Mean Reversion
When prices stretch too far
Imagine a rubber band. You can stretch it, but the further it goes, the harder it pulls back. Prices behave similarly — sometimes.
Mean reversion is the observation that when a price moves too far from its average, it has historically tended to snap back. Not always. Not predictably. But often enough that it's one of the most studied patterns in markets.
Where momentum says “follow the trend,” mean reversion says “the trend has gone too far.”
They're opposite assumptions. And understanding both gives you a more complete picture of how markets behave.
How it works
- Calculate the moving average of the price over the last N days
- Measure the distance between the current price and that average
- If the price is too far above the average (above a threshold) → mean reversion practitioners would typically interpret this as overextended
- If the price is too far below → they would typically consider it as potentially oversold
- When it crosses back to the average → the signal would reset
The two parameters that define the strategy:
- SMA window — how many days for the average (shorter = more sensitive)
- Threshold — how far is “too far” (higher = fewer signals, but historically more pronounced ones)
Educational content only — not investment advice, recommendations, or a suggestion to act. Past performance is not indicative of future results. Your decisions are your own. Full disclaimer.
When it works, when it doesn't
Tends to work well in
Range-bound markets — prices that oscillate around a stable level without a strong trend.
Tends to struggle with
Regime changes. When something fundamentally shifts (earnings collapse, sector rotation, macro shock), what looks “too far” might actually be the new normal. The rubber band breaks.
The key insight: Mean reversion is an assumption of stability. The assumption is that the current deviation is temporary and prices will return to their historical norm. Whether that assumption holds depends on context.
See it in action
Pick a ticker and adjust the SMA window and threshold to see how mean reversion would have historically performed.
What to notice:
- The distance line shows how far price is from its average — watch how it oscillates
- Threshold lines (red dashed) mark where signals trigger — move them to see how sensitivity changes
- Flat periods (position = 0) mean the strategy is waiting — not every day needs a trade
- Compare with buy & hold — sometimes doing less is doing more
Your turn
Consider how this pattern relates to investment decisions in general. When someone buys an asset after a drop — are they assuming the price has fallen too far and will revert?
That's mean reversion thinking. There's no right answer. But knowing which assumption you're operating under helps you understand your own decisions — and whether they worked for the reason you thought.
Reflect in your JournalWhat you've learned
- -Mean reversion is the observation that prices stretched far from their average have historically tended to snap back — but not always.
- -Two parameters define the strategy: the SMA window (how many days for the average) and the threshold (how far is 'too far').
- -It works best in range-bound markets and tends to fail during regime changes — when what looks 'too far' is actually the new normal.
- -Mean reversion is the opposite assumption to momentum: one assumes continuation, the other stability. Understanding both gives you a more complete picture.
Want to test this?
Many experienced investors suggest practicing with a paper money account on a reputable broker before risking real capital. Many brokers offer free simulated trading environments where you can test strategies with real market data and no financial risk.
Paper trading lets you build confidence, understand execution, and see how a strategy behaves in real time — without the emotional weight of real money on the line.
Important
Everything on this platform is educational and didactic in nature. We do not provide investment advice, financial advisory, or recommendations to buy or sell any financial instrument. Past performance is not indicative of future results. All strategies shown are historical simulations for learning purposes only. Always do your own research and consult a qualified financial advisor before making investment decisions.
Educational content · Not investment advice or recommendations
We're educators, not advisors. Your decisions are your own. Disclaimer