Key Takeaways
- Mean reversion assumes prices will return to an average—but this isn't always true
- Academic testing often fails to confirm mean reversion in major indices over relevant timeframes
- The strategy can "go wrong spectacularly" according to institutional research
What is Mean Reversion?
Client Question: "If a stock drops 20%, doesn't it have to come back eventually?"
Mean reversion is the opposite of momentum trading. Where momentum traders chase trends, mean reversion traders bet that extreme moves are temporary.
The Core Idea
Mean reversion traders believe:
- Stocks that have dropped sharply are likely to bounce
- Stocks that have surged are likely to pull back
- Prices tend to return to some "normal" level over time
The Appeal
The strategy feels intuitive—"what goes up must come down" and "it can't go down forever." This appeals to our sense of fairness and balance in markets.
What the Research Actually Shows
Academic research on mean reversion tells a more complex story:
Statistical Testing Challenges:
| Test | Finding |
|---|---|
| Augmented Dickey-Fuller test on NASDAQ | Failed to confirm mean reversion |
| Test statistic | -0.397 (not significant at any standard level) |
| Implication | Major indices don't consistently exhibit mean-reverting behavior |
Institutional Research (Aberdeen):
| Finding | Quote |
|---|---|
| Potential for catastrophic failure | "It can go wrong—sometimes spectacularly so" |
| Strategy success rate | "There are many more [strategies] that rely on mean reversion and don't work" |
| Alpha potential | Backtesting confirmed potential, but with significant drawdown risk |
Key Factors That Affect Mean Reversion
| Factor | Impact on Success |
|---|---|
| Magnitude of deviation | More extreme deviations tend to revert more quickly |
| Holding period | Less extreme deviations require more time to normalize |
| Market regime | Strong trends can persist far longer than expected |
| Fundamental changes | New information may permanently alter valuations |
When Mean Reversion Fails
Mean reversion strategies underperform in these environments:
- Strong fundamental regime changes - When the economy shifts structurally
- Structural market disruptions - Major regulatory or geopolitical changes
- Sustained momentum across asset classes - Broad market trends
The "Catching a Falling Knife" Problem
One of the most dangerous aspects of mean reversion trading is buying into a declining stock:
| Scenario | What Happens |
|---|---|
| Stock drops 50% | Mean reversion trader buys, expecting bounce |
| Stock drops another 50% | Now down 75% from original price |
| Company files bankruptcy | Stock goes to zero—no reversion ever occurs |
What Clients Miss
When clients say a stock "has to come back," they're making an assumption that may not be true:
| Assumption | Reality |
|---|---|
| "It dropped too far" | There may be no "correct" price for it to return to |
| "The market overreacted" | The market may be correctly pricing new information |
| "It always comes back" | Individual stocks can go to zero; they don't always recover |
Professional Framing
When clients believe in mean reversion:
"Mean reversion is a real phenomenon in some contexts—over very long periods, broad markets have historically recovered from crashes. But at the individual stock level and over shorter timeframes, the evidence is much weaker. Academic testing on major indices often fails to confirm consistent mean reversion. And institutional research notes that mean reversion strategies can 'go wrong spectacularly.' The phrase 'catching a falling knife' exists for a reason—sometimes stocks that have dropped 50% drop another 50%."
What did academic statistical testing (Augmented Dickey-Fuller) find when examining mean reversion in the NASDAQ index?