CFA Institute

Not for syndication. This article cannot be republished without the express permission of Business Expert Press (BEP). The following is adapted from the forthcoming Markets in Chaos: A History of Market Crises around the World by Brendan Hughes, CFA. I am concerned about the long-term health of the US dollar along with just about every other fiat currency in the world. Why? Because of the low interest rates, artificially inflated asset valuations, and soaring debt levels that followed the global financial crisis (GFC). How much has monetary policy changed since the GFC? In The Lords of Easy Money: How the Federal Reserve Broke the American Economy, Christopher Leonard observes that between 2007 and 2017 the US Federal Reserve printed more money than was printed over the previous 500 years. And this was before such efforts accelerated following the outbreak of COVID-19 to address weak economic growth and high unemployment. As we have seen, printing more money does not increase prosperity but inevitably makes money less valuable through higher inflation. This grand monetary experiment has undermined the global financial system and necessitates a radical solution. The United States cannot simply grow its way out of its current deficit levels. Higher taxes and budget cuts are among the only remaining tools available to policymakers, and while the former could raise federal income in the short term, it would likely reduce economic growth in the long term. Substantial and sustained budget cuts, meanwhile, are almost always unpopular, and politicians have little incentive to make them. After all, the negative effects of such measures are felt fairly immediately, while running up deficits only stings many years later, usually long after the politicians responsible have left the scene. But if the United States fails to control its deficits, the US dollar may lose its status as the world’s reserve currency. Some nations are already trying to reduce their dependence on the dollar. Reserve currencies rise and fall as part of long-term cycles, and every reserve currency runs the risk of ceasing to be one. For these reasons, I believe we have to return to the gold standard in some form. President Richard Nixon ended the previous gold standard era in 1971 when he eliminated the fixed convertibility between the US dollar and gold and made the dollar a fiat currency. While a country that issues fiat currency is unlikely to ever default on its debts, it can and often will print so much money that the currency becomes worthless. When this happens, the link between paper money and gold or other hard assets is often restored. Today, looming debt restructurings and potential defaults may soon lead to such a global monetary reset. Not only do I advocate for a return to the gold standard; I believe, as Milton Friedman did, that central banks should tie the growth of the money supply to GDP growth. Over the years, Keynesians have noted, correctly, that limits on money supply growth do not always impact the velocity of money. But when the money supply increases well in excess of GDP growth, it does destabilize the financial system. “Where is the understanding of history and the common sense about the quantity of money and credit and the amount of inflation?” — Ray Dalio To be sure, Friedman’s monetarism is not immune to criticism. How to define money supply — M1 vs. M2, for example — has never been clearcut. The rise of the shadow banking system and cryptocurrencies has not made the job any easier. Nevertheless, that money supply growth should mirror economic growth makes intuitive sense. When more money competes for the same goods and services, that money becomes less valuable. There is no benefit to printing massive piles of paper money in excess of GDP growth or incentivizing private banks to do so through fractional reserve banking and government bailouts. Fed chair Jerome Powell may downplay the correlation between money supply growth and inflation, but printing so much money in 2020, long after conditions had stabilized, was a policy mistake. That is why I believe a partial gold standard should be supplemented by tying money supply growth to GDP growth and introducing a full-reserve banking system. In 1933, a group of economists proposed such a full-reserve banking system as part of the so-called Chicago plan. They believed the fractional-reserve banking system still in use today bore responsibility for the Great Depression. But under a full-reserve system, with a 1:1 ratio of loans to reserves, every dollar in loans is backed by a dollar in deposits. A monetary system constructed along these lines would dramatically reduce the potential for extreme boom-and-bust cycles. We may never fully understand COVID-19’s effect on the domestic and global economy or of the aggressive monetary and fiscal measures taken in response. But it will almost certainly be much more difficult for the United States to reduce government debt today than in the post-World War II period. Between 1945 and 1959, the US government slashed its debt-to-GDP ratio by more than half, to roughly 50%, thanks largely to rapid economic growth and a population boom. US GDP increased from $228 billion in 1945 to almost $1.7 trillion in 1975. Today, not even the most bullish scenario anticipates economic growth anywhere near those levels in the years ahead. As for the population, without profound changes to immigration policy, given the low domestic birth rate, the United States will not expand fast enough to fuel the necessary economic growth. To make matters worse, Social Security and Medicare spending constituted 61% of federal spending in 2019 compared with approximately 30% in 1970. The United States has three options: It can raise taxes in the coming years to pay for the national debt and entitlement spending, restructure or default on the debt, or continue to print large sums of money. As I see it, the first option is highly likely. The second is highly unlikely given the country’s status as a fiat currency issuer. That means the third option

“You cannot be an impact investor without considering emerging markets. Investing in Africa presents both financial and impact opportunities.” — Jennifer Kenning, CEO and Co-Founder, Align Impact Investors looking to make a difference and make a profit should consider the fastest-growing continent for technology adoption, natural resource opportunities, and human capital: Africa. The second largest continent by land and population, Africa has abundant untapped natural resources, vast potential for sustainable agriculture, transformative free trade agreements, new policies to improve women’s rights, and soaring digital commerce opportunities. In the quest for strong returns that can also drive positive global change, it cannot be overlooked. Africa has the world’s most rapidly expanding workforce, with over 60% of the population under the age of 25, and forecasters predict that technology and infrastructure improvements will set the continent up for strong growth in the years ahead. Here are eight reasons why you should consider impact investing in Africa: 1. Africa Has Abundant Energy and Natural Resources Africa holds 40% of the world’s gold and 30% of its mineral reserves, including ample supplies of uranium, diamonds, and iron, according to the United Nations Environment Programme (UNEP). Moreover, amid the energy crisis brought on by the Russia-Ukraine conflict, Africa’s vast oil and gas resources are more valuable than ever. For example, Mozambique possesses 150-trillion cubic feet of liquefied natural gas (LNG) in offshore reserves, the equivalent of 24-billion barrels of oil. The Uganda-Tanzania pipeline is also being developed through foreign direct investment (FDI) over the next few years. 2. Africa Holds 60% of the World’s Uncultivated Arable Land Global food demand will increase by 70% by 2050, with demand in Africa growing even faster, according to World Bank forecasts. With so much available arable land, Africa can help meet the challenge. But investment and education are needed to modernize farming practices on the continent. Commercial lending through banks and institutions is costly, so there is an opportunity for impact investors in agricultural start-ups. The “Agriculture in Africa 2021: Focus Report” predicts that improved agricultural operations could spur growth across the continent’s entire economic and financial ecosystem. Coupled with the creation of the African Continental Free Trade Area (AfCFTA), achieving food security for the whole continent is possible as is increasing food exports. Agriculture accounts for 14% of GDP in sub-Saharan Africa and is a major employer. While intra-regional trade in agricultural products is lower in Africa than elsewhere, the AfCFTA may help address this. 3. Africa Could Be a Green Energy Hub Beyond oil and gas resources, Africa has great potential for wind and solar energy generation and can play a vital role in countering climate change. The continent has already begun leveraging renewable energy sources, including hydro, geothermal, and biofuels. However, investment at scale is imperative if African countries are to expand energy access while meeting their climate goals. At the 2022 Sustainable Energy for All Forum in Kigali, Rwanda, Bloomberg Philanthropies announced a new $242 million investment to speed up clean-energy adoption in 10 developing countries, including Kenya, Mozambique, Nigeria, and South Africa. Reducing dependence on fossil fuels and foreign sources are among the main rationales behind promoting alternative power sources. But on a human scale, these solutions can help extend the power grid to areas where it was previously cost-prohibitive. That increased connectivity will lead to greater skills, employment, and GDP growth. Indeed, Africa has essentially unlimited green energy potential. The International Renewable Energy Agency (IRENA) estimates the continent’s capacity could reach 310 GW by 2030. This would not only satisfy local power needs but also position Africa as a global leader in clean energy production, setting it up for investments in related infrastructure, climate-smart agriculture, and sustainable natural resources management. The sustainability challenge is particularly acute for Africa. As Jennifer Kenning of Align Impact observed in reference to a recent Intergovernmental Panel on Climate Change (IPCC) report: “While Africa is one of the lowest contributors to greenhouse gas emissions causing climate change, they are and will continue to experience widespread loss and damages due to climate change including biodiversity loss, water shortages, reduced food production, loss of lives and reduced economic growth.” 4. The African Continental Free Trade Area (AfCFTA) Will Revolutionize Trade AfCFTA will cover a market of 1.2 billion people with a gross domestic product (GDP) of $2.5 trillion making it the world’s largest free trade area by participating countries. As of June 2021, 54 African Union members have signed on. These nations can expect to reap the benefits of streamlined cross-border financial transactions, trade expansion, greater transparency, and increased collaboration. AfCFTA participants estimate the agreement will lift 30 million people out of extreme poverty by 2035. Thanks to global ESG standards, businesses will have fewer restrictions on the sale and purchase of goods. Import tariffs will be eliminated on 97% of goods traded on the continent. AfCFTA member countries could act as a single market and harness that influence to grow exports and expand trade. 5. Investing Contributes to Social Impact and Women’s Rights Closing the gender income gap and opening new markets through AfCFTA will benefit women and investors alike. According to the Economic Commission for Africa, women account for around 70% of informal cross-border traders in Africa. Historically, they have been vulnerable to harassment, violence, theft, and imprisonment. AfCFTA will improve conditions for solo women business owners who previously lacked established trade channels or protections. Young women participate in a Girl Power USA forum in Bushenyi, Uganda.Courtesy of Girl Power Talk 6. New Markets and Increased Trade Ensures Diversification Skilled investors know the importance of diversifying an investment portfolio. AfCFTA will spur export diversification, accelerate growth, attract FDI, and increase employment opportunities and income. Manufacturing will be a big component of the estimated $560 billion increase in African exports. Exports within the continent could also increase by 81%. According to the Mo Ibrahim Foundation, consumer and business spending could reach $6.7 trillion by 2030, making African countries more competitive both regionally and globally. While the continent suffers from a skills gap and a lack of

Stock investors loved Alan Greenspan because the policies he pursued during his tenure as chair of the US Federal Reserve benefited the equity markets. At least that was the conventional wisdom. But did the markets reflect this narrative on days when Greenspan testified before Congress? Did they tend to go up as we would expect, or did their performance contradict the narrative? And how did the markets respond when Jerome Powell and other Fed chairs testified? What does their behavior reveal about how they assessed each Fed chair? To answer these questions, we pulled S&P 500 and MSCI market and asset class data for all dates on which the last five Fed chairs testified before Congress and compared the results with both daily average returns and average return volatility. To better isolate market sentiment around each Fed chair, we did not include Fed rate announcement days in our analysis. The Fed had already communicated its rate decisions to the public prior to each Fed chair’s congressional appearance, and the market had presumably taken the decision — to hike, hold, or reduce rates — into account. So, how did the markets respond to the testimony of each Fed chair? Were there any standouts or surprises? As it turns out, Janet Yellen generated the most positive returns on the days when she testified relative to the four other Fed chiefs. On average, the S&P 500 rose 0.20% when Yellen spoke and only 0.08% when Greenspan testified. On the other end of the spectrum, days when Ben Bernanke or Powell testified are associated with more negative stock market performance. The S&P 500 returned –0.05% on average on days when Powell or Bernanke appeared before Congress. Of course, Bernanke helmed the Fed during the global financial crisis (GFC) and Powell during a period of resurgent inflation. So, the bearishness they evoked may not be especially surprising. Fed Chair Congressional Testimony Average Returns: One-Day Window (%) Paul Volcker Alan Greenspan Ben Bernanke Janet Yellen JeromePowell S&P 500 –0.03 0.08 –0.05 0.20 –0.05 Small-CapEquity 0.04 0.06 –0.15 0.07 0.00 GrowthEquity –0.03 -0.02 –0.01 0.08 –0.11 ValueEquity 0.00 0.03 –0.08 0.28 0.06 InternationalEquity 0.10 –0.02 0.01 0.05 –0.23 Total BondIndex 0.07 0.03 0.09 –0.05 0.01 High-YieldDebt 0.06 0.04 0.02 0.09 0.00 Short-TermDebt 0.02 0.02 0.01 –0.01 -0.01 Sources: S&P 500 and MSCI data We see similar results play out across small-cap and international equities as well as value and growth, with Yellen testimony days yielding better returns than Greenspan’s. We repeated our tests over a three-day window around the Fed chairs’ congressional testimony and again generated qualitatively similar outcomes. Bonds told a distinctly different story, however. While equities outperformed when Yellen testified, fixed income went in the opposite direction, with the total bond index returning –0.05% on days when Yellen appeared before Congress. Volatility was another datapoint we explored, with Bernanke testimony days displaying the most volatility overall. Standard Deviation of Returns around Fed Chair Testimony Days PaulVolcker AlanGreenspan BenBernanke JanetYellen JeromePowell S&P 500 0.88 0.93 1.40 0.52 0.77 Small-CapEquity 0.57 0.86 1.72 0.67 0.91 GrowthEquity 0.35 1.17 1.30 0.82 0.85 ValueEquity 0.93 0.93 1.56 0.55 0.83 InternationalEquity 0.55 0.84 1.37 0.81 0.97 Total BondIndex 0.16 0.29 0.27 0.25 0.17 High-YieldDebt 0.18 0.23 0.35 0.11 0.12 Short-TermDebt 0.08 0.08 0.04 0.04 0.03 Sources: S&P 500 and MSCI data Of all the Fed chairs, Yellen generated the most positive stock market reactions and the least volatility over the past 50 years, even as bond investors tended to respond negatively to her testimony. Otherwise, both Powell’s and Paul Volcker’s tenures featured a number of interest rate hikes in response to rising inflation. The weaker performance of equities on their testimony days may reflect how the markets came to associate them both with higher rates. 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. Image courtesy of the US Federal Reserve Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

The eye of a hurricane is a deceivingly perilous place. Those lucky enough to enter it unscathed may enjoy a well-deserved respite, but the blue skies and calm winds also create a false sense of security and encourage complacency. Some people may even be convinced that the storm has passed. The truth, however, is that the eye offers only a brief intermission, and the worst is yet to come. The US Federal Reserve raised the federal funds rate by 75 basis points on 27 July 2022. Many investors had feared a more aggressive 100-basis-point increase, so the relief was palpable. The very next day, the Bureau of Economic Analysis (BEA) issued its advanced estimate of second quarter GDP growth. The negative Q2 reading of 0.9% followed a Q1 decline of 1.6% and prompted a needless debate as to whether the US economy was in recession. The combination of a less-than-feared interest rate hike and two consecutive quarters of negative economic growth sparked a strong rally in US equities and other risk assets. Implicit in this rally was the hope that the Fed may soon ease its monetary tightening and that the much-dreaded recession was already in the rearview mirror. 12-Month Trailing US Inflation and Cumulative Federal Rate Hikes: Post-World War I/Great Influenza and Post-COVID-19 Sources: Federal Reserve Bank of Minneapolis, US Bureau of Labor Statistics. Indeed, as July gave way to August, a surprisingly strong jobs report and lower-than-expected CPI numbers made investors even more bullish. One can hardly blame them for basking in the sunny skies and losing sight of the second hurricane wall that potentially looms on the horizon. While such optimism may be tempting, it is inconsistent with the lessons of financial history — especially the US experience in the years after World War I and the years preceding the Great Inflation. The Fed is now battling inflation, not a recession, and it is too early to declare victory. The greatest blunder in Fed history was letting inflation fester for too long in the late 1960s. The Fed’s errors allowed inflation expectations to become entrenched, and the US economy paid a steep price in the form of more than a decade of stagflation. The Fed under Jerome Powell is unlikely to repeat this error, and taming inflation decisively will likely require more pain. Beware the Ides of October So when will the second wall of the monetary hurricane hit? It is impossible to tell. The Fed may even defy the odds and orchestrate a soft landing. But if the storm comes, beware the Ides of October 2022. Not only will the Fed’s tightening cycle be in its late stages, but October is a notorious month for financial panics. The 19th-century agricultural financing cycle first gave rise to periodic October panics, but even after the US transitioned to an industrial and consumer economy, the instinctive fear of October produced the occasional self-fulfilling prophecy. Financial history suggests that more market volatility and economic pain are on tap before the Fed wins its battle with inflation. This does not mean, however, that investors should embrace tactical asset allocation — that would be speculation rather than investment. Rather, they must simply maintain their situational awareness, remain committed to their long-term asset allocation targets, rebalance to those targets as appropriate, and continue to steel their nerves for more volatility and price declines to come. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images/Stocktrek Images 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

Despite posting a 9.6% return in fiscal 2024, large US college and university endowments once again fell short of market benchmarks — by a staggering 9.1 percentage points. The culprit? A combination of return smoothing and persistent structural underperformance. As the data shows, over the long term, endowments heavily invested in alternatives are falling well behind low-cost indexed portfolios. This post breaks down why and what the numbers really reveal about endowment strategy since the global financial crisis (GFC). The Data Is in The National Association of College and University Business Officers (NACUBO) recently released its annual survey of endowment performance. Funds with greater than $1 billion in assets had a return of 9.6% for the fiscal year ended June 30, 2024. A Market Index, the construction of which is based on US endowment funds’ typical market exposures and risk (standard deviation of return), returned 18.7%. That endowments underperformed their market index by a whopping 9.1 percentage points is a result that needs interpretation. Vexing Valuations Fiscal 2024 was the third consecutive year in which endowment returns were visibly distorted by return smoothing. Return smoothing occurs when the accounting value of assets is out of sync with the market. Exhibit 1 illustrates the effect. The endowment returns for fiscal years 2022, 2023, and 2024 were greatly attenuated relative to the Market Index. The US stock and bond markets declined sharply in the final quarter of fiscal year 2022. Private asset net asset values (NAVs) used in valuing institutional funds at year-end 2022 did not reflect the decline in equity values. This was caused by the practice of using NAVs that lag by one or more quarters in portfolio valuations. The equity market rose sharply the following year, and once again marks for private assets lagged as NAVs began to reflect the earlier downturn. This pattern repeated itself in 2024. The overall effect was to dampen the reported loss for 2022 and tamp down gains in 2023 and 2024. (See shaded area of Exhibit 1.) The pattern of distortion appears to have largely run its course in 2024. Exhibit 1: Performance of Endowments with Greater than $1 Billion in Assets. Dismal Long-Term Results Notably, the long-term performance of large endowments is unaffected by recent valuation issues. The annualized excess return of the endowment composite is -2.4% per year, in line with past reporting by yours truly. Exhibit 2 shows the cumulative effect of underperforming by that margin over the 16 years since the GFC. It compares the cumulative value of the composite to that of the Market Index. The typical endowment is now worth 70% of what it would have been worth had it been invested in a comparable index fund. At this rate of underperformance, in 12 to 15 years the endowments will be worth half what they would have been worth had they indexed. Exhibit 2 also illustrates the impact that return smoothing had on results for the final three years — an apparent sharp performance gain in 2022 resulting from return smoothing, followed by two years of reckoning. Exhibit 2: Cumulative Endowment Wealth Relative to Market Index. Parsing Returns I examine the performance of five NACUBO endowment-asset-size cohorts (Figure 3). These are fund groupings that range from less than $50 million in assets to more than $1 billion. Stock-bond mix explains a lot. Exhibit 3 shows that large funds invest more heavily in equities and earn higher total returns, accordingly. Ninety to 99% of the variation in total return is associated with the effective stock-bond allocation. There is nothing new here. (See, for example, Brinson et al., 1986). Excess return is the difference between total return and a market index based on the respective stock-bond allocations, as illustrated in Exhibit 1. All the excess returns are negative. Exhibit 3: Parsing Returns (fiscal years 2009 to 2024).         Cohort     Effective Stock-Bond Allocation     Annualized Total Return   Percent of Total Return Variance Explained by Asset Allocation (R2)       Excess Return 1  <$50 million 68-32% 6.0% 99% -1.2% 2  $51 – 100 71-29 5.8 99 -1.4 3  $101 – 500 76-24 6.0 97 -1.9 4  $501 – 1000 80-20 6.5 94 -2.3 5  >$1000 million 83-17 6.9 90 -2.4 Alts Explain the Rest Exhibit 4 shows the relationship of excess returns and the average (over time) allocation to alts for the five NACUBO endowment-asset-size cohorts. The relationship between them is inverse. For each percentage point increase in alts exposure, there is a corresponding decrease of 28 basis points in excess return. The intercept is -0.9%. Ninety-two percent of the variation in excess return (R2) is associated with the alts exposure. This tells us that, of the small percentage of return variation that goes unexplained by traditional asset allocation, 92% is explained by exposure to alts. Exhibit 4: Relationship of Excess Returns and Exposure to Alts. Why have alts had such a perverse influence on performance? The answer is high cost. I estimate the annual cost incurred by Cohort #5 funds has averaged 2.0% to 2.5% of asset value, the vast majority of which is attributable to alts. A Simple Story If you can tolerate the risk, allocating to equities pays off over time. Allocating to alts, however, has been a losing proposition since the GFC. And the more you own, the worse you do. It is a pretty simple story, really. source

For more on the crypto and blockchain phenomena, read Valuation of Cryptoassets: A Guide for Investment Professionals by Urav Soni and Rhodri Preece, CFA, from CFA Institute Research and Policy Center. A few foundational microeconomic assumptions and a discounted cash flow (DCF) framework can help inform crypto buy and sell decisions. “Crypto’s Unanswered Question: At What Price?” by Franklin J. Parker, CFA, highlights a conversation I often have with other charterholders, investors, and clients. These discussions have led to both valuable thought exercises and rousing debates. I am not a crypto expert and certainly not a crypto “bro.” I have no strong opinion on whether cryptoassets are undervalued or overvalued, the future of money and commerce or a fad that we’ll all look back on amusingly. Nevertheless, I believe crypto investors can employ a logical valuation framework by which they can make reasonable and informed crypto investment decisions. By applying a discounted cash flow (DCF) model, relying on microeconomic principles as inputs, and using gold and other commodities as guides, we can define a range of prices at which we could expect a reasonable, risk-adjusted rate of return over a given time horizon for a particular cryptoasset. Because cryptoasset prices are directly observable, using a DCF valuation framework, we only need to estimate a future price or range of future prices for a particular cryptoasset, which we can discount back to the present at a required cost of capital. The net present value of our expected future price would equal our estimated intrinsic value today. By comparing that to spot prices, we can make our buy and sell decisions. Admittedly, some elements of this future price estimation process involve a high degree of uncertainty, but others can be reasonably estimated with a modest amount of effort. For example, we know that, over the long run, profit-maximizing businesses will only produce if the marginal revenue exceeds the marginal cost to produce. As such, the marginal cost of mining a crypto coin sets a floor price around which supply will fluctuate. In the case of cryptoassets, the variable costs are reasonably simple to assess — computing costs / energy consumption, taxes, and transaction fees — and because computers can be turned on and off quickly, mining activities can be adjusted quickly depending on price fluctuations. In fact, we can observe this quick response function at work when we juxtapose hash rates over spot prices or estimated mining profitability. Accounting for pre-ordained “halvings” in the mining algorithm, estimating future variable costs associated with cryptoassets, is relatively simple and straightforward. Moreover, crypto miners presumably require a reasonable return on their physical capital investment over time, so we must also include an estimate for the future cost of hardware as well as other capital and fixed costs. With estimates for variable costs, fixed costs, and an assumed required cost of capital for the miners, we can calculate the range of prices at which a cryptoasset will be mined, thus setting the price floor at which we’d expect it to trade. Estimating a cryptoasset’s price ceiling, or the degree to which the actual price could exceed the price floor, is more challenging because it depends on demand, which entails a large degree of uncertainty. But all investments involve uncertainty and investors employ various logical approaches to work through it. For example, we can assess the various demand drivers that influence cryptoasset owners by evaluating it as money. Like gold, cryptoassets are generally divisible into smaller units, countable and fungible (unit of account), used by some to hedge against inflation (store of value), and used to buy and sell goods (medium of exchange). As such, cryptoassets generally meet the criteria for the definition of money, which allows us to measure a cryptocurrency’s demand based on its value as money and more specifically, its utility in these use cases. As a store of value, a cryptoasset may increase in price as confidence in fiat currency collapses or fears of inflation or hyperinflation spike. As a medium of exchange, a cryptoasset may rise in value the more it is used in domestic and international commerce as a method of buying and selling goods and services. We could incorporate a demand component based on the attractiveness of its anonymity — which has utility for both legal and illicit purposes — and we could even incorporate our expectations about how central banks might use cryptoassets to diversify their holdings in the future. A cryptoasset’s value across these various use cases would influence demand, and with it, the price of the cryptoasset itself. Presumably, the sum of a cryptoasset’s utility exceeds its cost and cryptoassets would continue to exist. The point is that, as with all investments, some assumptions must be made about future conditions, and as with gold, some of the key assumptions involve potential demand. Unlike gold, which has a long history, and, therefore, offers some sense for what demand will reasonably look like from various users, cryptoassets lack a long history of use and demand; its story as money is still being written. Nevertheless, this is where the individual assumptions of the investor come into play: their own personal risk tolerance, their investment goals, objectives, and required rate of return, and, ultimately, their own personal determination about the potential risk and potential return, and whether, given their expectations for risk and return, a cryptoasset is an attractive investment. We may all argue about the inputs and assumptions that go into the framework, but that is, after all, exactly what makes financial markets work; the interaction of millions of investors applying their own assumptions and expectations to various investment opportunities using a logical framework in order to avoid speculation. Which brings me to my answer to Parker’s unanswered question: “At What Price?” I don’t know at what price, but I know how someone who wants to answer that question could answer it for themselves. For more on this topic, check out Valuation of Cryptoassets: A Guide for Investment Professionals by Urav Soni and Rhodri

How is risk defined in portfolio optimization objective functions? Usually with a volatility metric, and often one that places a particular emphasis on downside risk, or losing money. But that only describes one aspect of risk. It doesn’t capture the entire distribution of outcomes investors could experience. For example, not owning an asset or investment that subsequently outperforms could trigger an emotional response in an investor — regret, say — that resembles their reaction to more traditional definitions of risk. That’s why to understand risk for portfolio optimization purposes, we need to consider regret. Among different investors, the performance of speculative assets such as cryptocurrencies could potentially evoke different emotional responses. Since I don’t have very favorable return expectations around cryptocurrencies and consider myself relatively rational, if the price of bitcoin increases to $1 million, I wouldn’t sweat it. But another investor with similarly unfavorable bitcoin return expectations could have a much more adverse response. Out of fear of missing out on future bitcoin price increases, they might even abandon a diversified portfolio in whole or in part to avoid such pain. Such divergent reactions to bitcoin price movements suggest that allocations should vary based on the investor. Yet if we apply more traditional portfolio optimization functions, the bitcoin allocation would be identical — and likely zero — for the other investor and me, assuming relatively unfavorable return expectations. Considering regret means moving beyond the pure math of variance and other metrics. It means attempting to incorporate the potential emotional response to a given outcome. From tech to real estate to tulips, investors have succumbed to greed and regret in countless bubbles throughout the years. That’s why a small allocation to a “bad asset” could be worthwhile if it reduces the probability that an investor might abandon a prudent portfolio to invest in that bad asset should it start doing well. I introduce an objective function that explicitly incorporates regret into a portfolio optimization routine in new research for the Journal of Portfolio Management. More specifically, the function treats regret as a parameter distinct from risk aversion, or downside risk — such as returns below 0% or some other target return — by comparing the portfolio’s return against the performance of one or more regret benchmarks, each with a potentially different regret aversion level. The model requires no assumptions around return distributions for assets, or normality, so it can incorporate lotteries and other assets with very non-normal payoffs. By running a series of portfolio optimizations using a portfolio of individual securities, I find that considering regret can materially influence allocation decisions. Risk levels — defined as downside risk — are likely to increase when regret is taken into account, especially for more risk-averse investors. Why? Because the assets that inspire the most regret tend to be more speculative in nature. Investors who are more risk tolerant will likely achieve lower returns, with higher downside risk, assuming the risk asset is less efficient. More risk-averse investors, however, could generate higher returns, albeit with significantly more downside risk. Additionally, allocations to the regret asset could increase in tandem with its assumed volatility, which is contrary to traditional portfolio theory. What are the implications of this research for different investors? For one thing, assets that are only mildly less efficient within a larger portfolio but potentially more likely to cause regret could receive higher allocations depending on expected returns and covariances. These findings may also influence how multi-asset funds are structured, particularly around the potential benefits from explicitly providing investors with information around a multi-asset portfolio’s distinct exposures versus a single fund, say a target-date fund. Of course, because some clients may experience regret does not mean that financial advisers and asset managers should start allocating to inefficient assets. Rather, we should provide an approach that helps build portfolios that can explicitly consider regret within the context of a total portfolio, given each investor’s preferences. People are not utility maximizing robots, or “homo economicus.” We need to construct portfolios and solutions that reflect this. That way we can help investors achieve better outcomes across a variety of potential risk definitions. For more from David Blanchett, PhD, CFA, CPA, don’t miss “Redefining the Optimal Retirement Income Strategy,” from the Financial Analysts Journal. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images / jacoblund 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

Editor’s Note: This is the first in a series of articles that challenge the conventional wisdom that stocks always outperform bonds over the long term and that a negative correlation between bonds and stocks leads to effective diversification. In it, Edward McQuarrie draws from his research analyzing US stock and bond records dating back to 1792. CFA Institute Research and Policy Center recently hosted a panel discussion comprising McQuarrie, Rob Arnott, Elroy Dimson, Roger Ibbotson, and Jeremy Siegel. Laurence B. Siegel moderated. The webinar unveils divergent views on the equity risk premium and McQuarrie’s thesis. Subscribe to Research and Policy Center, and you will be notified when the video airs. Edward McQuarrie: When I tell acquaintances that I’ve put together the historical record of stock and bond performance back to 1792, the first reaction is generally, “I didn’t know there were stocks and bonds 200 years ago!” They aren’t familiar with Jeremy Siegel’s book, Stocks for the Long Run, which is now in its 6th edition, where he presents a 200-year series of stock and bond returns that he first compiled 30 years ago.  The book conveys a simple message with compelling support from that history. That is, stocks have always made buy-and-hold investors wealthy, and the wealth accumulation possible from stocks far exceeds that of any alternative, such as bonds. My new research, “Stocks for the Long Run? Sometimes Yes, Sometimes No,” which was published in the Financial Analysts Journal, suggests otherwise. I will begin to explain those findings in this article. But first, a reminder of the theoretical support that undergirds Siegel’s “Stocks for the Long Run” thesis. Risk and Return Bonds, especially government bonds, are a “fixed income” asset. Investors get the coupon and the return of principal at maturity. Nothing less, but also nothing more. The risk is minimal, and the promised return is accordingly small, because it is largely assured. Stocks are risk assets. No guarantees. Your investment could go to zero. Notably, investors are risk averse. No utility maximizer would put a penny into stocks without a promise of upside, i.e., the potential for a strong return far enough in excess of fixed income returns to compensate for the much greater risk of investing in stocks. Therefore, over any lengthy interval, after short-term fluctuations shake out, stocks can be expected to outperform bonds, exactly as Siegel’s history shows. The Conundrum If stocks will assuredly outperform bonds over intervals of, say, 20 years or more, where is the risk? And if stocks aren’t risky over long intervals, why should their returns exceed the returns on bonds that are not risky? The logic behind “Stocks for the Long Run” blows up. Theory says, “Expected return is a positive function of risk.” But the Siegel history shows no risk for holding stocks over longer intervals. The stock investor always wins. The Resolution I call it a conundrum, not a paradox, because it is easily resolved. All that is needed is a demonstration that sometimes, regardless of the holding period, stocks do blow up, leading to underperformance in either absolute terms or relative to bonds. Stocks can win most of the time, over intervals of any length, if they lose some of the time, over intervals of any length. Those occasional shortfalls are sufficient to restore risk. And risk is the key to any reasonable expectation of earning an excess return over a government bond benchmark. I found those shortfalls in the historical record I compiled. The Updated Historical Record My Financial Analysts Journal article contains a summary of how I compiled the historical data. The online appendix goes into more detail and includes the raw data if you’d like to play around with it. Here is a chart depicting the updated historical record: What do you see? For almost 150 years, stocks and bonds produced about the same wealth. It was a horse race, with the lead swinging back and forth. Stocks would occasionally leap ahead, as in the 1920s, but would also occasionally fall behind, as in the decades before the Civil War. Net, the picture is one of parity performance until World War II. Then, during and after the war, the wealth lines dramatically diverge. Over the four decades from 1942 through 1981, stocks piled up an enormous lead over bonds. The stock investor would have turned $10,000 into $136,900 real dollars. The bond investor would have lost money, turning $10,000 into a real $4,060. Think about that for a moment: You would have lost money in “safe” government bonds. After the war, bonds proved to be a risk asset. Again, what happened after World War II was not that stocks performed extraordinarily well. If you mentally draw a straight line from the beginning of the stock line in 1792 to its end in 2019 (this chart stops before the pandemic), there is not much deviation in the second panel. There was a slight upward displacement through about 1966, but the inflation of the 1970s and the bear market of 1973 to 1974 brought stocks back on trend. Rather, bonds performed extraordinarily poorly during this period. Nowhere else in the chart do you see a multi-decade period of ever-declining bond wealth. The decades through WW I come closest, but the decline was abrupt and abbreviated — nothing like the multi-decade swoon that followed the second world war. The third panel represents my innovation in chart design. In a conventional multi-century chart, once wealth lines have diverged, as in the middle panel, the human eye cannot detect if parity performance has resumed. In a Siegel-style chart, (see p. 28 in the 6th edition of “Stocks for the Long Run” or p. 82 in the 5th edition), what you see is a gap in stock and bond performance that appears to continue to the present day. To see the return to parity performance that did occur after 1981, it is necessary to reset the bond wealth line equal to the stock line as of 1981. Once that is

Asset owners have dramatically increased their allocations to private markets over the past two decades, driven largely by a mistaken belief that private debt and equity deliver returns that are orders of magnitude above those of public markets. What makes most investors believe that private capital funds are such clear outperformers? The use of since-inception internal rate of return (IRR) as the industry’s preferred performance metric and the media’s coverage of the sector’s performance are to blame. The myth of the Yale model — a belief of superior returns stemming from a heavy allocation to private equity funds — is based solely on a since-inception IRR. While there is no ideal substitute for since-inception IRR, investors — especially retail investors — should understand that IRR is not equivalent to a rate of return on investment (ROI). This is the first in a three-part series in which I frame the problem, offer techniques for critical evaluation of fund performance reports, and propose alternative approaches to metrics and benchmarks. The call to action is for regulators or the industry, through self-regulation, to ban the use of since-inception IRR in favor of horizon IRRs. This simple action would eliminate many of the most misleading figures that are presented to investors and would facilitate comparisons. Figure 1 illustrates the migration of institutional assets to private capital over the past two decades. Recently, high-net-worth individuals and more broadly retail investors have joined the trend. The resulting growth in assets under management (AUM) might be unprecedented in the history of financial markets. Private capital fund AUM grew fifteen-fold — 14% per annum over the last 25 years.[1] Figure 1: Evolution of AUM of all private capital funds. Why did capital fly out of traditional asset classes and into private capital funds? The main cause seems to be a strong belief in superior returns. But here’s a reality check on performance. Below are performance metrics, using one of the largest databases available — the MSCI (private-i) — and including all 12,306 private capital funds with a total of $10.5 trillion in AUM, over the entire history of the database. Median IRR of 9.1% Pooled IRR of 12.4% 1.52 total value to paid-in capital (TVPI): TPVI is the sum of distributed and current valuation, divided by the sum invested. 1.05 Kaplan-Schoar Public Market Equivalent (KS-PME): KS-PME is the ratio of present value of capital distributed and current valuation, by present value of capital invested. A score of 1.05 indicates a slight outperformance over the benchmark S&P 500 Index and 1.4% per annum of direct alpha (annualized outperformance over that benchmark). The Source of the Belief: Evidence from News Coverage and Practitioner Publications These performance figures are good, but not spectacular when compared to long-term US stock market returns. According to data on Ken French’s data library, the US stock-market has averaged 12% per annum over nearly 100 years from 1927 and 2023.[2] Most importantly, the returns do not seem commensurate with the spectacular growth in private market AUM. Thus, the puzzle: What makes most investors believe that private capital funds are such clear outperformers? It would be interesting to conduct a survey among both retail and institutional investors to ask for the source of their belief. However, it is difficult to obtain many responses to a survey of this type and to extract what really drives a given belief. An alternative route is to collect information online, mostly from the media. This is the approach I take. While it has its own limitations and is necessarily imprecise, it can nonetheless give a sense of how people convey their beliefs. Exhibits 1 to 9 show some potentially influential articles and statistics. They are spread over time, starting in 2002 (Exhibit 1) and ending in 2024 (Exhibit 9). Exhibit 1 is an extract from a newspaper article covering the fact that a first-time fund was going to be the largest fund ever raised in Europe at the time. Such a situation is rather unusual as funds tend to start small and grow over time. There is, however, no such thing as a pure first-time fund, and the person raising the money had executed nine deals before raising that first-time fund. The article mentions two performance metrics, one is spectacular (62% per annum), the other one not so spectacular (£2.1 per £1 invested gross of fees). Given that this track record led to the largest fund ever raised at the time (2002), it is possible that investors reacted to the 62% annual figure. Sixty-two percent feels extraordinary indeed. In Exhibit 2, Bloomberg shares the Figure 1 from a widely distributed article, “Public Value, a Primer in Private Equity,” first published in 2005 by the Private Equity Industry Association. This figure compares an investment in the S&P 500 to one in top quartile private equity funds from 1980 to 2005. The S&P 500 delivered 12.3% per annum but the top quartile of private equity firms delivered 39% per annum. A 39% return for one quarter of all private equity funds is extraordinary indeed. Exhibit 3 is an extract from an article by The Economist, which wanted to explain the sharp increase in AUM of private equity in 2011. The Economist points to the poster child for private equity investing: the Yale Endowment track record. The article says that the university’s private-equity assets have produced an annualized return of 30.4% since inception. That investment program was launched in 1987; hence Yale Endowment obtained a 30.4% annual return over a 25-year period. This is certainly extraordinary. Exhibit 4 shows the investment memo of a large public pension fund, Pennsylvania’s Public School Employees’ Retirement System (PSERS). The investment committee recommends investing in Apax VII, and the main argument appears to be a gross return of 51% and a 32% net return. The memo states that this performance places Apax in the top decile of private equity firms. No other performance metrics are mentioned. Once again, these numbers appear extraordinary. This fund (Apax VII) closed

Over the past two decades, investors have poured capital into private assets, drawn by the promise of higher returns than public markets. But as Ludovic Phalippou highlights in “The Tyranny of IRR,” many investors are beginning to question whether private equity (PE) returns truly live up to their internal rate of return (IRR) figures. A key reason for the mismatch lies in partial investment. Unlike public assets, PE funds call capital gradually and return it in stages, meaning that a large portion of the committed capital may sit idle for years. This reduces the investor’s gain, even as IRR remains high. IRR compounds the problem by only considering capital deployed by the fund manager, not the full amount contributed by the investor. As a result, it overstates performance and hides the drag of unused capital. To understand what investors truly earn, we need a metric that captures this dilution. Enter the capital deployment factor (CDF) — a simple yet powerful tool that measures how much of the paid-in capital was put to work. It reveals not just how much was used, but also how much gain was lost due to partial investment. The CDF quantifies the impact of partial investment by showing what portion of paid-in capital was actually used to generate returns. Because gain is proportional to the CDF, it also indicates how much potential return was forfeited due to idle capital. What does the CDF reveal about the impact of partial investment on real PE funds? It shows that it is very significant, as the CDF of PE funds rarely exceeds 60% over their lifetime and typically falls to between 15% and 30% at the time of liquidation. A side effect of partial investment is that IRR becomes unreliable for comparing performance: Funds with the same IRR but different capital deployment levels can produce very different gains from the same capital paid in. By contrast, the CDF allows investors to calculate the IRR a fund would need to match the gain of another fund or a liquid asset for the same capital outlay. Capital Deployment Factor The CDF shows the fraction of the amount paid in by the investor that was deployed by the PE fund manager. It can be calculated at any time knowing the fund’s IRR, TVPI and duration. The TVPI is the total value to paid-in indicator at time t, IRR is the internal rate of return since inception expressed on an annualized basis, and DUR the number of years elapsed from inception to time t. For example, a PE fund with an IRR = 9,1% per annum and a TVPI = 1,52X, after 12 years: What does this CDF figure mean? It means that over the 12-year period, only 28.2% of the capital paid in by the investor was used by the fund manager to generate the gain. In other words, just over one dollar in four was put to use to produce wealth. The IRR and TVPI figures above were compiled by Phalippou from a vast and reputable PE fund database. IRR = 9.1% per annum representing the median IRR for PE funds in the database, and TVPI = 1.52x, their average TVPI. The duration reflects the average 12-year life of a PE fund. The CDF = 28.2% is thus broadly representative of the median PE fund at its date of liquidation. How does the CDF affect the investor? The impact of partial investment is considerable, since the gain is reduced in proportion to the CDF, as shown by the gain equation: PAIDINt is the total amount the investor paid in up to time t and Gaint, the gain at time t. Thus, the median PE fund sees its gain reduced by a factor of 0.282 owing to partial investment. What is the CDF’s typical range for PE funds?  It varies throughout the fund’s life. We found it rarely exceeds 60% during its lifetime and falls somewhere between 15% and 30% at liquidation. Venture capital funds and primary funds of funds tend to have higher CDFs than buyout funds, as illustrated in Figure 1. Figure 1. Who controls the CDF? The CDF is dictated by the PE fund manager, since the manager alone decides on the timing of flows. The CDF increases if the manager calls the capital earlier. The CDF also increases if payments are deferred. If the full amount is called in at the beginning and both capital and gain are repaid at the end of the measurement period, the CDF is equal to 100%. Comparing Returns Two funds are equivalent in terms of performance when they have generated the same gain from the same amount paid in. This formula expresses this equivalence criterion by giving the IRR that fund A must have if it is to generate the same gain as fund B out of the same amount paid in. Let’s look at an example: Fund(A): DUR = 12 years; CDF = 20.0%; IRR = ?. Fund(B): DUR = 12 years; CDF = 28,2%; IRR = 9,1% per year. What IRR should fund A have for its performance to be equivalent to that of fund B? Thus, fund A must have an IRR = 11.26% per annum for its performance to be equivalent to that of fund B, which has an IRR = 9.1%. The reason is fund A’s manager has used fewer of the resources at his disposal than fund B’s manager, which is reflected in their respective CDFs. If fund A has an IRR greater than 11.26%, it is considered to have outperformed fund B. Let’s now assume that fund C has a CDF = 100% and the same duration as fund B. For fund C to have equivalent performance to fund B, its IRR could be much lower at: A CDF = 100% implies that the amount paid in remained fully invested throughout the 12-year period, with no interim cash flows, the capital and gain being recovered by the investor at the end of the period. This would