What beta means

Beta is a stock’s sensitivity to the overall market. A beta of 1.0 says the stock has tended to move one-for-one with the index; 1.5 says it has swung about half again as hard in both directions; 0.5 says it has moved about half as much. It is the number the WACC post plugged into CAPM (the Capital Asset Pricing Model) to get a cost of equity, and asked you to accept as “illustrative”. This post shows where it comes from and why “illustrative” was the honest word.

Two things beta is not. It isn’t a measure of how risky a business is in the sense of whether it might go bust — a high beta just means a company whose price swings with the market, whatever the business underneath looks like. (A share can be jumpy and still have a low beta, if its jumps don’t line up with the index’s.) And it isn’t stable: it’s estimated from past prices, and past prices change their minds.

The formula

Beta = Covariance(stock returns, market returns) / Variance(market returns)

     = Correlation(stock, market) × ( σ_stock / σ_market )

The second line is the useful one. Beta is correlation (how reliably the two move together) multiplied by relative volatility (how much bigger the stock’s swings are). A stock can have a low beta because it doesn’t follow the market, or because it follows it but barely moves. They’re different situations with the same number.

In practice you regress the stock’s daily (or weekly, or monthly) returns on the index’s returns; beta is the slope of that line.

Worked example: Britannia against the Nifty 50

Daily returns for Britannia (NSE: BRITANNIA) and the Nifty 50 price index, 2 April 2024 to 30 March 2026 (the first return uses the 1 April 2024 close). Source: NSE closing prices via Yahoo Finance (stock, index). Historical data, for illustration only.

  Full two years FY25 (Apr 2024 – Mar 2025) FY26 (Apr 2025 – Mar 2026)
Trading days 493 247 246
Correlation with Nifty 0.28 0.20 0.37
Stock volatility (annualised) 20.6% 21.2% 20.0%
Index volatility (annualised) 13.8% 14.1% 13.5%
Beta 0.42 0.29 0.55
R² (how much the index explains) 0.08 0.04 0.14

Check the identity: 0.28 × (20.6 / 13.8) = 0.42. Same answer as the regression, which is the point — beta is that product.

Three things worth reading off this table.

Britannia is a low-beta stock, at 0.42 over the full window. That fits the textbook: a biscuit company’s sales don’t swing with the economic cycle the way a steel mill’s do, so its shares tend not to swing with the index either.

Beta is unstable. Split the same two years in half and you get 0.29 in one year and 0.55 in the next — the second is nearly double the first. Nothing about the business changed that much. The estimate did. Measured on weekly returns instead of daily, the full-window beta comes out at 0.54. Same stock, same two years, four defensible numbers ranging from 0.29 to 0.55.

The index explains very little. An R² of 0.08 means the Nifty’s daily moves explain only about 8% of the variation in Britannia’s daily returns. The other 92%-odd is the stock doing its own thing — results, input costs, a competitor’s price cut. For a large, liquid stock that is normal, and it is why beta is a statement about tendency, not a prediction for any given day.

The WACC post used a beta of 1.1 for Desi Bites, a fictional small-cap. That’s a reasonable convention for a small packaged-foods company; it is not something you could measure, because Desi Bites has no price history. Even for Britannia, which has plenty, the table above shows why any single beta deserves a range around it.

🧒 Explain it like I'm 10 (optional — skip if this is already clear)

Imagine everyone in your class jumps when the teacher shouts “jump!”. Beta is how high you jump compared to the class average. If the class jumps 10 cm and you jump 15 cm every time, your beta is 1.5. If you jump 4 cm, it’s 0.4.

But here’s the catch: if you sometimes jump high and sometimes don’t bother, someone measuring you this week might get a completely different number from someone measuring you next month. That’s what happened to Britannia’s number in the table.

Common mistakes

  • Treating beta as a fixed property of a company. It’s an estimate from a window of past prices. Change the window or the frequency and it changes — here, from 0.29 to 0.55 on adjacent years.
  • Reading low beta as low risk. Beta only captures the market-wide part of the movement. A stock with a beta of 0.4 and an R² of 0.08 has most of its risk in the part beta doesn’t measure.
  • Plugging a two-decimal beta into CAPM and reporting the cost of equity to two decimals. The input has one significant figure of confidence; the output can’t have more. This is why the sensitivity post exists.
  • Comparing betas measured against different indices. A beta against the Nifty 50 and one against a small-cap index aren’t the same quantity.

Takeaway: beta is correlation times relative volatility — how much a stock has tended to move for a 1% move in the index. Britannia’s is 0.42 over two years, but 0.29 in one of those years and 0.55 in the other, which is roughly all you need to know about treating any beta as a precise number.