Regression to the Mean in Trading: What Sir Galton Got Wrong and What Indian Traders Must Learn Right

“Bhaiya, stock ₹120 se ₹80 aa gaya hai. Ab toh wapas jayega ₹120 par. Right?”

What is regression to the mean in trading? Discover its psychological roots, statistical truths, and why Indian traders must use it wisely—not blindly.

That’s what we often hear from friends, family, and Telegram trading groups. The idea sounds logical. A stock that’s fallen too much “must” bounce back. It always did before, right?

But here’s the catch: what if it doesn’t?

Welcome to one of the most misunderstood — yet powerful — ideas in stock trading: mean reversion (aka regression to the mean). Born out of a flawed scientific conclusion by Sir Francis Galton, this concept now fuels millions of trading decisions daily — especially in India.

Yet, for Indian stock traders navigating daily volatility, limited capital, and emotional stress, blindly following this idea can be financially fatal.

Let’s dive deep — not just into the concept, but into how you, as a serious trader, can use it with wisdom, not hope.

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📚 What Is Regression Toward the Mean? (Primary Keyword)

In simple words, regression toward the mean refers to this idea:

“Extremes are followed by moderation.”

If a stock moves too far up or down from its average, we expect it to come back to its “normal” level. Like a rubber band that stretches but then pulls back.

But where did this idea come from?

In the 1800s, Sir Francis Galton tried to prove that tall fathers have tall sons. But he found something odd — extremely tall dads had slightly shorter sons, and shorter dads had taller sons. He concluded height “regresses toward mediocrity.”

Wrong.

He forgot the role of mothers, environment, and randomness. But his incorrect logic gave birth to a term that stock traders use to this day — often without understanding its limits.

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📈 Mean Reversion in the Stock Market

In trading, mean reversion is used to identify buying or selling opportunities when prices deviate far from their average.

Examples Indian traders often believe in:

• “This PSU bank has crashed 30%… it’ll bounce back soon!”
  
• “This smallcap was ₹400, now it’s ₹180. Easy 2x from here.”
  

But here’s the problem: not every fall is random.

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🤯 Why Mean Reversion Often Fails in Real-World Trading

Galton’s error is a warning for traders: never assume a fall or rise is purely random.

For mean reversion to be valid, three assumptions must hold:

1. The true value of the stock remains the same between two time points.
   
2. The current price does not reflect that true value.
   
3. The price change is due to random noise, not real change.
   

Let’s break this down with an Indian example:

Imagine a midcap IT company stock crashed from ₹800 to ₹450.
If the fundamentals are unchanged (revenue, profits, future outlook), and the crash was due to bad market sentiment or fake news — it may revert.

But if the drop happened due to loss of clients or regulatory issues, then the “mean” has now shifted. The old average is irrelevant.

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🎭 The Psychology Behind Mean Reversion

Here’s where most traders — especially in India — get trapped.

We are wired to expect fairness. If something went too high, it must come down. If it crashed, it must recover.

It’s the mental shortcut our brain loves.

But stock markets aren’t a Bollywood script. There’s no guarantee of a happy ending.

3 Psychological Errors Traders Make:

• Recency bias: Assuming past patterns will repeat.
  
• Anchoring: Believing ₹400 was the “real” price.
  
• Hope over logic: Confusing mean reversion with wishful thinking.
  

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🧪 Mean Reversion Strategies — The Right Way to Use It

So does this mean you should throw out mean reversion?

Not at all.

It’s powerful when used with context.

Here’s how Indian traders can use it wisely:

✅ Situations Where Mean Reversion Works:

• Overreaction to news: Sudden panic on rumors (e.g., GST hike) with no long-term impact.
  
• Intraday spikes: Stocks moving wildly due to low volume or F&O expiry.
  
• Overbought/Oversold levels: Based on technicals like RSI or Bollinger Bands.
  

❌ Situations Where It Fails:

• Structural changes: Like Yes Bank falling from ₹400 to ₹10.
  
• Fundamental shifts: Sudden drop in earnings, SEBI penalties.
  
• Bubble stocks: Meme rallies with no valuation support.
  

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📊 Mean Reversion ≠ Mean Prediction

A rookie mistake: assuming mean reversion is a prediction tool.

It’s not predictive — it’s descriptive.

It tells you that extreme outliers often don’t last, but it doesn’t say when or why they will correct.

This is why traders often lose money waiting endlessly for a price to return to its previous level.

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🧠 What You Should Remember

• Regression toward the mean is statistical, not emotional.
  
• It assumes randomness, not reality shifts.
  
• Not every fall is temporary; not every rise is unjustified.
  
• Mean reversion works best in liquid, stable, low-volatility setups.
  
• Always combine it with volume, fundamentals, and macro context.
  

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🏏 Desi Analogy: The Cricket Comeback Illusion

Imagine a cricketer who scored 200 runs in a match. Fans expect him to repeat or stay above 100 every game. But most games, he’ll come back to his average of 35–40.

That’s regression to the mean.

Now imagine he got injured and lost form. If fans still expect 100+ scores, they’re ignoring reality and relying on false hope.

Don’t do this with stocks. Don’t expect them to “perform” just because they did once.

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🔑 Quick Takeaways

• Don’t assume price drops will reverse. Check the reason first.
  
• Mean reversion ≠ guarantee. It’s probability.
  
• Combine with technicals and fundamentals.
  
• If stock price is far from mean, ask: “Why?”
  
• Avoid revenge trades hoping for bounce-backs.
  

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📣 Call to Action:

Have you ever waited too long for a stock to bounce back to your buy price?
Did you assume mean reversion, only to be stuck?Comment below or share your experience. Let’s learn together. 🙌
And if this post helped shift your thinking — do share it with fellow traders. Let’s grow the right way.