This time is almost always different, it seems, but the data suggest that things are typically always the same: chaotic and volatile. Stock market investors should be prepared for large short-term moves in stocks and they should be skeptical of narratives suggesting a causal relationship between environmental variables and future volatility.
How did Momentum investing perform after the previous two valuation peaks?
This article answers this question.
Key finding: Momentum investing also performed well following episodes when value stocks were cheap. Of course, momentum portfolios did not perform nearly as well as value portfolios, but they did still beat the generic market.
We dig into the details below.
We examine the short-duration premium using pre-scheduled economic, monetary policy, and earnings announcements. We provide high-frequency evidence that duration premia associated with revisions of economic growth and interest rate expectations are consistent with asset pricing models but cannot explain the short-duration premium. Instead, we show that the trading activity of sentiment-driven investors raises prices of long-duration stocks, which lowers their expected returns, and results in the short-duration premium. Long-duration stocks have the lowest institutional ownership, exhibit the largest forecast errors at earnings announcements, and show the highest mispricing scores.
We find that factor momentum concentrates in factors that explain more of the cross section of returns and that it is not incidental to individual stock momentum: momentum-neutral factors display more momentum.
An equal-weighted portfolio of Best Brands (BBs) in the U.S. earns an excess return of 25 to 35 bps per month during the period 2000-2020. This result is remarkably robust across various factor models and therefore is not driven by exposure to common (risk) factors. The excess returns of the BB portfolio are not due to firm characteristics, industry composition, or small-cap stocks. We provide evidence suggesting that expensing investments in brands (instead of capitalizing them) and the tendency to underestimate the effect of brand name on generating future earnings are two mechanisms contributing to the excess returns.
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
Investments aligned with environmental, social, and governance (ESG) principles are rapidly growing globally. In the exchange traded fund (ETF) industry, this gives rise to the power of ESG rating firms that have the influence to direct capital flows into ETFs tracking the indexes. This article examines the issues of substantial ESG rating divergence across rating firms, the impact on investors’ choices, and the influence on the ETF industry. The divergence appears to be the greatest in social and governance components, and is often qualitative in nature. The author found that certain economic sectors are more prone to ESG rating divergence than others. She presents a case study about two ESG ETFs that are viewed quite differently under various rating lenses, and offers suggestions to investors, advisors, and analysts on how to research ESG ETFs, given the major rating divergence. The article concludes with ways the ETF industry could improve its practices collectively to better serve investors with clarity and to sustain the growth of ESG impact investments.
Current Exposures:
Non-standard errors capture uncertainty due to differences in research design choices. We establish substantial variation in the design choices made by researchers when constructing asset pricing factors. By purposely data mining over two thousand different versions of each factor, we find that Sharpe ratios exhibit substantial variation within a factor due to different construction choices, which results in sizable non-standard errors and allows for p-hacking. We provide simple suggestions that reduce the average non-standard error by 70%. Our study has important implications for model selection exercises.
Do equity markets care about income inequality? We address this question by examining equity markets’ reaction and investors’ portfolio rebalancing in response to the first-time disclosure of the ratio of CEO to median worker pay by U.S. public companies in 2018. We find that firms’ disclosing higher pay ratios experience significantly lower abnormal announcement returns. Additional evidence suggests that equity markets “dislike” high pay dispersion rather than high CEO pay or low worker pay. Firms whose shareholders are more inequality-averse experience a more pronounced negative market response to high pay ratios compared to firms with less inequality-averse shareholders. Finally, we find that during 2018 more inequality-averse investors rebalance their portfolios away from high pay ratio stocks relative to other investors. Overall, our results suggest that equity markets are concerned about high within-firm pay dispersion, and investors’ attitude towards income inequality is a channel through which high pay ratios negatively affect firm value.
Here is the bottom line: converting into the ETF structure can bring a lot of benefits to the table, but porting your official track record over to an ETF can be challenging.
However, even if the facts and circumstances of your situation suggest that porting your official track record into an ETF is impossible, all is not lost. Retail consumers, institutional investors, platform providers, gate-keepers, and so forth, will likely be aware of your previous performance and reputation as an asset manager/advisor and they can often read between the lines. For example, if an advisor has been running the "ACME US Dividend Strategy" for 20 years, and this same advisor launches the "ACME US Dividend ETF" with the same investment process and investment objective, it doesn't take a rocket surgeon (or a brain scientist) to figure out that the ETF is probably a more tax-efficient version of the old strategy.
This paper provides new evidence showing that carbon transition risk is becoming increasingly material and is priced both in equity and debt markets. We find that there is a widespread price-earnings discount linked to corporate carbon emissions. This discount varies, however, by sector and trends differently in Europe than in the US. We also find that a small discount emerges for corporate bonds, although it is statistically significant only for small caps. Finally, we find evidence that the pricing discount also emerges, albeit to a smaller extent, for other greenhouse gas emissions.
We estimate that passive investors held at least 37.8% of the US stock market in 2020. This estimate is based on the closing volumes of index additions and deletions on reconstitution days. 37.8% is more than double the widely accepted previous value of 15%, which represents the combined holdings of all index funds. What’s more, 37.8% is a lower bound. The true passive-ownership share for the US stock market must be higher. This result suggests that index membership is the single most important consideration when modeling investors’ portfolio choice. In addition, existing models studying the rise of passive investing give no hint that prior estimates for the passive-ownership share were 50% too small. The size of this oversight restricts how useful these models can be for policymakers.
Relative sentiment is an indicator that measures the positions, flows, and attitudes of institutional investors compared to those of individual investors–where institutions typically consist of large asset managers, insurance companies, pension funds, and endowments. In some instances, however–depending on the dataset and the asset class under consideration–institutions might also include hedge funds, CTAs, and other large speculators.
Short-term alpha signals are generally dismissed in traditional asset pricing models, primarily due to market friction concerns. However, this paper demonstrates that investors can obtain a significant net alpha by combining signals applied on a liquid global universe with simple buy/sell trading rules. The composite model consists of short-term reversal, short-term momentum, short-term analyst revisions, short-term risk, and monthly seasonality signals. The resulting alpha is present across regions, translates into long-only applications, is robust to incorporating implementation lags of several days, and is uncorrelated to traditional Fama-French factors.
I am grateful for this book because I am less confused about sustainable investing, and I am inspired to learn more about the topic. I commend Larry and Sam’s work for being technically accurate and complete, while accessible to a reader who isn’t an expert on the subject and is looking to learn more.
Using a unique dataset of individual transactions-level data for a universe of U.S. consumer facing stocks, we examine the information content of consumer credit and debit card spending in explaining future stock returns. Our analysis shows that consumer spending data positively predict various measures of a company’s future earnings surprises up to three quarters in the future. This predictive power remains strong in both large- and small-cap universes of consumer discretionary firms in our sample and is robust to the type of transactions data considered (credit card, debit card, or both), although the relationship is stronger in the small-cap universe where informational asymmetries are more pronounced. Based on this empirical observation we build a simple long-short strategy that takes long/short positions in the top/bottom tercile of stocks ranked on our real-time sales signal. The strategy generates statistically and economically significant returns of 16% per annum net of transaction costs and after controlling for the common sources of systematic factor returns. A simple optimization exercise to form (tangency) mean-variance efficient portfolios of factors leads to an optimal factor allocation that assigns almost 50% weight to our long-short portfolio. Our results suggest that consumer transaction level data can serve as a more accurate and persistent signal of a firm’s growth potential and future returns.
Litigation finance is a rapidly growing niche asset class focused on debt and equity investments in litigation claims and law firms. We find that in-sample returns in the space have been in excess of 20% annually with limited correlation to other investment areas. This apparent excess return may be due to information asymmetry and barriers to entry in the space. Our findings highlight the opportunities and risks for investors in this nascent asset classes and suggest such excess returns are due in part to limits to the speed with which efficient markets take hold.
If one had to invest in buy and hold treasury bonds or trend-followed treasury bonds, it is likely that most investors would prefer the trend-followed bond investment. However, in a broader portfolio context, the analysis suggests that how one 'eats' their bond exposure is largely irrelevant and the portfolio's long-term outcome will be driven by equity market dynamics. Bonds systematically lower an equity-centric portfolio's returns, but they also lower the risk profile of the overall portfolio.
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
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