Momentum Is the Most Persistent Anomaly in Finance
In 1993, Narasimhan Jegadeesh and Sheridan Titman published their landmark study in the Journal of Finance, examining US stocks from 1965 to 1989. The core finding: a strategy of buying past winners and selling past losers earned approximately 1.5% per month, or roughly 12% annualized. The effect was solid across all combinations of 3, 6, 9, and 12-month formation and holding periods.
That was over 30 years ago. In 2023, Jegadeesh and Titman published a retrospective confirming the effect's persistence. Asness, Moskowitz, and Pedersen documented momentum premia across eight diverse markets and asset classes in 2013. The effect exists in equities, bonds, commodities, currencies, and crypto. It shows up in markets going back to Victorian-era London. And unlike many academic anomalies, it has not been arbitraged away.
Why Momentum Exists
The persistence of momentum is itself a puzzle. In an efficient market, any predictable pattern should be exploited until it disappears. The fact that momentum still works after decades of widespread knowledge suggests its source is structural.
The most compelling explanation combines behavioral finance with market microstructure. On the behavioral side, investors underreact to new information. When a company reports strong earnings, the stock jumps, but not enough. The full price adjustment takes weeks or months as analysts update their models, funds rebalance, and the broader market digests the implications. This gradual information diffusion creates a drift in the direction of the initial move.
On the structural side, many large institutional investors are constrained in how quickly they can adjust positions. A pension fund that decides to increase its allocation to an asset class cannot buy everything at once without moving the market against itself. They spread purchases over weeks, creating sustained buying pressure that extends the trend.
There is also a reflexive component. Rising prices attract attention, media coverage, and new buyers. Falling prices trigger stop losses, margin calls, and forced selling. These feedback loops amplify and extend price moves beyond what fundamentals alone would justify.
Momentum in Crypto Is Amplified
Crypto markets exhibit stronger momentum effects than traditional equity markets. Yukun Liu and Aleh Tsyvinski at Yale found that a strategy of buying Bitcoin when its value increased more than 20% in the prior week generated outstanding returns and a very high Sharpe ratio. Their paper was published in the Review of Financial Studies in 2021. A subsequent 2022 paper established that market, size, and momentum are the three factors that capture cross-sectional expected cryptocurrency returns.
A 2024 study in the Journal of Financial and Quantitative Analysis found that a long-short strategy buying crypto coins with the highest expected returns and selling the lowest earned 3.87% per week, substantially outperforming other cryptocurrency factors.
The reasons for amplified crypto momentum are intuitive. More retail participation, fewer institutional arbitrageurs, higher volatility, and stronger narrative-driven flows. When a token starts moving, the social media amplification cycle kicks in faster and harder than in equity markets. The same underlying mechanism (gradual information diffusion plus reflexive feedback) operates with more intensity.
Multi-Timeframe Analysis
One of the more useful practical findings from momentum research is that the effect operates differently across timeframes. Very short-term momentum (under a week) is noisy and dominated by microstructure effects. Medium-term momentum (1-12 months) is where the effect is strongest. Long-term momentum (12+ months) actually reverses, as overextended trends mean-revert.
Practitioners using multiple timeframes report win rates of 60-75%, compared to approximately 45% with single-timeframe analysis. Signal alignment across at least two timeframes showed 58% win rates for aligned trades versus 39% for non-aligned trades. These figures come from practitioner backtesting rather than peer-reviewed journals, but the directional evidence is consistent.
A stock showing strong momentum on the daily, weekly, and monthly charts is more likely to continue trending than one showing momentum on only one timeframe. When all timeframes align, the convergence of forces pushing the trend forward is at its strongest.
Building a solid Momentum System
A functioning momentum system needs several components. Entry signals that identify when momentum is establishing, not after it has already extended. Multiple confirmation timeframes. A ranking mechanism when multiple opportunities exist simultaneously. Position sizing rules that account for volatility. And exit criteria for both stops and profit targets.
Backtesting is non-negotiable, but it comes with serious caveats. Harvey, Liu, and Zhu catalogued 316+ factors claimed to predict stock returns in their 2016 Review of Financial Studies paper, and concluded that most claimed findings are likely false due to cumulative data-mining. Any momentum system should be validated out-of-sample across multiple market regimes, with realistic transaction costs and slippage assumptions.
Explore these tools on Blockcircle: Momentum Trading Engine