This exhibit shows the cumulative returns of a long-short momentum strategy (winner-minus-loser portfolio) in US equities from 1866 to 2024. Performance is gross of transaction costs in USD. Both value-weighted and equal-weighted portfolios are displayed, highlighting the remarkable growth and resilience of momentum over more than 150 years. Chart represents a snapshot of the data which is fully accounted for through 2024. Source: Baltussen, Dom, Van Vliet & Vidojevic (2026). Momentum factor investing: Evidence and evolution, forthcoming in Journal of Portfolio Management.
Yet momentum should not be viewed as a single, uniform strategy. Its performance depends heavily on how the portfolio is built. Design choices such as whether returns are value-weighted or equal-weighted, where breakpoints are set, industry neutralization, and microcap stock inclusion can all affect both the level of returns and the amount of risk taken.
To quantify this sensitivity, we create more than 4,000 variations of momentum portfolios. All of them generate positive Sharpe ratios, indicating that the momentum premium is broadly robust. However, the performance range is substantial: the median Sharpe ratio is 0.61, but individual specifications span from 0.38 to 0.94. This indicates that reported returns can vary depending on how the factor is built. For practitioners, it underscores the importance of rigorous specification checks and transparency in factor design, especially when benchmarking or reporting results.
In recent decades, momentum research has broadened well beyond simple price trends. New forms of momentum capture different ways in which returns continue over time. Fundamental momentum, based on earnings surprises, analyst revisions, or news sentiment, reflects investors’ tendency to underreact to new information. Residual momentum focuses on firm-specific return patterns, isolating company-level news and typically producing smoother, higher-Sharpe results. Anchor-based momentum, such as the distance to a stock’s 52-week high, exploits behavioral biases like anchoring and the reluctance to sell at a loss.