Momentum & Factor Models

Where mean reversion bets a stretched price snaps back, momentum bets the opposite: that a trend already in motion tends to keep going. Factor models formalize this and other persistent drivers of returns into rules-based portfolios.

The Concept

Betting the Trend Continues, Not Reverts

Momentum is the observed tendency for assets that have recently performed well to keep outperforming over the following months, and for recent laggards to keep lagging — the mirror image of the mean-reversion idea from the previous lesson. It's one of the most extensively studied and persistent patterns in academic finance, showing up across stocks, sectors, currencies and commodities, though it isn't guaranteed to continue and can suffer sharp, sudden reversals ("momentum crashes").

A factor is a specific, measurable characteristic that has historically been associated with different returns across a group of securities. Momentum is one factor; others widely studied include value (cheap stocks relative to fundamentals outperforming expensive ones), quality (financially healthy companies outperforming weaker ones), and size (smaller companies historically carrying a different risk/return profile than larger ones).

A factor model builds a portfolio systematically around one or more of these characteristics — ranking a universe of stocks by a factor score and holding the top slice — rather than relying on any single stock-specific thesis. The appeal is diversification across many small, uncorrelated bets on the same measurable driver, instead of concentrated bets on individual company stories.

⚖️ Illustrative Example: Ranking a Universe by 6-Month Momentum

A simple momentum factor ranks stocks by their trailing 6-month return and holds the top decile. Five illustrative stocks from a hypothetical universe:

Stock6-Month ReturnMomentum RankIllustrative Action
Stock A+42%1Hold (Top Momentum)
Stock B+31%2Hold (Top Momentum)
Stock C+8%3No Position
Stock D-6%4No Position
Stock E-19%5No Position (Bottom Momentum)

A momentum factor strategy holds Stocks A and B not because of any specific view on their businesses, but purely because their trailing return ranks them at the top of the universe — the same rule applied systematically across hundreds or thousands of names.

Watch For This

5 Things to Know About Momentum & Factors

  1. Momentum and mean reversion aren't contradictions — they tend to operate over different timeframes (momentum over months, mean reversion often over days to weeks) and different assets can favor one over the other.
  2. Momentum crashes are a known, documented risk — momentum strategies have historically suffered sharp, sudden reversals, particularly around market turning points.
  3. Factors can go through long periods of underperformance — value underperformed growth for much of the 2010s, a reminder that "persistent" doesn't mean "constant."
  4. Factor investing is diversification across bets, not stocks — a well-built factor portfolio holds many names, so no single company's news should dominate the outcome.
  5. Factors can crowd — when many funds chase the same factor definitions, the resulting mass buying/selling can itself become a source of risk during unwinds.
Put It Into Practice

4 Things to Check Before Trusting a Factor Strategy

📏 Define the Lookback Precisely

  • "Momentum" can mean 3-month, 6-month, or 12-month trailing return — the choice materially changes which names rank highest.

🔄 Set a Rebalancing Rule

  • Rankings shift constantly — decide how often you'll re-rank and rebalance the holdings, and how much turnover (and cost) that implies.

🧺 Diversify Across Names

  • The statistical edge in a factor comes from holding many names, not a concentrated handful — narrow it too much and it stops behaving like a factor bet.

🛑 Plan for Drawdowns in the Factor Itself

  • Expect the factor to underperform for extended stretches — a plan for riding that out matters as much as the factor definition.
🧮 Related lessons: Mean Reversion (previous in this track) covers the opposite bet, and Backtesting (next) shows how to properly test a factor rule like this before risking real money.
Worth knowing: this lesson explains the historical, academic evidence behind momentum and factor investing using illustrative numbers and historical framing — it isn't personalized financial advice, and no strategy described here is a recommendation to trade. Past patterns, including momentum, are never guaranteed to repeat. Speak to a licensed advisor about what's appropriate for your situation.
Activity

Try It Yourself: Momentum Ranker

Enter trailing returns for up to 6 assets — see them ranked by momentum, with the top slice highlighted as an illustrative "hold" group.

Asset6M ReturnRankAction

Model: assets are sorted by trailing return, highest first, and the top N are marked "Hold" — a simplified illustration of how a momentum factor ranks a universe, not a real trading signal.

End of Lesson

Quick Check: 5 Questions

Answer all five, then hit "Check My Answers" to see how you did. Get one wrong? No problem — the explanation will show you exactly why.

0/5
Nice work — review any explanations below to lock it in.
1. What does a momentum strategy bet on?
Momentum is the tendency for recent winners to keep outperforming and recent laggards to keep lagging — the mirror image of mean reversion.
2. What is a "factor" in this context?
Momentum, value, quality and size are all examples of factors — measurable characteristics linked to differences in historical returns.
3. In the illustrative example, why were Stocks A and B held?
A momentum factor strategy ranks purely on trailing return, holding the top slice regardless of any company-specific view.
4. What is a documented risk specific to momentum strategies?
Momentum strategies have historically suffered sharp, sudden reversals known as momentum crashes, especially around market turning points.
5. Why does the lesson recommend diversifying across many names in a factor strategy?
Factor investing works as diversification across many small, uncorrelated bets on the same measurable driver, not concentrated single-stock theses.
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Next Up: Backtesting

You've now seen two opposing rules-based edges — mean reversion and momentum. The next lesson covers how to properly test either one against history before risking real money.