Are you secretly running a momentum fund?

You picked your stocks one at a time. A cloud company here, a chipmaker there, a bank you liked the look of, an ETF a friend mentioned. Each choice felt like its own decision. So it comes as a surprise when someone tells you that, viewed from a distance, you’ve quietly assembled something that behaves a lot like a momentum fund — piling into whatever has been going up lately.

You never decided that. Nobody does, on purpose, one stock at a time. But the tilt is there anyway, baked into the sum of your choices. Understanding why is the whole point of factor investing — and it’s less about picking winners than about seeing what your portfolio is actually made of.

What are investment factors?

They are shared traits — size, cheapness, recent trend, profitability — that explain much of how many stocks move together. When you look at a single company, you see its story: the products, the CEO, the earnings call. But decades of research keep landing on an uncomfortable idea — most of what moves a stock isn’t its story. It’s a handful of shared traits that lots of stocks have in common.

Think of it like health. Two people can have completely different lives, but a doctor still measures the same underlying factors — blood pressure, cholesterol, resting heart rate — because those explain a huge share of what happens next. Stocks have their own version of these vital signs. We call them factors.

The most studied ones are:

• Market — the plain fact that you own stocks at all. When the whole market rises or falls, almost everything you hold moves with it. This is usually the single biggest driver of your returns, and it’s the one most people underestimate.
• Size — smaller companies have historically behaved differently from mega-caps. Not necessarily better, but differently, with their own rhythm of good and bad stretches.
• Value — “cheap” stocks (low price relative to earnings, book value, cash flow) versus “expensive” growth stocks. A portfolio can lean hard toward one camp without you ever using the word.
• Momentum — stocks that have been rising tend to keep rising for a while, and losers keep losing, until they don’t; Jegadeesh and Titman documented it in “Returns to Buying Winners and Selling Losers” (1993). This is the sneaky one, and we’ll come back to it.
• Profitability — firms with robust operating profitability have behaved differently from those with weak profitability (often loosely called “quality”).
• Investment — companies that grow their assets conservatively have behaved differently from those that invest aggressively.

None of these is a crystal ball. Each has gone through long, painful stretches of underperformance. The point isn’t that any factor is “good.” The point is that these traits are shared, and your exposure to them explains a surprising amount of how your portfolio moves.

What is a Fama-French factor model?

It is a regression that explains a portfolio’s returns as a blend of factor exposures. Economists Eugene Fama and Kenneth French introduced the three-factor version — market, size and value — in “Common risk factors in the returns on stocks and bonds” (1993). Mark Carhart added momentum in “On Persistence in Mutual Fund Performance” (1997), and Fama and French extended their own model to five factors, adding profitability and investment, in “A five-factor asset pricing model” (2015). The factor return series themselves are published free in the Kenneth R. French Data Library.

The mental model is a recipe. Instead of describing a cake as “delicious,” you list what’s actually in it: 60% flour, 25% sugar, 15% butter. Fama-French does that with returns. It runs a regression — a statistical fit — that answers: how much of your ups and downs can be explained by each factor?

The output is a set of numbers called factor loadings, or betas. A quick, made-up example of what a decomposition might look like:

• Market beta: 1.2 — you swing about 20% harder than the overall market.
• Size: +0.4 — a meaningful tilt toward smaller companies.
• Value: −0.6 — a strong lean away from value, toward growth.
• Momentum: +0.5 — a real momentum tilt.

Read that last line again. A momentum loading of +0.5 says a big chunk of this portfolio’s behavior tracks “stuff that’s been going up.” The owner may have never thought the word “momentum” in their life.

There’s also a leftover piece the factors can’t explain, called alpha. Honest translation: it’s the part of your results that isn’t accounted for by these common exposures. Sometimes it’s genuine skill. Often, over enough time, it shrinks toward zero once the factors do the explaining — which is a humbling and useful thing to see with your own eyes.

How does a portfolio end up with a momentum tilt by accident?

By buying what has been rising and letting winners grow. Here’s the mechanism, and it’s almost gravitational.

You buy what’s been working. The names in the headlines, the tickers up 80% this year, the sectors everyone’s excited about — those are, by definition, recent winners. Recent winners are exactly what the momentum factor is made of. So a portfolio built from “what’s hot” is a momentum portfolio wearing a disguise.

It compounds. Your winners grow into a larger share of your holdings just by rising, so the tilt gets stronger even if you never buy another share. A position that was 5% of your money becomes 15% after a great run, and now it’s steering the ship.

And it correlates. Those exciting growth names tend to share traits — high valuations, similar business models, sensitivity to the same interest-rate moods. You feel diversified because you own twelve different companies. In factor terms, you might own one bet twelve times.

This is why two people with completely different-looking holdings can get nearly identical results in a given year: under the hood, they’re running the same factor recipe. It’s also why understanding your true exposures connects directly to understanding your portfolio’s risk — the drawdowns, the beta, the value-at-risk you’re actually signed up for.

Does knowing your factor exposures predict returns?

No. It shows the bets you are already making, not which will pay. Let’s be careful here, because factor investing gets oversold. Knowing your factor tilts will not tell you what happens next. No factor pays off reliably, on schedule, or ever again with certainty — every one of them can and does underperform for years.

What factor analysis does give you is honesty about the bets you’re already making:

• Concentration you couldn’t see. “Diversified across 20 stocks” and “20 stocks loading on the same three factors” look identical on a holdings list and completely different in reality.
• Intent versus reality. If you believe you’re a patient value investor but your loadings say growth-and-momentum, that gap is worth knowing before a rough patch tells you the hard way.
• Better questions. Instead of “is this stock good?” you get to ask “do I actually want this much momentum exposure, or did it just accumulate?”

You can’t decide whether to keep a bet you don’t know you’re making. Seeing the recipe doesn’t tell you how to cook — it just means you’re no longer cooking blind.

---

If you want to see your own recipe rather than guess at it, Tradune’s Factor X-Ray runs a Fama-French five-factor-plus-momentum regression on your portfolio’s daily returns and shows how it decomposes across market, size, value, profitability, investment and momentum — so a hidden momentum tilt shows up as a number instead of a surprise. This is educational analysis of your existing exposures, not a recommendation to buy, sell, or tilt toward anything.