US exceptionalism provided the same explanation for the outperformance of US stocks in the 1990s. However, that regime changed. From 2000-2007, while the S&P 500 Index returned just 1.9% per annum (underperforming riskless one-month Treasury bills by 1.3% per annum), the MSCI EAFE Index returned 5.6% per annum, and the MSCI Emerging Markets Index returned 15.3% per annum.
The listing domicile explained about 50% of the valuation gap. In other words, US-listed stocks are substantially more expensive than internationally listed stocks for no reason other than the place of listing.
NAV timing investors could potentially create trading strategies which would systematically transfer wealth from buy-and-hold investors to themselves.
While the media headlines are preaching doom, the fundamentals are telling a very different story—credit spreads have widened, and EBITDA multiples are the lowest they have been in a decade. The bottom line is that for investors able to accept its limited liquidity, private, senior, secured and sponsored by private equity direct lending continues to be a compelling component of a diversified portfolio deliver what has always attracted investors: high current income, resilience through market cycles, and a disciplined approach to risk management. We are far from a bubble.
In 2024 investors were provided with nine lessons. Many of them are repeats from prior years. Unfortunately, too many investors fail to learn them—they keep making the same errors.
What matters is not the expectation of future growth, but the deviation between projected growth and realized growth, which, by definition is a surprise, and, thus, is not forecastable.
Because AI systems can produce hundreds of seemingly coherent theoretical explanations for mined empirical results, investors need to establish high hurdles before allocating to anomaly-based strategies.
Given the similar net returns that UMM and LMM loans have delivered, allocators should consider diversifying across borrower size cohorts. Since LLM loans are somewhat riskier, careful due diligence should be performed in terms of a lender’s credit loss history, fees/expenses, and use of leverage.
Simple, easy-to-implement, systematic formula-based investing can still generate market outperformance, providing investors with efficient exposure to well-documented factor premiums.
A critical task in stock selection is identifying a firm’s true profitability. Given the potential of AI to deal with large data, an important question is: Can AI outsmart seasoned analysts?
Systematic factor-driven value strategies have underperformed broad market indices (such as the S&P 500) over the past 15+ years. That has led many to question [...]
Cliffwater found that private equity allocations by state pensions produced a 11.0% net-of-fee annualized return over the 23-year period ending June 30, 2023. Over the same period the CRSP 1-10 Index (U.S. total market) returned 7.2% and the MSCI All Country World ex USA Index returned 4.4%.
An anomaly is a pattern in stock returns that deviates from what is expected based on established financial theories or models. These patterns can sometimes [...]
The bottom line is that returns to the low volatility anomaly have only justified investing when low-volatility stocks were in the value regime, after periods of strong market performance, and when they excluded high-volatility stocks that have low short interest (providing clues as to how to improve its performance). This may be why live funds have been generating large negative alphas once we account for common factor exposures.
The growth rate of private credit has been so rapid (growing to nearly $2 trillion by the end of 2023, roughly ten times larger than it was in 2009), that concerns about there being a bubble have been raised.
Greenwood and Sammon’s findings of a disappearing index effect provides further support for the findings of McLean and Pontiff, Does Academic Research Destroy Stock Return Predictability? 2016. Once anomalies are well recognized by the market they decline and may even disappear, though limits to arbitrage can allow them to persist. Their findings also provide support for Andrew Lo’s The Adaptive Markets Hypothesis (2004). The bottom line is that markets are becoming more efficient, raising the hurdles for active managers to generate alpha.
The authors of the research discussed developed a machine learning model that can accurately predict trading volume for individual stocks. They then demonstrated how this model can be used to construct a portfolio that outperforms a traditional market-cap weighted portfolio.
The hurdles to adding alpha for active managers are getting higher—investment practitioners make use of it as soon as or shortly after it is available.
Because the Sahm rule focuses solely on the unemployment rate, caution is warranted before assuming it is signaling a recession.
An index-tracking approach generally lacks flexibility, which detracts from performance, leaving returns on the table. Intelligent design can overcome such issues. For example, an S&P 500 Index could choose to rebalance one month ahead of the scheduled reconstitution, minimizing the impact of reconstitution. Direct index funds are already engaging in such strategies with ETFs.
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