Does Momentum work in Option Markets?
This paper explores the question of option momentum by examining what the research says about the performance of option investments across different stocks.
Is there a theoretical foundation behind industry and factor momentum
Industry and factor momentum should be viewed as recent developments in the wider momentum story, although these aggregated measures of momentum lack any theoretical foundation.
The Role of the Secular Decline in Interest Rates in Asset Pricing Anomalies
Jules van Binsbergen, Liang Ma and Michael Schwert, authors of the September 2022 study “The Factor Multiverse: The Role of Interest Rates in Factor Discovery,” posed an interesting question: Are the findings of at least some of the reported anomalies the direct result of the 40-year secular decline in global interest rates and thus not really anomalies?
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.