Global Factor Performance: November 2022
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
The Cross Section of Stock Returns Pre-CRSP data: Value and Momentum are confirmed as robust anomalies
We study the cross-section of stock returns using a novel constructed database of U.S. stocks covering 61 years of independent data.
Market Risk and Speculative Factors
Soroush Ghazi and Mark Schneider authors of the August 2022 study “Market Risk and Speculation Factors” decomposed the excess market return (the equity risk premium) into speculative (in the simple sense that it is negative, reflecting a premium investors pay to hold assets that are more subject to speculative demand) and non-speculative, or risk (in the simple sense that it is positive, a necessary characteristic for a factor to reflect compensation for risk) components.
Momentum Factor Investing: 30 years of Out of Sample Data
In this article, the author examines the research published over the last 30 years on momentum and its theoretical credibility. One of the original momentum articles was published by Jegadeesh and Titman in 1993, and is considered the seminal work on the topic. The research review contained in this publication begins with the 1993 work and confines itself to only the highest quality journals among the plethora of work that has been published on momentum.
Mind the Momentum Gap to Improve Performance
This article discusses the academic research about the Momentum Gap and the role that its predictive potential may have in reducing momentum crashes, hence possibly improving performance.
Bias in Beta and Implications for Empirical Asset Pricing
In this article, the author examines several important questions related to asynchronous trading, or the variation in trading frequency that occurs when trading stocks or other assets.
Lottery Demand and the Asset Growth Anomaly
It is well documented in the literature that over the long term, low-investment firms have outperformed high-investment firms—with the negative relation between asset growth (AG) and future stock returns particularly featured by the overvaluation of high AG stocks.
Global Factor Performance: October 2022
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
Momentum Everywhere, Including Emerging Markets
Atilgan et al. contribute to the momentum literature with “Momentum and Downside Risk in Emerging Markets.”
Does Gender Affect Reactions to Market Sentiment Shifts?
Does gender matter in institutional investing?
Gender Pay Gap Transparency
In this article, we examine what the research says about gender pay gap transparency. We look at the research questions and academic insights with an eye toward why it matters.
Momentum Investing: How Did Momentum Investing Perform After the Previous Two Valuation Peaks?
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.
The Short-Duration Equity Premium
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.
Is Momentum a Separate Factor?
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.
Brand Values and Long-Term Stock Returns
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.
Global Factor Performance: September 2022
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
How You Sort Matters in Sorting Factor Portfolios
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.
Is Relative Sentiment an Anomaly?
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.
Alpha from Short-Term Signals
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.
Mining Credit Card Data for Stock Returns
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.