Momentum: Why What Rises Tends to Keep Rising (and How to Measure It)

You're sitting in front of the screen, looking at a stock that has gained 40% over the last 12 months, and you have two thoughts simultaneously. First: "I've missed this one, it's too late now." Second: "But what if it keeps going up?" And it's precisely in this contradiction that one of the best-documented phenomena in financial history lives — momentum.

The paradox is that your intuition ("what goes up must come down") goes directly against what the data has shown for almost a hundred years. Whether you profit or lose often depends on whether you understand the difference between what you feel and what you measure.

A Tale of Two Investors

Imagine two people at the screen. Adam is looking for "value." He sees a stock that has fallen from 100 to 50 over the year → he thinks it's a 50% discount and can't go lower. David looks at another stock that has risen from 100 to 150 over the same period → and yet he buys. Adam follows his intuition, David goes against it.

Six months later: Adam's "cheap" stock has fallen to 35 (the company is undergoing a structural crisis that the market correctly priced). David's "expensive" one is trading at 190 (the company is riding a strong trend and exceeding expectations). It's not a law and doesn't always hold — but statistically, it happens more often than common sense would allow us to believe.

What Momentum Actually Is

Momentum is a simple observed tendency: assets that have performed above average in the recent past statistically have a higher chance of performing above average in the following period. Conversely, losers tend to lag for a while. It's not a certainty, it's a probabilistic tilt.

It sounds almost too simple to work. And that's exactly why it was ignored for so long — it goes against common sense and classical theory, which states that past prices should say nothing about future ones.

Why Momentum Works at All (The Psychology Behind the Numbers)

The phenomenon isn't magic, but predictable human behavior:

• Underreaction: Analysts and investors react slowly to new information. After great results, it takes weeks to months for everyone to adjust their models — and the price moves gradually, not in a jump.
• Herding effect: Once the trend is confirmed, more jump on board — institutional funds and retail alike — pushing the price further in the same direction.
• Anchoring: Investors mentally cling to the old price ("but it was 100!") and refuse to believe the company can have a genuinely higher value.

These three forces together explain why information doesn't flow into prices all at once but seeps in — and why a trend tends to have inertia.

What the Data Says

A classic academic study from the 90s (Jegadeesh and Titman) divided U.S. stocks based on returns over the past 3 to 12 months into groups. The "winners" portfolio then consistently outperformed the "losers" portfolio — roughly by a few percentage points annually, consistently across decades.

A few numbers for illustration (all approximate, historically):

• Momentum as a factor has been tested on data since the 1920s and worked on stocks, commodities, currencies, and bonds.
• The effect is strongest in the 6 to 12-month window — shorter windows are noisy, longer ones tend to reverse.
• Reversal effect: on very short (days/weeks) and very long (3–5 years) horizons, the opposite often works — a return to the mean.

Key warning: none of these numbers is a promise. Momentum also has a dark side — so-called "momentum crashes." When the market sharply reverses after a drop, the losers' portfolio shoots up, and the momentum strategy suffers one of the worst losses ever. After the bottom of the 2009 crisis, it was one of the historically most brutal months for this factor.

How Momentum Is Specifically Measured

Here's where the fun begins, because "momentum" isn't a single number — it's a whole family of metrics. Let's look at three of the most common approaches.

1. Simple Price Return Over a Period

The simplest variant: take today's price and the price from X months ago.

Momentum = (Price_today / Price_12M_ago) - 1

Example: a stock was 100 a year ago, today it's 135 → momentum = +35%. Quick, but rough.

2. "12 Minus 1" Momentum

Professionals usually skip the last month. Why? Because on a one-month horizon, a short-term reversal effect rules — the last jump often "noises" the signal. Thus, the return is measured for months 12 to 2 (a year without the last month). A small adjustment that historically cleans the signal significantly.

3. Risk-Adjusted Momentum

A raw return of +35% looks great, but what if the stock was jumping 8% daily? That's why the return is often divided by volatility:

Score = Return over period / Volatility over period

This gives you something like "momentum per unit of risk." Two stocks with +30% aren't the same if one was calm and the other a roller coaster.

Relative vs. Absolute Momentum

• Relative (cross-sectional): you compare stocks with each other — who's in the top 20% (quintile) of the ranking.
• Absolute (time-series / "trend"): you ask if the asset is above its own moving average (e.g., 200-day). Either the trend is up, or it's not.

Both approaches are legitimate and often combined.

Practical Framework: How to Calculate Momentum Yourself

You don't need a supercomputer. Just a spreadsheet and discipline. Try this mini-procedure on 5 stocks you follow:

1. Download prices as of today and exactly 12 and 1 month ago.
2. Calculate "12 minus 1": return from the date 12M ago to the date 1M ago (skip the last month).
3. Sort them from highest to lowest — you'll get your own momentum ranking.
4. Add a risk check: for top names, check if the growth wasn't just one wild jump on one news (that's not a trend, that's a fluke).
5. Check fundamentals: pure price momentum can be deceptive if it's just an empty bubble rising. Is it supported by growing revenues and stable margins?
6. Define a stop rule in advance: what will you do if the stock falls below its 200-day average? Decide now, not in panic.

Behavioral trap you'll encounter: momentum forces you to buy things that have already gone up — and that hurts psychologically. "But it's already expensive!" This discomfort is precisely why the factor still works — most people simply can't handle it.

Where Momentum Has Limits

So it's not all praise:

• Higher turnover. The ranking changes, so momentum strategies often trade more → higher costs and tax impacts.
• Susceptibility to market reversals. The mentioned "momentum crashes" come suddenly and painfully.
• Overcrowding. When too many players follow the same signal, its strength can weaken.

Momentum is not the holy grail — it's one of several factors (alongside value, quality, size) that make the most sense in combination.

In QMA

Manually calculating "12 minus 1" for five stocks is doable. For five hundred, not so much. In QMA, you'll find momentum reflected in scores and screeners — instead of downloading prices into Excel, you see the relative strength of individual titles ranked and supplemented with other factors, so you immediately know if high momentum is also supported by quality, or if it's just a solitary rocket jump. QMA filters that ranking for you and shows it in context — not as an isolated number.

Key Takeaways

• Momentum is an observed statistical tendency, not a certainty — it works in probabilities on a horizon of roughly 6–12 months and has its dark side in the form of sudden reversals.
• Learn to measure it correctly: use the "12 minus 1" window instead of raw annual return and consider risk adjustment by dividing by volatility.
• Create your own mini-ranking today from 5 stocks you follow using the procedure above — you'll understand momentum better from one table than from ten articles.
• Set your rules in advance, because momentum without discipline is just chasing what's already taken off.

open in QMA

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Always conduct your own research or consult a financial advisor before making investment decisions.