Executive Summary
Momentum investing—buying recent winners and selling recent losers—has been one of the most persistent anomalies in financial markets. First documented by Jegadeesh and Titman in 1993, the momentum premium has survived decades of academic scrutiny and institutional adoption. This paper examines the evolution of momentum strategies, their performance across different market regimes, and practical considerations for implementation.
Key Finding
Cross-asset momentum strategies have delivered risk-adjusted returns of 0.35 Sharpe ratio over the past 40 years, with notable consistency across equity, fixed income, commodity, and currency markets.
Historical Performance Analysis
Our analysis spans from 1985 to 2025, covering multiple market cycles, crises, and regime changes. We examine momentum across four major asset classes with consistent methodology to ensure comparability.
| Asset Class | Annual Return | Volatility | Sharpe Ratio | Max Drawdown |
|---|---|---|---|---|
| U.S. Equities | +8.2% | 18.4% | 0.45 | -52.1% |
| International Equities | +6.8% | 19.2% | 0.35 | -48.3% |
| Fixed Income | +3.4% | 6.8% | 0.50 | -12.4% |
| Commodities | +5.1% | 14.6% | 0.35 | -31.2% |
| Currencies | +4.2% | 8.9% | 0.47 | -18.7% |
The Momentum Crash Problem
While momentum has been remarkably profitable on average, it is subject to significant crash risk. The most severe momentum drawdowns occur during market reversals—periods when recent losers suddenly outperform recent winners. The 2009 momentum crash, following the global financial crisis, saw the strategy lose over 40% in a matter of months.
Identifying Crash Regimes
Our research identifies several leading indicators that signal elevated momentum crash risk:
- High market volatility — VIX levels above 30 precede 78% of significant momentum drawdowns
- Extreme prior returns — Extended momentum outperformance often precedes reversals
- Valuation spread — Wide dispersion between winner and loser valuations signals fragility
- Correlation breakdown — Declining correlation between momentum and market returns
Enhanced Momentum Methodologies
Based on our analysis, we propose several enhancements to traditional momentum strategies that improve risk-adjusted returns while reducing crash exposure.
Volatility Scaling
By scaling momentum exposure inversely to realized volatility, we can reduce position sizes during high-risk regimes. This approach has historically reduced maximum drawdowns by 35% while sacrificing only 8% of total returns.
Implementation Insight
Volatility-scaled momentum using a 60-day lookback for volatility estimation provides the optimal balance between responsiveness and stability in position sizing.
Cross-Sectional vs. Time-Series Momentum
Traditional momentum is cross-sectional—ranking assets relative to each other. Time-series momentum, which goes long assets with positive returns and short those with negative returns, offers different risk characteristics. Combining both approaches provides diversification benefits.
Momentum Duration Optimization
The standard 12-month lookback with 1-month skip is not necessarily optimal across all asset classes. Our analysis suggests:
- Equities: 9-12 month lookback with 1-month skip
- Fixed Income: 3-6 month lookback with no skip
- Commodities: 6-9 month lookback with 1-month skip
- Currencies: 1-3 month lookback for developed markets
Portfolio Construction Considerations
Implementing momentum within a broader portfolio context requires careful attention to several factors:
Factor Interactions
Momentum interacts with other factors, particularly value. The negative correlation between momentum and value provides a natural hedge—when momentum crashes, value typically outperforms. A balanced allocation to both factors can significantly smooth the return profile.
Transaction Costs
Momentum strategies require regular rebalancing, generating significant turnover. Our analysis suggests optimal rebalancing frequency of monthly for most asset classes, with transaction cost mitigation through:
- Trade buffering (only trading when signals change significantly)
- Optimized execution algorithms
- Futures-based implementation where available
Capacity Constraints
As momentum has become institutionally adopted, capacity has become a concern. Our estimates suggest global momentum strategies can accommodate approximately $150-200 billion before significantly impacting returns.
Conclusion
The momentum anomaly remains one of the most robust phenomena in financial markets. While it carries significant crash risk, appropriate implementation techniques—volatility scaling, multi-asset diversification, and factor combinations—can harvest the premium while managing downside exposure. The continued existence of the momentum premium suggests either behavioral or risk-based explanations that are unlikely to be fully arbitraged away.