Momentum investing remains a cornerstone of systematic equity strategies, and our recent research shows it is one deserving of allocators’ full attention. In our latest review (forthcoming, 2026), we provide a comprehensive update on its empirical foundations and practical evolution.
Drawing on more than 150 years of data and thousands of portfolio specifications, we reaffirm momentum’s resilience while highlighting its transformation into a multidimensional phenomenon. The momentum premium is not a statistical fluke or a product of data mining; rather, it is a consistent and sizable return spread that has endured across eras, geographies, and portfolio construction choices.
For institutional investors, however, our findings are both a validation and a challenge: momentum is robust, but its implementation and risk profile have changed in ways that demand careful attention.
150 Years of Persistence….and Counting
Momentum’s long-term persistence is perhaps its most defining feature and the primary reason it remains relevant for investors. Exhibit 1 illustrates this long-term performance, showing the cumulative returns of a simple long-short momentum strategy from 1866 to 2024.
Over this 150-year sample, a simple long–short strategy that buys past winners and sells past losers turns an initial $1 into more than $10,000, reflecting annualized returns of roughly 8–9%. These returns are not only sizable, but also highly statistically significant, with t-statistics far above the thresholds typically used to determine whether a result is real or due to chance.
Importantly, this finding is not sensitive to how the portfolios are constructed. Whether we use value-weighted or equal-weighted returns, adjust the definition of momentum, or alter the time period examined, the premium persists. Such robustness across specifications and sample windows strengthens the conclusion that momentum is not an artifact of a particular methodology.
For institutional investors, the message is straightforward: momentum has endured across eras, market conditions, and portfolio designs, indicating that it reflects a structural feature of financial markets rather than a fleeting anomaly.
Exhibit 1: Long-Term Performance of Momentum
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.
Industry and network momentum capture both top-down forces (sector trends, macro cycles) and bottom-up relationships (product-market linkages, analyst attention spillovers), while factor momentum reflects slow-moving capital flows into styles and persistent macro environments favoring certain characteristics. These alternative signals are imperfectly correlated with traditional price momentum and with one another, providing meaningful diversification.
The multidimensional composite (EW_ALL), which equally weights price momentum and ten alternative signals, delivers higher average returns, stronger t-statistics, and substantially improved drawdown characteristics relative to price momentum alone.
Exhibit 2 illustrates the cumulative performance of this composite versus traditional price momentum since 1927, making the diversification benefits and risk-efficiency gains readily apparent.
Exhibit 2: Multidimensional Momentum vs. Price Momentum
This exhibit compares the cumulative returns of traditional price momentum and the multidimensional momentum composite (EW_ALL) since 1927. Performance is gross of transaction costs in USD. All underlying signal portfolios are equal-weighted. The equal-weighted composite combines price momentum with ten alternative momentum signals, demonstrating superior returns and risk-adjusted performance relative to price momentum alone. Chart represents a snapshot of the data which is fully accounted for through 2024. Source: Baltussen et al. (2026). Momentum factor investing: Evidence and evolution, forthcoming in Journal of Portfolio Management.
The Blind Spot
The Achilles heel of momentum, however, remains its crash risk. Momentum strategies are vulnerable to sharp reversals, particularly during market regime shifts. We document maximum drawdowns as large as –88% for traditional price momentum, accompanied by left-skewed and fat-tailed return distributions.
However, many alternative momentum signals are less volatile, and the multidimensional composite meaningfully reduces risk relative to price momentum alone. Building on prior work, we implement volatility-scaling at both the portfolio and stock levels, dramatically reducing drawdowns and improving Sharpe ratios. The resulting risk-managed momentum strategy (RM_MOM) delivers annualized returns of nearly 18% at volatility comparable to standard momentum, with drawdowns cut nearly in half.
Diversify the Signals
For institutional investors, the implications are clear. Factor construction matters, and robustness checks across portfolio designs are critical. Diversifying momentum signals can deliver superior risk-adjusted returns.
Managing crash risk through volatility scaling and multidimensional portfolios is essential for sustainable momentum exposure. While risk-based theories may explain some of the premium, behavioral biases and limits to arbitrage remain central to momentum’s persistence.
We consider Momentum an “eternal” feature of financial markets. But its implementation must evolve. Investors who embrace multidimensional, risk-managed momentum strategies will be better positioned to capture persistent alpha while navigating the inevitable risks.
References
Baltussen, Dom, Van Vliet & Vidojevic (2026). Momentum factor investing: Evidence and evolution, forthcoming in Journal of Portfolio Management.
