How to Calculate Portfolio Beta (With a Worked Example)
Portfolio beta is the weighted average of your holdings' betas. Here's the formula, a worked example, what counts as a benchmark, and the edge cases that make naive beta calculations wrong.
Portfolio beta is the weighted average of your individual holdings' betas: multiply each position's beta by its portfolio weight and add the results up. A portfolio beta of 1.2 means that, historically, a 1% market move came with roughly a 1.2% move in your portfolio — in both directions.
What is beta, exactly?
Beta measures how much of an asset's movement is explained by the market's movement. Technically it's the covariance of the asset's returns with the market's returns, divided by the variance of the market's returns. In plain terms:
| Beta | Meaning |
|---|---|
| 1.0 | Moves with the market |
| 1.5 | Amplifies market moves ~50% |
| 0.7 | Dampens market moves ~30% |
| ~0 | Largely independent of the market |
| Negative | Tends to move opposite the market (rare in equities) |
How do I calculate my portfolio's beta?
Portfolio beta = Σ (position weight × position beta) — a weighted average.
Worked example:
| Holding | Weight | Beta | Weight × Beta |
|---|---|---|---|
| AAPL | 40% | 1.2 | 0.48 |
| JNJ | 30% | 0.7 | 0.21 |
| TSLA | 30% | 1.8 | 0.54 |
| Portfolio | 100% | 1.23 |
In a 10% market decline, this portfolio would be expected to fall roughly 12.3% — before any stock-specific news, which beta deliberately ignores.
What details make naive beta calculations wrong?
Getting a usable number means handling four edge cases most spreadsheets skip:
- The benchmark should include dividends. Beta against a price-only index (^GSPC) understates the benchmark's return by 1–2% a year. Use a total-return series (^SP500TR).
- Missing betas shouldn't default to 1.0. New listings and thinly traded assets often lack enough history for a meaningful beta (a common minimum is ~30 return observations). Silently assuming 1.0 drags your portfolio beta toward the market; the honest treatment is to exclude those holdings and renormalize the remaining weights.
- ETFs need a real beta, not a guess. A fund's beta reflects its underlying holdings — an S&P 500 fund sits near 1.0, a tech sector fund well above it. (What a fund actually holds is checkable on our ETF overlap pages.)
- Crypto betas need matched timestamps. Crypto trades 24/7 while equities close at 4pm ET; computing daily-return beta across mismatched closes biases it toward zero. Weekly sampling fixes the mismatch.
These are exactly the rules a PortLens scan applies when it computes your beta — the full recipe, including the benchmark and data sources, is in our methodology.
What is beta actually good for?
- Sizing your downside. Beta × expected market drawdown is a first-order estimate of your systematic loss.
- Risk-adjusting your returns. Metrics like the Treynor ratio (excess return ÷ beta) and Jensen's alpha (return above what your beta predicts) separate skill from simply holding a high-beta portfolio.
- Spotting accidental leverage. A "balanced" portfolio with a computed beta of 1.4 is telling you something the holdings list doesn't.
What are beta's limitations?
Beta is backward-looking, assumes the relationship with the market is stable, and says nothing about company-specific risk (a beta-0.9 stock can still fall 60% on its own news). Correlations also converge in crises, so low-beta portfolios drop more in crashes than their beta implies. Use it as one lens alongside diversification measures like effective holdings.
This article is for information and education only and is not investment advice. See our methodology and disclosures.