Stock Beta Calculator
Calculate stock beta from correlation and standard deviations, or covariance and market variance.
Includes CAPM expected return from risk-free + market rate.
Beta measures how much a stock moves relative to the overall market. A beta of 1 means the stock historically tracks the market closely. A beta of 1.5 means a 10% market move typically produces a 15% move in the stock – more volatile, higher potential returns but bigger drawdowns. Beta near zero means little correlation with market swings. Negative beta is rare but real: some assets like long-dated Treasuries or certain commodity producers run negative beta during equity bear markets.
Two equivalent ways to calculate beta:
From correlation: beta = rho * (sigma_stock / sigma_market)
rho is the Pearson correlation coefficient between the stock and market returns over the chosen history. sigma is standard deviation of returns over the same period. If a stock has sigma = 25% and the S&P 500 has sigma = 15%, with correlation 0.7, then beta = 0.7 x (25/15) = 1.17.
From covariance: beta = Cov(stock, market) / Var(market)
Mathematically identical, and more direct if you have regression output from a spreadsheet.
Beta feeds into the Capital Asset Pricing Model (CAPM):
E(r) = rf + beta x (rm - rf)
rf is the risk-free rate (typically the 3-month T-bill yield). rm is the expected market return (historical S&P 500 average is roughly 10% nominal, 7% real). The term (rm - rf) is the equity risk premium – the extra return demanded for taking on market risk rather than holding the risk-free asset.
Note: beta is backward-looking and unstable. A beta estimated over 2019-2021 data can look very different from one estimated over 2022-2024. Always check the estimation period before using beta in a decision.
How we build and check this calculator
This calculator runs entirely in your browser, so the numbers you enter stay on your device. The math behind it is written by hand and tested against worked examples and standard references before the page goes live.
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