This paper provides new evidence on the efficacy of prioritizing transactions so as to focus portfolio turnover on the trades that offer the strongest signals and hence the highest potential performance impact.
Low short positions come from positive public news, while negative news can drive average short or extremely high short positions
There is strong empirical evidence demonstrating that momentum (both cross-sectional and time-series) provides information on the cross-section of returns of many risk assets and has generated alpha relative to existing asset pricing models.
Higher volatility is associated with faster, initially stronger reversals, while lower turnover is associated with more persistent, ultimately stronger reversals
Momentum continues to receive much attention from researchers because of the strong empirical evidence.
While the empirical research on cross-sectional (long-short) momentum has shown that returns have been high, investors have also experienced huge drawdowns—momentum exhibits both high kurtosis and negative skewness. Since 1926 there have been several momentum crashes that featured short, but persistent, periods of highly negative returns. For example, from June to August 1932, the momentum portfolio lost about 91%, followed by a second drawdown from April to July 1933.
Strong empirical evidence demonstrates that momentum (both cross-sectional and time-series) provides information on the cross-section of returns of many risk assets and has generated alpha relative to existing asset pricing models.
In their two papers, Goulding, Harvey, and Mazzoleni showed that observed market corrections and rebounds carry predictive information about subsequent returns and showed how that information could be utilized to enhance the performance of trend-following strategies by dynamically blending slow and fast momentum strategies based on four-state cycle-conditional information.
Be careful before acting on what is considered to be conventional wisdom. Make sure it’s supported by empirical evidence. In this case, the evidence makes clear that “cut your losses and let your profits run” should not be conventional wisdom.
For investors that use trend-following strategies, Avramov, Kaplanski, and Subrhmanyam provided new evidence supporting momentum strategies and showed that the distance between short- and longer-term momentum signals provides additional explanatory power in the cross-section of equity returns.
Antonello Cirulli and Patrick Walker, authors of the December 2023 study “Outperforming Equal Weighting,” examined whether equally weighted portfolios could be enhanced by avoiding negative exposure to some of the most prominent factor anomalies documented in asset pricing literature.
Option returns display momentum, meaning that firms whose options performed well in the previous 6 to 36 months are likely to see high option returns in the next month as well.
While the research shows that fund managers are skilled, skill doesn’t translate into outperformance due to the diseconomies of scale.
Momentum investors utilize different timeframes to identify high momentum equities: past 6, 9, 12 months as an example. Obviously, there is a significant degree of overlap in momentum stocks identified across various past time frames. However, there has been little research focused on understanding the characteristics of momentum stocks formed on six and 12 months that overlap one another. The authors refer to the subset as “overlapping” stocks and suggest they constitute the largest proportion of the profitability of the momentum strategy.
The Jegadeesh and Titman (1993) paper on momentum established that an equity trading strategy consisting of buying past winners and selling past losers, reliably produced risk-adjusted excess returns. The Jegadeesh results have been replicated in international markets and across asset classes. As this evidence challenged and contradicted widely accepted notions of weak-form market efficiency, the academic community took notice and started churning out research. As a result, a very large number of academic studies were published on momentum. The article summarized here has conveniently summarized 47 articles deemed as the highest quality and published in either the Journal of Finance, the Review of Financial Studies, or the Journal of Financial Economics, all three considered premier journals in the finance discipline. It is difficult to understate the importance of having a well-curated summary of momentum research. Keep it in your library.
Trend follower nerd alert: This study is important because it offers a comprehensive analysis of TS momentum strategies, its unifying framework that links performance to underlying variables, and its practical implications for investors seeking to enhance their understanding of momentum investing and improve their portfolio performance.
Short term return anomalies are generally dismissed in the academic literature "because they seemingly do not survive after accounting for market frictions.” In this research, short term “factors” are taken seriously and the authors argue the standard parameters may not apply for short horizons.
Factor seasonality reflects its own stock-level equivalent. It is not an independent risk factor.
The traditional financial theory attributes security returns to market- or factor-based risk, with no role ascribed to other influences. In this research, the authors argue for including investor demand as an additional variable in explaining returns. Can changes in investor demand generate systematic changes in security returns?
Doug Pugliese, the head of our 1042 QRP business, was recently invited on the ScuttleButt Podcast to discuss the ESOP landscape and the costs and benefits of 1042 QRP transactions. (article on the topic is here).
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