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Lesson 3 of 5 8–12% of the exam

How to calculate and interpret beta

Beta measures how much an asset's return moves with the market: β = Cov(Ri, Rm) ÷ σm², or equivalently ρ × σi ÷ σm. The market has a beta of 1 and the risk-free asset 0. A portfolio's beta is the weighted average of its holdings' betas.

6 min cram, 28 min full read. Based on the 2027 CFA® Program Level I curriculum, Portfolio Construction, Learning Module 2. Also part of the 2026 curriculum, so it applies to the November 2026 exam too.

Tailor this to you: take the self-assessment

Before this: Systematic vs nonsystematic risk and return-generating models, Simple Linear Regression in Finance

On the exam

  • Calculate and interpret beta

Calculate and interpret beta. Expect a beta from covariance or from correlation and standard deviations, a portfolio beta that includes cash, and an interpretation item such as what a beta of 1.4 means.

How deeply to learn each part
Know the idea
Understand it in general. It frames other topics, but you will not calculate with it.
Use it
Understand it well enough to solve a question with it. Recognize when it applies.
Memorize
Learn it by heart. The exam will not give it to you.

You know this one. The full lesson is folded away. The takeaways, formulas and checkpoint below are your quick refresher, and the checkpoint is a fair test of whether you still do.

You tested strong here. The full lesson is folded away. The takeaways, formulas and checkpoint below are your quick refresher, and the checkpoint is a fair test of whether you still know it.

Cram mode: the one-screen version of this lesson. Switch to Full for the explanations, worked examples and interactives.

How is beta calculated?

Beta measures how strongly an asset’s return moves with the market’s return. It is the systematic risk of the asset, expressed per unit of market risk. The market’s variance is the yardstick, so beta is the asset’s covariance with the market divided by the market’s variance.

Beta from covariance Memorize
βi=Cov(Ri,Rm)σm2\beta_i = \frac{\text{Cov}(R_i, R_m)}{\sigma_m^2}

Covariance equals correlation times both standard deviations, so one σm cancels and beta can be written from correlation instead.

Covariance from correlation Use it
Cov(Ri,Rm)=ρi,m σi σm\text{Cov}(R_i, R_m) = \rho_{i,m}\,\sigma_i\,\sigma_m
Beta from correlation Memorize
βi=ρi,m σiσm\beta_i = \rho_{i,m}\,\frac{\sigma_i}{\sigma_m}
Rearrange itBeta from covariance: solve for any input
The question asks for
An asset's covariance with the market is 0.0162 and the market's standard deviation is 15.00%. The asset's beta is closest to:

0.0162 ÷ 0.15² = 0.72

Beta0.72

On your calculator
  1. 0.0162÷0.15x²=

x² square

  1. 0.0162ENTER0.15ENTER×÷

ENTER enter (on the HP, puts the number on the stack)

Rearrange itBeta from correlation: solve for any input
The question asks for
A stock's correlation with the market is 0.6. Its standard deviation is 30.00% and the market's is 18.00%. The stock's beta is closest to:

0.6 × 30 ÷ 18 = 1

Beta1

On your calculator
  1. 0.6×30÷18=
  1. 0.6ENTER30×18÷

ENTER enter (on the HP, puts the number on the stack)

What does a beta mean?

A beta of 1.3 means that, on average, when the market’s return is 1 percentage point above normal, this asset’s return is 1.3 points above normal. The market portfolio has a beta of 1 and the risk-free asset has a beta of 0, because T-bills do not move with the market.

Reading a beta
Beta of an assetsensitivity of its return to the market return
  • Above 1: aggressive Use it amplifies market moves; required return above the market’s
  • Equal to 1: moves with the market Memorize the market portfolio itself
  • Between 0 and 1: defensive Use it moves less than the market
  • Zero: no market sensitivity Memorize the risk-free asset; capital asset pricing model (CAPM) return equals Rf
  • Negative: moves against the market Use it rare, for example some hedges; CAPM return below Rf

How is beta estimated in practice?

Regress the asset’s returns on the market’s returns. The fitted line is the security characteristic line , and its slope is beta. A common choice is 60 monthly returns against a broad index.

Security characteristic line Use it
Ri−Rf=αi+βi (Rm−Rf)+eiR_i - R_f = \alpha_i + \beta_i\,(R_m - R_f) + e_i
InteractiveBeta is a slope: regress the stock on the market

Try this 0 of 3

  • Push the stock's σ to 42% and find the correlation that keeps β at 1.00
  • Set the correlation to 0 and look at the fitted line
  • Open the covariance route and compare it with the trap

60 monthly returns: correlation 0.60, stock σ 35%, market σ 21% (annualized). The fitted line has slope β 1.00 and intercept 0.20% a month; the market explains 36% of the stock's variance. Beta is the slope of the line, not the width of the cloud.

−30−1501530Stock return, monthly (%)−15−10−5051015Market return, monthly (%)
  • One month
  • Fitted line, slope β 1.00
  • Slope 1 (moves with the market)
Beta (slope)1.00
Intercept α (monthly)0.20%
Correlation ρ0.60
R² (share explained by the market)0.36
The stock and the market (annualized)
Show working
Show working

β = ρ × σi ÷ σm = 0.60 × 35% ÷ 21% = 1.0000.

The regression on these 60 months gives the same slope: b₁ = 1.0000, intercept 0.2000% a month, R² = ρ² = 0.3600.

Trap: σi ÷ σm alone = 35 ÷ 21 = 1.6667 ignores the correlation; only the part of the stock's risk that moves with the market counts.

Beta from correlation
  1. 0.6×35÷21=β 1.0000
  1. 0.6ENTER35×21÷β 1.0000

ENTER enter (on the HP, puts the number on the stack)

Display: 1.0000

Beta by regression (two-variable statistics)
  1. 2NDDATA2NDCLR WORKclear old data
  2. 15.32ENTER↓22.11ENTER↓X01, Y01
  3. 6.16ENTER↓2.41ENTER↓X02, Y02
  4. 0.6+|-ENTER↓4.03ENTER↓X03, Y03
  5. …same for every point
  6. 2.03ENTER↓1.55ENTER↓X60, Y60
  7. 2NDSTATpress 2ND SET until LIN shows
  8. ↓↓↓↓↓↓↓↓a = 0.2000 (intercept)
  9. ↓b = 1.0000 (slope)
  10. ↓r = 0.6000

2ND second function (the shifted label above a key) · DATA data worksheet · CLR WORK clear the worksheet · ENTER enter (on the HP, puts the number on the stack) · +|- change sign · STAT statistics worksheet

  1. fCLEAR Σ
  2. 22.11ENTER15.32Σ+Y first, then X
  3. display1
  4. 2.41ENTER6.16Σ+Y first, then X
  5. display2
  6. 4.03ENTER0.6CHSΣ+Y first, then X
  7. display3
  8. …same for every point
  9. 1.55ENTER2.03Σ+Y first, then X
  10. display60
  11. 0gŷ,rSTO7a = 0.2000 (intercept: ŷ at x = 0
  12. storeitinR7,sinceΣ+keepsnandthesumsinR1toR6)
  13. x≷yr = 0.6000
  14. 1gŷ,rRCL7−b = 1.0000 (slope: ŷ at x = 1 minus ŷ at x = 0)

f gold shift key · CLEAR Σ clear the statistics registers · ENTER enter (on the HP, puts the number on the stack) · Σ+ add a data point · CHS change sign · g blue shift key · ŷ,r estimated y and correlation · STO store · x≷y swap the last two numbers · RCL recall a stored number

Display: b₀ 0.2000, b₁ 1.0000, r 0.6000

Beta is the slope, not the scatter: a noisy stock can still have a beta of 1.

Change the correlation and the two standard deviations and the cloud regenerates. Beta is the slope of the fitted line, not the width of the scatter: a noisy stock can still have a beta of 1.

The estimate depends on three choices: which index stands in for the market, how often returns are measured (daily, weekly or monthly) and how long the period is. Different choices give different betas for the same stock.

How do you find a portfolio’s beta?

A portfolio’s beta is the weighted average of its holdings’ betas, because covariance is additive.

Portfolio beta Memorize
βp=∑i=1nwi βi\beta_p = \sum_{i=1}^{n} w_i\,\beta_i
Go deeper Adjusted beta, and why betas drift toward 1

Betas estimated from history tend to move toward 1 over time, as companies diversify and mature. Many data providers publish an adjusted beta that blends the raw estimate with 1.

Adjusted beta Know the idea
βadj=23 βraw+13\beta_{adj} = \tfrac{2}{3}\,\beta_{raw} + \tfrac{1}{3}

For a raw beta of 1.8 the adjusted figure is (2 × 1.8 + 1) ÷ 3 = 1.53.

Adjusted beta
  1. 1.8×2+1=÷3= 1.5333
  1. 1.8ENTER2×1+3÷ 1.5333

ENTER enter (on the HP, puts the number on the stack)

Because beta is a regression slope, it comes with a standard error, as in the regression module of Quantitative Methods. A company’s beta also depends on how much debt it carries, a point that returns in Corporate Issuers when betas are adjusted for leverage.

Exam tip Covariance over variance, or correlation times the ratio of standard deviations. If the question gives ρ and two σ values, use the second form; do not square anything.

Memorize this

MemorizeBeta formulas

Memory hook Cov over market variance, and the correlation version is the same fraction with Cov split into ρσiσm, so one σm cancels.

Know it cold βi=Cov(Ri,Rm)σm2=ρi,mσiσm\beta_i = \dfrac{\text{Cov}(R_i,R_m)}{\sigma_m^2} = \rho_{i,m}\dfrac{\sigma_i}{\sigma_m}. Divide by the market’s variance, not its standard deviation.

MemorizeAnchors

AssetBeta
Market portfolio1
Risk-free asset (cash, T-bills)0
Portfolioweighted average of the betas, cash included at 0

Memory hook Cash drags a portfolio beta down in proportion to its weight.

Reading a beta
Beta of an assetsensitivity of its return to the market return
  • Above 1: aggressive Use it amplifies market moves; required return above the market’s
  • Equal to 1: moves with the market Memorize the market portfolio itself
  • Between 0 and 1: defensive Use it moves less than the market
  • Zero: no market sensitivity Memorize the risk-free asset; capital asset pricing model (CAPM) return equals Rf
  • Negative: moves against the market Use it rare, for example some hedges; CAPM return below Rf
Beta from covariance Memorize
βi=Cov(Ri,Rm)σm2\beta_i = \frac{\text{Cov}(R_i, R_m)}{\sigma_m^2}
Quick example

Cov(Ri, Rm) = 0.0300 and σm = 25%. β = 0.0300 ÷ 0.0625 = 0.48.

On your calculator
  1. 0.03÷0.25x²= 0.48

x² square

  1. 0.03ENTER0.25ENTER×÷ 0.48

ENTER enter (on the HP, puts the number on the stack)

Covariance from correlation Use it
Cov(Ri,Rm)=ρi,m σi σm\text{Cov}(R_i, R_m) = \rho_{i,m}\,\sigma_i\,\sigma_m
Quick example

ρ = 0.5, σi = 30%, σm = 20%. Cov = 0.5 × 0.30 × 0.20 = 0.0300.

On your calculator
  1. 0.5×0.3×0.2= 0.03
  1. 0.5ENTER0.3×0.2× 0.03

ENTER enter (on the HP, puts the number on the stack)

Beta from correlation Memorize
βi=ρi,m σiσm\beta_i = \rho_{i,m}\,\frac{\sigma_i}{\sigma_m}
Quick example

ρ = 0.55, σi = 28%, σm = 22%. β = 0.55 × 28 ÷ 22 = 0.70.

On your calculator
  1. 0.55×28÷22= 0.7
  1. 0.55ENTER28×22÷ 0.7

ENTER enter (on the HP, puts the number on the stack)

Security characteristic line Use it
Ri−Rf=αi+βi (Rm−Rf)+eiR_i - R_f = \alpha_i + \beta_i\,(R_m - R_f) + e_i
Quick example

Rf = 2%, β = 1.2, α = 0.5%. If the market returns 8%, the line gives 0.5 + 1.2 × (8 − 2) = 7.7% of excess return, so a return of 9.7% before the firm-specific part.

On your calculator
  1. 8−2=×1.2+0.5+2= 9.7
  1. 8ENTER2−1.2×0.5+2+ 9.7

ENTER enter (on the HP, puts the number on the stack)

Portfolio beta Memorize
βp=∑i=1nwi βi\beta_p = \sum_{i=1}^{n} w_i\,\beta_i
Quick example

30% in a stock with β 1.6, 50% in the market (β 1) and 20% in T-bills (β 0). βp = 0.48 + 0.50 + 0 = 0.98.

On your calculator
  1. 0.3×1.6+(0.5×1)= 0.98
  1. 0.3ENTER1.6×0.5ENTER1×+ 0.98

ENTER enter (on the HP, puts the number on the stack)

Adjusted beta Know the idea
βadj=23 βraw+13\beta_{adj} = \tfrac{2}{3}\,\beta_{raw} + \tfrac{1}{3}
Quick example

A raw beta of 1.8 adjusts to (2 × 1.8 + 1) ÷ 3 = 1.53, pulled toward 1.

On your calculator
  1. 1.8×2+1=÷3= 1.5333
  1. 1.8ENTER2×1+3÷ 1.5333

ENTER enter (on the HP, puts the number on the stack)

How it is asked

  1. Beta from correlation

    ρ 0.55, σi 28%, σm 22%. Beta?

    0.55 × 28 ÷ 22 = 0.70. Traps: 0.43 (inverted ratio), 1.27 (ignores ρ).

  2. Beta from covariance

    Cov 0.0162, σm 15%. Beta?

    0.0162 ÷ 0.0225 = 0.72. Trap: dividing by σm gives 0.108.

  3. Portfolio beta with cash

    60% at 1.1, 30% at 0.5, 10% T-bills. Beta?

    0.66 + 0.15 + 0 = 0.81. Traps: simple average 0.53, cash at beta 1 gives 0.91.

  4. Zero beta

    Under the CAPM, what return does a zero-beta asset have?

    The risk-free rate. Trap: zero.

Exam traps

  • Dividing covariance by σm instead of σm². Beta is covariance over the market's variance.
  • Using σi ÷ σm and forgetting the correlation. A stock can be far more volatile than the market and still have a beta near 1.
  • Ignoring the cash weight in a portfolio beta, or giving T-bills a beta of 1. Cash has beta 0.
  • Thinking a zero-beta asset has a zero expected return. Under the CAPM it earns the risk-free rate.

Checkpoint

4 exam-style questions. About 90 seconds each.

  1. 1A stock's correlation with the market is 0.45. The stock's standard deviation is 32% and the market's is 16%. The stock's beta is closest to:

  2. 2A portfolio holds 40% in a stock with beta 1.5, 35% in a stock with beta 0.8 and 25% in Treasury bills. The portfolio beta is closest to:

  3. 3An asset with a beta of zero has an expected return, under the CAPM, most likely equal to:

  4. 4An asset's covariance with the market is 0.0243 and the market's standard deviation is 18%. The asset's beta is closest to:

Key takeaways

  • β = Cov(Ri, Rm) ÷ σm² = ρ × σi ÷ σm.
  • Market β = 1, risk-free β = 0, and a portfolio's beta is the weighted average of its holdings' betas.
  • Beta is the slope of a regression of the asset's returns on the market's; the estimate depends on the index, interval and period.
Beta from covariance Memorize
βi=Cov(Ri,Rm)σm2\beta_i = \frac{\text{Cov}(R_i, R_m)}{\sigma_m^2}
Quick example

Cov(Ri, Rm) = 0.0300 and σm = 25%. β = 0.0300 ÷ 0.0625 = 0.48.

On your calculator
  1. 0.03÷0.25x²= 0.48

x² square

  1. 0.03ENTER0.25ENTER×÷ 0.48

ENTER enter (on the HP, puts the number on the stack)

Covariance from correlation Use it
Cov(Ri,Rm)=ρi,m σi σm\text{Cov}(R_i, R_m) = \rho_{i,m}\,\sigma_i\,\sigma_m
Quick example

ρ = 0.5, σi = 30%, σm = 20%. Cov = 0.5 × 0.30 × 0.20 = 0.0300.

On your calculator
  1. 0.5×0.3×0.2= 0.03
  1. 0.5ENTER0.3×0.2× 0.03

ENTER enter (on the HP, puts the number on the stack)

Beta from correlation Memorize
βi=ρi,m σiσm\beta_i = \rho_{i,m}\,\frac{\sigma_i}{\sigma_m}
Quick example

ρ = 0.55, σi = 28%, σm = 22%. β = 0.55 × 28 ÷ 22 = 0.70.

On your calculator
  1. 0.55×28÷22= 0.7
  1. 0.55ENTER28×22÷ 0.7

ENTER enter (on the HP, puts the number on the stack)

Security characteristic line Use it
Ri−Rf=αi+βi (Rm−Rf)+eiR_i - R_f = \alpha_i + \beta_i\,(R_m - R_f) + e_i
Quick example

Rf = 2%, β = 1.2, α = 0.5%. If the market returns 8%, the line gives 0.5 + 1.2 × (8 − 2) = 7.7% of excess return, so a return of 9.7% before the firm-specific part.

On your calculator
  1. 8−2=×1.2+0.5+2= 9.7
  1. 8ENTER2−1.2×0.5+2+ 9.7

ENTER enter (on the HP, puts the number on the stack)

Portfolio beta Memorize
βp=∑i=1nwi βi\beta_p = \sum_{i=1}^{n} w_i\,\beta_i
Quick example

30% in a stock with β 1.6, 50% in the market (β 1) and 20% in T-bills (β 0). βp = 0.48 + 0.50 + 0 = 0.98.

On your calculator
  1. 0.3×1.6+(0.5×1)= 0.98
  1. 0.3ENTER1.6×0.5ENTER1×+ 0.98

ENTER enter (on the HP, puts the number on the stack)

Adjusted beta Know the idea
βadj=23 βraw+13\beta_{adj} = \tfrac{2}{3}\,\beta_{raw} + \tfrac{1}{3}
Quick example

A raw beta of 1.8 adjusts to (2 × 1.8 + 1) ÷ 3 = 1.53, pulled toward 1.

On your calculator
  1. 1.8×2+1=÷3= 1.5333
  1. 1.8ENTER2×1+3÷ 1.5333

ENTER enter (on the HP, puts the number on the stack)

All Portfolio Construction formulas, every lesson

Practice exam-style questions on Portfolio Risk and Return: Part II (CAPM and Performance Measures)

Questions about this lesson?

Where this comes back

Questions candidates ask

How do you calculate beta from correlation?

Multiply the correlation between the asset and the market by the asset's standard deviation, then divide by the market's standard deviation: β = ρ × σi ÷ σm. For example 0.6 × 35% ÷ 21% = 1.00.

What does a beta of 1.5 mean?

On average, when the market return is 1 percentage point above its normal level, the asset's return is 1.5 points above its normal level, and the same on the downside. It has more systematic risk than the market, so the CAPM gives it a higher required return.

How do you calculate portfolio beta?

Multiply each holding's beta by its weight in the portfolio and add the results. Cash and T-bills count with a beta of zero, so a larger cash weight lowers the portfolio beta.

Spotted an error? Tell us and we will fix it.

  1. The capital market line
  2. Systematic vs nonsystematic risk and return-generating models
  3. How to calculate and interpret beta
  4. The CAPM and the security market line
  5. Sharpe ratio, Treynor ratio, M² and Jensen's alpha

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