A large body of evidence demonstrates that momentum, including time-series momentum (trend following), has improved portfolio efficiency. Research has found that there are a few ways to improve on simple trend-following strategies. Techniques that have been found to improve Sharpe ratios and reduce tail risk include volatility scaling and combining fast and slow signals as well as combining long-term reversals. These have been incorporated by many fund managers into investment strategies. Cheng, Kostyuchyk, Lee, Liu and Ma provided evidence that machine learning could be used to further improve results. With that said, a word of caution on the use of machine learning is warranted. The powerful tools and the easy access to data now available to researchers create the risk that machine learning studies will find correlations that have no causation and thus the findings could be nothing more than a result of torturing the data. To minimize that risk, it is important that findings not only have rational risk- or behavioral-based explanations for believing the patterns identified will persist in the future, but they also should be robust to many tests. In this case, investors could feel more confident in the results if their findings were robust to international equities and other asset classes (such as bonds, commodities and currencies).
An interesting question is do the trades of the more sophisticated institutional investors against anomalies provide information on returns? To answer that question, Yangru Wu and Weike Xu, authors of the study “Changes in Ownership Breadth and Capital Market Anomalies,” published in the February 2022 issue of The Journal of Portfolio Management, examined whether the entries and exits of informed institutional investors (or ownership breadth changes) interact with the aforementioned 11 anomaly signals studied by Stambaugh and Yuan can be used to improve the performance of anomaly-based strategies. They explained that they emphasized institutions’ new entries and exits because they could be triggered by private information and correlated with future earnings news, thereby capturing useful information regarding future stock returns. To determine if the trades of the institutional investors were informed, they sorted all stocks into 10 decile portfolios based on quarterly changes in ownership breadth. Their data sample covered all NYSE/AMEX/Nasdaq common stocks from May 1981 to May 2018.
Value and momentum are two of the most powerful explanatory factors in finance. Research on both has been published for about 30 years. However, it was not until recently that the two had been studied in combination and across markets. Bijon Pani and Frank Fabozzi contribute to the literature with their study “Finding Value Using Momentum,” published in The Journal of Portfolio Management Quantitative Special Issue 2022, in which they examined whether using six value metrics that have an established academic background combined with the trend in relative valuations provide better risk-adjusted returns than Fama-French’s traditional HML (high minus low book-to-market ratio) factor. The value metrics chosen were book value-to-market value; cash flow-to-price; earnings before interest, taxes, depreciation, and amortization (EBITDA)-to-market value; earnings-to-price; profit margin-to-price; and sales-to-price. Using six different measures provides tests of robustness, minimizing the risk of data mining. However with so many dials to turn there is a risk of achieving positive returns that aren't material or achieving postive results with the potential for overfitting.
The intuition behind betting against beta is that leverage-constrained investors, instead of applying leverage, obtain an expected return higher than the market’s expected return through overweighting high-beta stocks and underweighting low-beta stocks in their portfolios. Their actions lower future risk-adjusted returns on high-beta stocks and increase future risk-adjusted returns on low-beta stocks. We take a deeper look into this idea.
As the chief research officer of Buckingham Strategic Partners, the issue I am being asked to address most often is about fixed income strategies when yields are at historically low levels and inflation risk is heightened due to the unprecedented increase in money creation (through quantitative easing), the extraordinary expansionary fiscal spending around the globe, and the war in Ukraine driving prices higher (especially for food and energy). As always, to answer the question we turn first to the academic evidence on which investments in general provide the best hedges against inflation.
Long-only factor performance is more likely to degrade from sector neutralizing—keeping the sector component produced better long-only factors in 78 percent of the trials. The largest negative from sector neutralizing occurred for the value-weighted long-only factors that trade large stocks, arguably the most investable portfolio.
Robin Greenwood, Andrei Shleifer, and Yang You authors of the study “Bubbles for Fama”, published in the January 2019 issue of the Journal of Financial Economics evaluated Fama's claim that stock prices do not exhibit price bubbles. Based on a fixed threshold for the industry price increases (e.g., a 100 percent price run-up during two consecutive years) to filter their events and to analyze what happens afterward, they examined U.S. industry returns over the period 1926‒2014 (covering 40 episodes) and international sector returns (1985‒2014).
“Employees are our greatest asset” is a phrase often heard from companies. However, due to accounting rules requiring that most expenditures related to employees be treated as costs and expensed as incurred, the value of employees is an intangible asset that does not appear on any balance sheet. That leaves the interesting question of whether employee satisfaction provides information on future returns.
The superior performance of low-volatility stocks was first documented in the literature in the 1970s—by Fischer Black in 1972, among others —even before the size and value premiums were “discovered.” The low-volatility anomaly has been shown to exist in equity markets around the world. Interestingly, this finding is true not only for stocks but for bonds as well. In other words, it has been pervasive...but
As mind-bending as it sounds, although a company’s internally generated intangible investments generate future value, they are currently not accepted as assets under US GAAP. Omission of this increasingly important class of assets reduces the usefulness and relevance of financial statement analysis that uses book value. In fact, Amitabh Dugar and Jacob Pozharny, authors of the December 2020 study “Equity Investing in the Age of Intangibles,” concluded that the relationship between financial variables and contemporaneous stock prices has weakened so much for high intangible intensity companies in both the U.S. and abroad that investors can no longer afford to ignore the changes in the economic environment created by intangibles.
Taken together, our results suggest that firms’ personnel expenditures reflect not just the cost of labor in the current period but also the investment in human capital contained within that cost, and that market participants fail to fully understand the opportunity and efficacy of human capital development embedded in the disclosure of the expense.
From 2017 through March 2020, the relative performance of value stocks in the U.S. was so poor, experiencing its largest drawdown in history, that many investors jumped to the conclusion that the value premium was dead. It is certainly possible that what economists call a “regime change” could have caused assumptions to change about why the premium should exist/persist.
The reported results we covered have important implications for investors in terms of portfolio construction, risk monitoring, and manager selection. Because these common factors explain almost all the returns of bond portfolios, investors should construct their bond portfolios using low-cost, passively (systematically) managed funds with these factors in mind and then carefully monitor their exposure to these systematic risks.
The main takeaway for investors is that Kelly, Moskowitz, and Pruitt demonstrated that past return characteristics are strongly predictive of a stock’s realized exposures to common risk factors, providing direct evidence that price trend strategies are in part explainable as compensation for common factor exposures—past returns predict betas on factors and those factors have high average returns.
We've been suffering through the deepest and longest drawdown in values history. Looking for a scapegoat to explain the lackluster performance many have pointed to low interest rates as the root cause of the underperformance. The question is have interest rates impacted value in the past?
Despite the fact that a company’s internally generated intangible investments create future value, under current U.S. generally accepted accounting principles, internally developed intangibles are not included in reported assets. While research and development is an important intangible asset, so too is branding. Omission of an increasingly important class of assets reduces the usefulness and relevance of financial statement analysis that uses book value.
Using data on 65,000 stocks from 23 countries, they evaluated the performance of the Fama-French factors, examining the factor premia in global markets to verify their robustness across different company size categories and geographical regions. Their data sample covered the period 1987-2019.
One of the big problems for the first formal asset pricing model developed by financial economists, the CAPM, was that it predicts a positive relationship between risk and return. However, empirical studies have found the actual relationship to be basically flat, or even negative. Over the last 50 years, the most “defensive” (low-volatility or low-beta, low-risk) stocks have delivered both higher returns and higher risk-adjusted returns than the most “aggressive” (high-volatility, high-risk) stocks.
Liquidity—the ability to buy and sell significant quantities of a given asset quickly, at low cost, and without a major price concession—is valuable to investors. Therefore, they demand a premium as compensation for the greater [...]