when it incorporates Scope 3 emissions. As such, the model better captures the full extent of a company’s sustainability performance. Scope 3 emissions will only become more relevant: New regulatory developments and reporting standards in Europe require companies to disclose these emissions beginning in 2024. The risk management theme is at the core of climate finance and anticipates a positive correlation between greenhouse gas emissions and stock returns, or a negative correlation between emissions and company valuations. Investors recognize that firms with strong environmental practices are more likely to be sustainable in the long term and are better positioned to navigate changing regulations, consumer preferences, and market dynamics, and are thus attractive investments.  So, What’s the Takeaway? The distinction between brown and green performance may not be so clear cut. Why? Because interest rates, investment trends, and other phenomena can influence sector performance. Moreover, many factor models assume that governments around the world will implement policy changes in the future. Carbon taxes, among other measures, have been discussed as potential tools for solving climate issues, and many models anticipate they will be implemented sometime in the months and years ahead. But the impact of such changes in climate change policy have yet to take effect or appear in financial returns. These conclusions aside, reducing climate risk exposure has several implications for investors. First, conservative investors will try to reduce their transition risk by hedging their exposure to it, and investors with exposure to transition risk will expect higher returns as compensation. If they don’t think they are earning enough return on that risk, they will engage with their companies and try to persuade them to hedge that risk. For corporates, on the other hand, transition risk management has one principal consequence: The more exposure to climate change risk, the higher the cost of capital. That implies both lower price multiples on future earnings and higher break-even rates on new investments. 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

Under the private equity fundraising model, every few years fund managers secure capital commitments with a 10-year duration and charge management and advisory fees during the lock-up period. While longer-dated products have emerged over time, the basic pattern has remained essentially unchanged. Unfortunately, fundraising is cyclical. Downturns require patience: Fund managers must wait until the green shoots of recovery appear before going back to market for a new vintage. Clearing the Fundraising Hurdle Economic slowdowns affect the credit supply, capital availability, and the health of portfolio assets. In the wake of the global financial crisis (GFC), even large firms like UK-based Terra Firma couldn’t close a fresh vintage, while others — BC Partners, for example — barely survived, maintaining their asset bases but never truly expanding again. Global operators, too, struggled to get back on the growth path. Some, such as TPG and Providence Equity, had difficulty attracting fresh commitments and raised far less than they had for their pre-GFC vehicles. KKR took eight years to close a new flagship buyout fund, collecting $9 billion in 2014, barely half the $17.6 billion it had generated for its previous vintage. While small fund managers were stuck with the legacy model, the largest players looked elsewhere for solutions. Vertical integration was one path forward: For example, Carlyle acquired fund of funds manager Alpinvest from pension funds APG and PGGM in 2011. Warren Buffett’s Berkshire Hathaway offered PE firms a new template. Thanks to the float of its car insurance unit, GEICO, the company has permanent access to a perennial pool of capital. Apollo, Blackstone, and KKR, among others, all acquired insurance businesses over the past decade to harvest a similar fount of capital and leverage a perpetual source of fees. Indecent Exposure But there is a snag. Insurance is sensitive to random variables: Rampant inflation, for example, leads to higher claims costs and lower profits, especially for property-liability insurers. Sudden interest rate movements or, in the case of life insurers, unexpectedly high mortality rates (e.g., due to a pandemic) can have outsized effects on the bottom line. The Financial Stability Board (FSB) in the United States suspended the global systemically important insurer (GSII) designation two years ago, acknowledging that the insurance industry, unlike its banking counterpart, does not present a systemic risk. But the macroeconomic backdrop is much harder to control than corporate matters and can hinder cash flows. As such, the failure of an individual insurer might not have a domino effect, but it could be precipitated by a severe lack of liquidity. That outcome is more likely when the insurer is exposed to illiquid private markets. So, a sustained economic crisis could impede a PE-owned insurer’s ability to underwrite policies, issue annuities, or settle claims. Insurers have a public mission to cover the health or property of their various policyholders. PE firms, on the other hand, have a primary fiduciary duty to institutional investors. Indeed, unlike private capital, the insurance industry is highly regulated with strict legal obligations. This has critical implications. For example, past customer service and corporate governance issues at life insurers Athene and Global Atlantic, today owned respectively by Apollo and KKR, resulted in heavy fines. Such incidents can expose private capital to public scrutiny and make the trade more unpredictable, especially when insurance activities account for much of the business. Last year, for instance, Athene represented 30% of Apollo’s revenue. Alternatives Supermarkets Another solution to the PE fundraising dilemma was asset diversification, a blueprint first implemented by commercial banks in the late 1990s and early 2000s. Citi and the Royal Bank of Scotland (RBS) acquired or established capital market units and insurance activities to give clients a one-stop shop. Cross-selling has the dual advantage of making each account more profitable and increasing customer stickiness. Blackstone, Apollo, Carlyle, and KKR (BACK) built similar platforms to help yield-seeking LP investors diversify across the alternative asset class. They now offer single-digit-yielding products like credit alongside riskier higher-return leverage buyout solutions as well as longer-dated but low-yielding infrastructure and real asset investments. By raising funds for separate and independent asset classes, BACK firms shield themselves from a potential capital market shutdown. While debt markets suffered during the GFC, for example, infrastructure showed remarkable resilience. Still, such innovations have drawbacks. “Universal” banks underperformed their smaller and more tightly managed rivals. Opportunistic deal-doing betrayed a lack of focus. For instance, RBS acquired used-car dealership Dixon Motors in 2002 despite little evidence of potential synergies. In addition, a pathological obsession with return on equity (ROE) failed to account for the declining quality of the underlying assets. Moreover, retail bankers frequently proved to be mediocre traders, M&A brokers, corporate lenders, and insurers. Early indications suggest that multi-product platforms like BACK may not be able to produce the best results across the full spectrum of private markets. Carlyle’s mortgage-bond fund operations and its activities in Central Europe, Eastern Europe, and Africa as well as KKR’s European buyout unit all failed or struggled in the past, which demonstrates the challenge of monitoring and maintaining performance across the board while running a financial conglomerate. Murky product-bundling may further hamper returns at these world-straddling alternative asset supermarkets. A Performance Conundrum That diversification decreases risk while lowering expected returns is one of economic theory’s bedrock principles. Yet, in 2008, diversification at “universal” banks showed how risk can be mispriced when the performance correlation between products is underestimated. Risk can increase when all-out growth strategies are not accompanied by adequate checks and balances. The quasi-exclusive emphasis on capital accumulation and fee-related earnings by publicly listed alternative fund managers may come at the expense of future returns. This is one lesson of Berkshire Hathaway’s business model that the new breed of PE firms may not recognize. Achieving unconditional access to a capital pool is one thing; putting that capital to work is quite another. The cash surplus from the insurance float — over $100 billion as of 30 June –has made it virtually impossible for Berkshire Hathaway to beat public

Thomas M. Idzorek, CFA, is the author of “Personalized Multiple Account Portfolio Optimization,” for the Financial Analysts Journal, and co-author of Popularity: A Bridge between Classical and Behavioral Finance, from the CFA Institute Research Foundation. Like many topics that inspire passion and thoughtful debate, environmental, social, and governance (ESG) investing is complex and multifaceted. Unfortunately, at least in the United States, ESG investing has become politicized, which makes nuanced perspective and analysis more and more difficult. If only there were an economic theory we could leverage to rise above the binary, politicized landscape, that would help us understand the different impacts of ESG analysis on risk and expected return and how such considerations should or should not influence portfolio construction for different investors. Fortunately, we have such a theory — the popularity asset pricing model (PAPM)!  While most finance and investment professionals know about the capital asset pricing model (CAPM) as well as Harry Markowitz’s mean–variance optimization, PAPM knowledge is much more limited. In the CAPM, every investor formulates their investment problem in Markowitz’s mean–variance framework. By assumption, markets are perfectly efficient and all investors “agree” on the risk and expected returns of all assets. Thus, everyone arrives at the same efficient frontier and the same Sharpe-maximizing market portfolio, which is then levered or unleveraged based on risk tolerance. Mean–variance optimization becomes unnecessary, and investors have no other “tastes” beyond their risk tolerance, which leads to different levels of leverage.  Empirically, there are numerous anomalies in which realized long-term average returns differ from the expected returns from the CAPM. Eugene Fama and Kenneth French, in particular, have proposed various hidden risk factors to explain departures from the CAPM. Their paper “Disagreement, Tastes, and Asset Prices,” marks a shift in their perspective. They describe “disagreement” and “tastes” as the two missing ingredients from the CAPM that affect asset prices. Disagreement is the notion that people have different capital market expectations, and tastes are the investor’s individual preferences beyond risk tolerance for various attributes and characteristics. The PAPM incorporates both ingredients in a generalized equilibrium asset pricing model. Each investor solves a mean–variance optimization problem based on their capital market expectations, which include an additional term that captures how much utility the investor derives from a portfolio that tilts toward their preferred characteristics and away from those they dislike. At the same time, that term allows for any magnitude of like and dislike. For example, an investor may be somewhat fond of green energy but hate handguns. If enough investors have a strong positive or negative feeling about a characteristic, it impacts asset prices. Over long periods and in line with the PAPM, many CAPM anomalies indicate that a return premium may accrue to the shunned characteristic. Under PAPM, individual investors may all have unique views on how ESG characteristics or sub-ESG characteristics influence expected risk and return. They may also have different tastes as to what characteristics they want reflected in their portfolio. Likewise, they may view almost any given characteristic from a pecuniary and nonpecuniary perspective.  For example, genetically modified organisms (GMOs) evoke a range of views from investors. From a pecuniary perspective, some may believe that demand and price for GMOs will increase or decrease and, as a result, future returns will be better or worse than the market.  From a nonpecuniary perspective, some investors may prefer investing in companies that produce GMOs because they believe it will help feed humanity and end world hunger. Others may want to avoid such companies because they fear GMOs could threaten biodiversity.  Such views and preferences may or may not be mutually exclusive and at times may defy expectations. One investor may believe that demand and prices for GMO products will fall but still think that fighting world hunger is a worthy cause. Another investor may expect price and demand to rise but feel that it is a small price to pay to prevent GMOs from potentially harming the environment. Investors are complex. As practitioners, we should seek out foundational theories and models that reflect reality and that have fewer and less restrictive assumptions. ESG true believers may think that ESG investing can save the world and improve a portfolio’s expected risk and return. ESG skeptics, on the other hand, may feel that taking ESG considerations into account in investing decisions should be illegal. Both perspectives are flawed. The expectation that selecting only investments with high ESG scores will lead to superior returns is just as wrongheaded as restricting the use of pecuniary ESG information in investment analysis and portfolio construction. After all, investors who ignore pecuniary ESG considerations operate at an informational disadvantage and are likely to underperform. So, too, are those who only invest in securities with good ESG scores for nonpecuniary reasons or who avoid such securities for nonpecuniary reasons. On the other hand, investors who consider pecuniary ESG factors and ignore nonpecuniary ones are likely to overperform. Investors who apply pecuniary ESG considerations and have nonpecuniary tastes are likely to underperform, yet from a PAPM perspective, they should own personalized, utility-maximizing portfolios! For those without tastes or strong pecuniary views, that “personalized” portfolio will often be a passive, low-cost portfolio.  Therefore, individual investors and those that serve them should build personalized portfolios that reflect their views and preferences to the degree that they have them.  As for institutional portfolios, those who manage public pension plans or other large portfolios that serve diverse groups of people should not limit the investment universe based on their personal preferences. This is especially true when those whom the portfolio serves have no other choice. To the degree that any pecuniary factor, ESG, or otherwise, may influence risk and return, stewards of public capital should consider all applicable information and should not be restricted from using applicable pecuniary ESG information. This could include seeking to take advantage of the impact of tastes by purchasing unpopular assets and avoiding overly popular ones. The PAPM moves us beyond broad strokes and divisive rhetoric by explaining how disagreement and tastes influence personalized portfolio construction and ultimately

The finance community has invested much effort to identify new factors that may indicate a security’s forward-looking performance or a portfolio’s risk attributes. While this research can help us better understand asset pricing and offer the possibility of better performance, too often it presumes continuous markets, free trading, and boundless liquidity. Far less research has focused on the practitioner’s dilemma: implementation shortfalls caused by frictions like trading costs and discontinuous trading. These real-life frictions can erode the performance of smart beta and factor strategies. Along with asset management fees, they are the main sources of the sometimes-vast gap between live results and paper portfolio performance. Smart rebalancing methods can capture most of the factor premia while cutting turnover and trading costs relative to a fully rebalanced portfolio by prioritizing trades to the stocks with the most attractive signals and focusing portfolio turnover on trades that offer the highest potential performance impact. In our study of long-only value, profitability, investment, and momentum factor portfolios created between 1963 and 2020, we examine performance and related turnover. We present results for the same strategies after applying three different turnover reduction methods to periodic portfolio rebalancing. We measure the efficacy of these different rebalancing rules in preserving as much of the factor premiums as possible. We also construct a monthly composite factor based on monthly value and momentum signals to guide rebalancing of multi-factor strategies. The first rebalancing method, which we call proportional rebalancing, trades all stocks proportionally to meet the turnover target. For example, if the strategy indicates trades that are twice as large as the turnover target, this method trades 50% of the indicated trade for each stock. The second rebalancing method, priority best, buys the stocks with the most attractive signals and sells the stocks with the most unattractive signals, until the turnover target is reached.[1] The third method, priority worst, deliberately sorts the queues in the “wrong” order, buying the stocks that seem the most marginal in terms of their signals, saving the strongest buy or sell signals to trade last. In these comparisons, we find that the priority best method typically outperforms the other two methods. Calendar-Driven Rebalancing Not Always the Best Option Instead of forcing portfolios to rebalance on a fixed schedule, we also consider a rule in which we rebalance when the distance between the current and target portfolios exceeds a preset threshold. Conditional on meeting this threshold, we then rebalance a prespecified proportion of the deviations using one of the three rules mentioned above. Again, we find that the priority-best rule generally outperforms the other two rules in the context of non-calendar-based rebalancing. We seek to construct a turnover-constrained factor that retains as much of the reference factor’s premium as possible. An intuitive rule for prioritizing trades is based on stocks’ signal values. For example, if two new stocks enter the top quartile and we have enough turnover budget to trade into just one of them, it might make sense to trade the one with the more attractive signal. This rule implicitly assumes that future average returns are monotonic in the signal. That is, if we have stocks A, B, and C with signals 1.0, 1.5, and 2.0, we would expect a trading rule that prioritizes trades based on signal values to outperform other trading rules. In the first part of our analysis in the Financial Analysts Journal, we report a number of performance metrics for the long-only factors we study. These factors, which hold various segments of the market, earn Sharpe ratios ranging from 0.60 for the monthly-rebalanced composite factor to 0.47 for the monthly-rebalanced value factor. All factors, except for the monthly value factor, earn CAPM alphas that are statistically significant at the 5% level.[2] These Sharpe ratios and alphas, however, are based on the portfolios’ gross returns. The extent to which an investor could have come close to attaining this performance depends on the turnover the factor strategies incur and how much the underlying stocks cost to trade. We then report CAPM alphas and t-values associated with these CAPM alphas for six sets of decile portfolios to assess how monotonic returns are in the signals. Our estimates indicate that expected returns are not entirely monotonic for most of the factors’ signals, meaning a trading rule that prioritizes trades based on signal values may not always add value. Only trades with sufficient conviction can generate a post-trading-cost benefit to investors. If the signals were to convey perfect information about the stocks’ future performance, a fully rebalanced portfolio would deliver the best outcome, though not necessarily net of trading costs. When the signals are noisy and imperfect predictors of expected returns, as in the real world, a full-fledged rebalance is not likely to be the best solution when trades are costly. Priority-Best Rule Optimizes Rebalancing Benefits The priority-best rule, by design, significantly reduces turnover relative to an unconstrained version, while capturing most of the return benefit associated with factor investing. The efficacy of this rule, however, depends, as hypothesized, on the monotonicity of the relationship between a factor’s signal values and its average returns. The main takeaway from our application of the priority-worst rule is that any investor who wants to run a momentum strategy, and accepts that this strategy will trade frequently, would do well to prioritize trades with the most attractive signal values. We also report the results from a simple rebalancing method, using the proportional rebalancing rule, which does not prioritize any trade over another but instead partially executes a fixed fraction of trades to satisfy the turnover constraint. The estimates show that this rule typically falls between the two extremes represented by the priority-best and priority-worst rules. The benefit of this rule may be diversification: by spreading the trades across a larger number of stocks, the resulting portfolios occasionally take less risk. Our estimates suggest the priority-best rule is even better for controlling turnover in a non-calendar-based setting than in a calendar-based setting. Its efficacy in controlling turnover relative to

The Power of Money: How Governments and Banks Create Money and Help Us All Prosper. 2023. Paul Sheard. Penguin Random House. In The Power of Money: How Governments and Banks Create Money and Help Us All Prosper, Paul Sheard, an Australian American economist and the former vice chair of S&P Global, provides novel explanations related to money, including what it is and how governments, commercial banks, and central banks create it and influence its creation. He clarifies several common misunderstandings and controversies that many people have about money, including whether the US government is imposing a huge burden on our grandchildren and mortgaging their future by racking up large amounts of debt. That particular species of fallacious thinking, termed a “category error,” treats the government as if it were a single household, when, in fact, it is analogous to an amalgam of all households in a country. The current generation can borrow only from itself, not from future generations that do not exist yet. According to Sheard, every generation leaves to the next generation a capital stock that is always bigger and better than what it received from the prior generation. There is no reason that governments should always balance their budgets, and generally, they should not. If too much government debt is outstanding at some point, then macroeconomic policy can take care of it. Sheard explores many important money topics that are relevant today, such as bank runs and financial crises, the euro sovereign debt crisis, wealth inequality, and bitcoin and other cryptocurrencies. Money can cause serious problems for an economy and society at large. The risk of bank runs and financial crises arises because of the inherent mismatch between the liquidity of financial claims that the monetary economy generates and the illiquidity of the productive assets that constitute the real economy. The central bank’s role as the lender of last resort empowers it to prevent financial crises and quell those that occur. Sheard argues that the US Federal Reserve erred in not acting as lender of last resort to Lehman Brothers in 2008. The euro sovereign debt crisis of 2009–2010 revealed a deep structural flaw in the euro area’s economic architecture. Member states are obligated to pool their monetary sovereignty but not their fiscal sovereignty. They cede their monetary sovereignty to the European Central Bank while retaining responsibility for their fiscal affairs. The situation results in member nations having to borrow in a foreign currency, one they cannot produce at will. For the euro to endure, says Sheard, euro area members must voluntarily accept stringent fiscal restraints and recognize that pooling monetary sovereignty is a political act. The right of a nation state to create and control its own money is a core aspect of sovereignty. According to Sheard, if the EU political elites cannot explain to their electorates that monetary union is just as deeply political in nature as fiscal union and garner the necessary consent to complete the economic and monetary union, the euro may one day be finished. The book also looks at the economic forces behind large wealth disparities, especially in relation to the tiny cohort of the uber-rich. Sheard argues that extreme wealth inequality is a by-product of prosperity-generating market processes and that the uber-rich do much less harm than is often claimed. If the government deems improving the plight of the poor desirable, it should do so independently of whether and how it “taxes the rich.” Finally, Sheard considers bitcoin and other cryptocurrencies to be not as detached from the legacy monetary system as they appear and likely to struggle to compete with it when it comes to fulfilling the three canonical roles of money: unit of account, medium of exchange, and store of value. Cryptocurrencies are likely to find a permanent niche in the monetary ecosystem, but they may at this time be early in their innovation cycle, making definitive predictions tough. Rather than challenging the traditional monetary system, cryptocurrencies and their foundational technologies are more likely, by spurring innovation, to help reshape it. In summary, this book is useful reading at a time when innovations such as bitcoin and other cryptocurrencies, as well as policy experiments such as quantitative easing (QE), have made it critical to understand how money works. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author(s). 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

“Once a majority of players adopts a heretofore contrarian position, the minority view becomes the widely held perspective.”[i] DAVID SWENSEN, late CIO of the Yale Investments Office Over the past several years, private credit fund managers have raised enormous amounts of capital, and future inflows are only expected to increase. Figure 1 shows the total assets under management of private credit funds from 2005 to 2023. Institutional investment plans constitute the bulk of these assets, and many investment consultants continue their aggressive pushes to add more. The following article questions the merits of such recommendations. It begins by explaining the distinct nature of alternative asset class investment cycles. Next, it explains the origin and evolution of the private credit boom, which now resides squarely in the “flood” stage of the investment cycle. Finally, it explains how a deep-seated conflict of interest at the heart of the investment consulting model is causing flood waters to rise despite dismal prospects for most investors. Figure 1: Private Credit Assets Under Management (2005-2023). Sources: Financial Times, Preqin, The Wall Street Journal; CION Investments. Alternative Investment Cycles The Fall 2024 issue of the Museum of American Finance’s Financial History magazine includes my article, “A 45-Year Flood: The History of Alternative Asset Classes.” It explains the origins of several alternative asset classes such as venture capital (VC) and buyout funds. It then explains why these asset classes have attracted massive inflows of institutional capital over the past several decades. Most importantly, the article explains the distinct investment cycle through which alternative asset classes progress. The cycle roughly includes the following three phases. Formation: A legitimate void appears in capital markets. For example, in the aftermath of World War II, US companies had a wealth of opportunities to commercialize war-related technologies, but banks remained skittish because of their experiences during the Great Depression. This prompted the formation of the VC industry. Early Phase: Innovative capital providers generate exceptional returns as the number of attractive opportunities exceeds the supply of capital available to fund them. The experience of VC and buyout fund investors, such as the Yale University Endowment, in the 1980s is a perfect example.[ii] Flood Phase: In pursuit of new revenue streams, opportunists launch a barrage of new funds, and then a herd of followers invests in them. This invariably compresses future returns because the supply of capital far exceeds the number of attractive investment opportunities. In 2024, all major alternative asset classes — including private equity, VC, private real estate, hedge funds, and now private credit — have attributes that are consistent with the flood phase. In comparison to traditional asset classes like publicly traded US equity and fixed income, alternative asset classes have much higher fees, significant illiquidity, hidden risks, mind-bending complexity, and limited transparency. Making matters worse, most alternative asset classes have resided squarely in the flood phase for several decades. Unsurprisingly, multiple studies show that, on average, alternative asset classes detracted value from institutional investment plan performance rather than added it over the past few decades. For example, a June 2024 paper published by the Center for Retirement Research at Boston College cited four studies showing significant value detraction. The paper also presented the Center’s own research suggesting that alternatives added slightly less than no value relative to a passive 60/40 index over the past 23 years. Despite the high fees, hidden risks, and lackluster results, trustees massively increased allocations to alternatives over the past few decades. According to Equable, the average public pension plan allocated 33.8% of their portfolio to alternatives in 2023 versus only 9.3% in 2001. Private credit is just the newest alternative investment craze, but its trajectory followed the same well-trodden path. Now, just like those that came before, it is stuck in the flood phase. The Dynamics of the Private Credit Boom “Experience establishes a firm rule, and on few economic matters is understanding more important and frequently, indeed, more slight. Financial operations do not lend themselves to innovation. What is recurrently so described is, without exception, a small variation on an established design, one that owes its distinctive character to the aforementioned brevity of the financial memory. The world of finance hails the invention of the wheel over and over again, often in a slightly more unstable version.”[iii] JOHN KENNETH GALBRAITH, financial historian In the aftermath of the 2008/2009 global financial crisis (GFC), the US commercial banking system tightened lending standards and restricted loan issuance in several market segments. This enabled banks to restore their depleted reserves and strengthen their balance sheets. It also opened a temporary void in capital markets, which triggered a sharp rise in demand for private credit. Much like the formation of VC funds in the aftermath of World War II, private credit was hardly a novel innovation. It has existed in various forms for centuries. But the latest variation on this “established design” was widespread use of the limited partnership model. The key advantage of this model is that it offers fund managers protection against bank runs, which is a timeless risk for commercial banks. The cost of this protection, however, is borne almost entirely by fund investors rather than fund managers. Investors must accept much higher fees, many years of illiquidity, and an enormous lack of transparency regarding the nature and value of the underlying loans in which they are invested. Overlooking these disadvantages and enamored by returns produced in the early phase of the private credit cycle, trustees have poured hundreds of billions of dollars into this asset class over the past several years. They have all but ignored multiple red flags that invariably materialize in the flood phase. Why are institutional investors increasing their allocations to private credit? Because investment consultants are advising trustees to do so. Investment Consulting and Mean-Variance Obfuscation “You don’t want to be average; it’s not worth it, does nothing. In fact, it’s less than the [public] market. The question is ‘how do you get to first quartile?’ If you can’t, it doesn’t

What if you could get the performance of private equity (PE) without locking up your capital for years? Private equity has long been a top-performing asset class, but its illiquidity has kept many investors on the sidelines or second-guessing their allocations. Enter PEARL (private equity accessibility reimagined with liquidity). It is a new approach that offers private equity-like returns with daily liquidity. Using liquid futures and smarter risk management, PEARL delivers institutional-grade performance without the wait. This post unpacks the technical foundation behind PEARL and offers a practical roadmap for investment professionals exploring the next frontier of private market replication. State of Play Over the past two decades, PE has evolved from a niche allocation to a cornerstone of institutional portfolios, with global assets under management exceeding $13 trillion as of June 30, 2023. Large pension funds and endowments have significantly increased their exposure, with leading university endowments allocating approximately 32% to 39% of their capital to private markets. Industry benchmarks like Cambridge Associates, Preqin, and Bloomberg PE indices are published quarterly. They have reporting lags of one to three months and are not investable. These benchmarks report annualized returns of 11% to 15% and Sharpe ratios above 1.5 for the industry. A few research-based, investable daily liquid private equity proxies investing in listed stocks have been developed. These include the factor-based replication inspired by HBS professor Erik Stafford, the Thomson Reuters (TR) sector replication benchmark, and the S&P Listed PE index. While these proxies offer real-time valuation, they markedly underperform in risk-adjusted terms, with annual returns of 10.9% to 12.5%, Sharpe ratios of 0.42 to 0.54, and deeper maximum drawdowns of 41.7% to 50.4% compared to industry benchmarks. This disparity underscores the trade-off between liquidity and performance in PE replication. PEARL aims to bridge the gap between liquid proxies and illiquid industry benchmarks. The objective is to construct a fully liquid, daily replicable strategy targeting annualized returns of ≥17%, a Sharpe ratio of ≥1.2, and a maximum drawdown of ≤20%, by leveraging scalable futures instruments, dynamic graphical models, and tailored asymmetry and overlay techniques. Core Methodological Approach Liquid Futures Instruments PEARL invests in a large universe of highly liquid futures contracts on equity indices like the S&P 500, specific sectors and international markets, foreign exchange, Vix futures, interest rates, and commodities. These instruments typically have average daily trading volumes exceeding $5 billion. This high liquidity enhances scalability and reduces transaction costs compared to traditional replication strategies focused on small-cap equities or niche sectors. Equity futures are used to replicate the long-term returns of private equity investments, while exposures to other asset classes help improve the overall risk profile of the allocation. Graphical Model Decoding We model the replication process as a dynamic Bayesian network, representing allocation weights wt(i) for each asset class i in {Equities, FX, Rates, Commodities}. The framework treats these weights as hidden state variables evolving in time according to a state-space model. The observed NAV follows: Where rt(i) is the return of asset class i at time t. We infer the sequence {w_t} via Bayesian message passing coupled with maximum likelihood estimation, incorporating a Gaussian smoothness prior (penalty λ = 0.01) to enforce continuity across daily updates. Key features of graphical-model approach: State-space formulation: captures the joint dynamics of allocations and returns, extending Kalman filter approaches by modeling cross-asset interactions. Dynamic inference: prediction–correction via message passing refines weight estimates as new data arrives. Interaction modeling: directed links between latent weight variables across time steps allow for richer dependency structures ( e.g., equity–rate spillovers). Continuous updating: allocations adapt to regime changes, leveraging full joint distributions rather than isolated regressions. This graphical-model approach yields stable, interpretable allocations and improves replication accuracy relative to piecewise linear or Kalman-filter methods. In Figure 1, we used a simplified graphical model showing the relationship between observed NAV and inferred allocation as time goes by. For illustration purpose, we used different assets, with one being an Equity shortened in Eq, a second one an exchange rate shorted in Fx, a third one, an interest rates instrument shortened in Ir, and finally a commodity asset shortened in Co. Figure 1. Asymmetric Return Scaling To emulate the valuation smoothing inherent in PE fund reporting, we apply an asymmetric transformation to daily returns. Specifically, resulting in a 10% reduction of negative returns. Empirical analysis indicates this adjustment decreases average monthly drawdown by approximately 50 basis points without materially affecting positive return capture. Tail Risk and Momentum Overlays PEARL integrates two robust overlay strategies: tail risk hedge volatility strategy and risk-off momentum allocation strategy. Both are grounded in empirical machine‐learning and CTA‐style signal filtering, to mitigate drawdowns and enhance risk‐adjusted returns: Tail Risk Hedge Volatility Strategy: A supervised machine‐learning classifier issues probabilistic activation signals to switch between front‑month (short‑term) and fourth‑month (medium‑term) VIX long futures positions. The model leverages three core indicators: 20‑Day Volatility‑Adjusted Momentum: Captures recent VIX futures momentum normalized by realized volatility. VIX Forward‑Curve Ratio: Ratio of next‑month to current‑month VIX futures, serving as a carry proxy. Absolute VIX Level: Reflects mean‑reversion tendencies during elevated volatility regimes. Backtested from January 2007 through December 2024, this overlay: Increases the equity allocation annual return from 9% to 12%. Reduces annualized volatility from 20% to 16%. Curbs maximum drawdown from 56% to 29%. Increases the portfolio Sharpe ratio by 71% and delivers a 2.5× improvement in Return/MaxDD in comparison to a long equity portfolio. Risk‑Off Momentum Allocation Built on a cross‑asset CTA replication framework, this strategy systematically targets trends inversely correlated with the S&P 500. Key metrics include: Diversification Benefit: Achieves a -36% correlation versus the S&P 500. Downside Capture: Generates positive returns in 88% of months when the S&P 500 falls more than 5%. Performance in Stressed Markets: From 2010 to 2024, delivers an average monthly return of 3.6% during equity market downturns, outperforming leading CTA benchmarks by a factor of two in months with negative equity returns. Collectively, these overlays provide a dynamic hedge that activates during risk‑off periods, smoothing equity market shocks and enhancing the overall portfolio resilience.

“Exigencies are to be expected to occur, in the affairs of nations, in which there will be a necessity for borrowing. That loans in times of public danger, especially from foreign war, are found an indispensable resource, even to the wealthiest of them . . . it is essential that the credit of a nation should be well established . . . Persuaded as the Secretary is, that the proper funding of the present debt, will render it a national blessing.  Yet he is so far from acceding to the position, in the latitude in which it is sometimes laid down: ‘public debts are public benefits,’ a position inviting to prodigality, and liable to dangerous abuse — that he ardently wishes to see it incorporated, as a fundamental maxim, in the system of public credit of the United States, that the creation of debt should always be accompanied with the means of extinguishment. (Emphases added)” — Alexander Hamilton, “The First Report on Public Credit“ The United States hit its $31.4 trillion debt ceiling on 19 January 2023, a limit Congress approved only two years ago. The US Treasury is now taking extraordinary emergency measures to prevent the nation from defaulting. The current battle over the debt ceiling reveals a painful reality that the nation must confront. There are two important principles at stake, both of which Alexander Hamilton references in the quote above. The first is that maintaining US creditworthiness is essential to the nation’s economic health. To voluntarily default on the federal debt would compromise the very foundation of the country’s economic success. The second is that the current path of unsustainable fiscal deficits could lead to an involuntary default in the years ahead that would be just as catastrophic. These uncomfortable truths have some critical implications: 1. Public Debt Isn’t What It Used to Be In 1790, the survival of the United States was far from certain. The country had won the Revolutionary War and ratified the Constitution, but its finances were in disarray. The states and the federal government couldn’t service their war debt or even pay their veterans. This affected the performance of the nation’s economy and the government’s ability to regulate it. But Hamilton, the first secretary of the Treasury, understood the essential role that the integrity of the nation’s credit played in ensuring economic prosperity. He coordinated the passage of several regulations that restored the nation’s creditworthiness. These programs included the consolidation of war debt under the federal government, the institution of tariffs to fund outstanding debt payments, and the creation of a central bank. Without these measures, the United States may not have had the financial wherewithal to endure the “exigencies” to which Hamilton referred. Adhering to Hamiltonian financial principles helped the United States persevere through the War of 1812, the Civil War, and World War I. When these exigencies ended, the country abided by Hamilton’s second principle and ran federal budget surpluses to extinguish the debt. But that changed after World War II. Initially, the United States paid down its debt as it had before, but by the 1960s, permanent peacetime deficits had become the norm. Over the next decade, this trend is expected to continue with the deficit averaging 5% of GDP per year, according to the Congressional Budget Office’s (CBO’s) 2022 estimate. Such a trajectory is impossible to maintain indefinitely; yet the aging population and secular declines in productivity threaten to make the problem even worse beyond 2032. US Federal Budget Deficit as a Percentage of GDP, 1791 to 2022 Sources: White House Office of Management and Budget (OMB), US Bureau of the Census Why did the United States change its philosophical approach to public credit? One reason is simply that it could. The US dollar became the world’s reserve currency after the Bretton Woods Agreement in 1945, and US Treasuries became an essential store of value for central banks and savers across the world. The massive expansion of entitlement programs also played a role. This is not a political judgment: These programs have real social benefits, but the corresponding costs exceed the nation’s ability to fund them. According to the Congressional Budget Office (CBO), Social Security and health care programs such as Medicare and Medicaid account for much of the federal budget. By 2032, they will account for well over 50%, and their costs will only grow as the population ages. 2. Don’t Make the Cure Worse Than the Disease The United States cannot amass debt faster than the US economy grows forever. But it can for quite a while longer. So, defaulting on the debt by refusing to raise the debt limit constitutes an unforced, self-inflicted wound. At the height of the 2008 global financial crisis (GFC), Congress initially voted down the Troubled Asset Relief Program (TARP), which immediately caused the panic to intensify. In a second vote, the measure passed and TARP helped restore faith in the US financial system. No one knows what would have happened if the second attempt had failed, but it would have been disastrous. The same is true for the debt ceiling. The United States has never defaulted on its public debt, so we can’t predict the consequences. But they will be severe. The possibility of a default in the more distant future is a risk that must be addressed, but a voluntarily default would be the financial equivalent of driving a car off a cliff rather than running out of gas. The Disadvantages of a Divided Nation US political divisions are at a cyclical high, but they have been worse. After all, the nation went to war with itself in 1861. Nevertheless, the threat to US financial stability demands a unified effort. The longer unsustainable debt accumulation goes on, the more severe the consequences and the more draconian the countermeasures will ultimately have to be. As unwise as a voluntary default in 2023 might be, it would be equally irresponsible to saddle future generations with debts they cannot afford or that will require dramatic

Our primer on commercial real estate (CRE) investing explored the core components of real estate investing decisions. But what about CRE investing in the current environment? How has the post-pandemic world of renewed geopolitical tensions, resurgent inflation, and rising interest rate pressures reshaped how real estate capital markets operate? How has hawkish monetary policy impacted CRE over the past year? Where is the CRE sector headed, and how can investors respond? Here we explore the historical data as well as various theories and perspectives on CRE’s “new normal.” Above all, we consider what strategies may emerge for investors. The era of “free money” is over, at least for now. The COVID-19 pandemic and the subsequent fiscal and monetary stimulus efforts brought it to a close, if inadvertently, in late 2021 when US Core Consumer Price Index (CPI) growth — CPI excluding food and energy prices — exceeded 3% per annum for the first time in nearly three decades.  Lockdowns and travel restrictions drove the work-from-home (WFH) phenomenon and helped US families stockpile more than $2.6 trillion in excess liquid savings. With overstuffed consumer balance sheets and a slow return to normalcy, discretionary spending increased throughout 2021 and inflation began to rise. Unemployment plunged from its peak-COVID high of 14.7% in April 2020, which paired with global supply chain issues, among other factors, pushed Core CPI above 6.0% — levels last seen in the stagflation era of the late 1970s and early 1980s.  To control inflation, central banks mainly deploy contractionary monetary policy: They raise interest rates. With inflation soaring in 2021 and 2022, the US Federal Reserve hiked rates at the fastest pace in generations.  With interest rates much higher than last year, investors have a new perspective on cap rates for CRE, which generally are at a spread, or premium, to underlying interest or risk-free rates. Moreover, interest rates are a key driver for any leverage associated with a (direct) real estate investment. As such, these pressures will mean reduced deal flow for CRE in the near term and, likely, moderated return potential across most CRE sectors. But that does not mean there will not be excess value in pockets of CRE. The potential cresting of interest rates and the crisis in the mid-size and regional banking sector — which may get worse before it gets better — have remade the CRE opportunity landscape. The Current State of US Interest Rates and Monetary Policy The Federal Open Market Committee (FOMC) raised benchmark interest rates by an aggregate 500 basis points (bps) between March 2022 and 3 May 2023, and rates seem to have a (temporary) reprieve of further increases over the summer. The Fed confirmed as much at its June meeting, holding firm on the rate and signaling its intent to remain cautious and deliberate over the coming months but indicating that further rate hikes could be in the cards before the end of the year if inflation persists. If the most aggressive phase of monetary tightening is behind us, rates may stabilize in the near future. April’s data showed 10 straight months of declining inflation, with the annualized CPI increase falling below 5% for the first time in two years, to 4.4% in May. Core inflation is slowing, at 5.3% year-over-year in May, vs. 5.5% in April and 5.6% year-over-year in March. The surprising June CPI release solidified these trends: CPI reached 3.0% year-over-year and Core inflation 4.8%; both results were lower than the median estimates. All this suggests that Fed hawkishness may be easing. This is welcome news for real estate markets. As interest rates soared in the second half of 2022 and early 2023, cap rates expanded for the first time in years. In the first quarter of 2023 alone, US residential (apartment) and strip center retail nominal cap rates expanded 15 bps, according to Green Street data. Nominal cap rates for office, perhaps the most challenged sector at present, grew by 115 bps. Amid rising interest rates, asset values declined in most CRE sectors — by an aggregate 15% since property prices peaked around March 2022. Rising interest rates affect real estate valuations through cap rate expansion. This, in turn, influences the profitability of an investment — negatively for liquidating investors and potentially positively for acquiring investors. On a go-forward basis, however, lower asset values are not necessarily bad news for real estate operators. With cap rates higher than they were a year ago, there is once again room for “cap rate compression.” That is, expanding cap rates reflect an adjustment in the pricing of risk in real estate markets: Investors now have more opportunities to acquire assets at appealing rates and engineer compelling total returns by exiting at a calmer, more favorable moment in the market at compressed cap rates. Monetary tightening has also created uncertainty in capital markets, which has compromised transaction volume. Buyers and sellers do not know where the bottom of the market is or what the terminal interest rate is and so cannot come together on a price. This is especially true among real estate operators. If rates stabilize, transaction volumes should increase. Institutional investors are waiting on the sidelines with ample capital to deploy. At the institutional level, private equity real estate (PERE) funds held a record $400 billion in “dry powder” as of Q3 2022. In a higher interest rate environment, distressed opportunities should develop. Operators who transacted in the lower-rate regime now face steeper costs of capital due to floating-rate debt, maturing loans that they cannot refinance at anticipated levels given shifts in cap rates/valuation, or untenable interest rate derivative costs. Even with quality assets in quality markets, these operators may have to sell or default on loans. Turmoil in Mid-Sized Banking Several high-profile regional and mid-sized banks have failed in 2023. Silicon Valley Bank (SVB) and Signature Bank both collapsed within days of one another and, respectively, constituted the second and third largest bank failures in US history. A distressed Credit Suisse was acquired by UBS in close cooperation with Swiss