Portfolio Beta Calculator

For each holding, enter a ticker, portfolio weight as a percentage, and beta estimate. The calculator multiplies each beta by its share of the accepted total weight, then adds the weighted values. The result is one coefficient for the portfolio relative to the estimates you supplied.

The weight total must be 100% within 0.01 percentage points. The calculator normalizes a total inside that tolerance. It rejects repeated tickers, incomplete rows, weights outside 0% to 100%, and nonfinite results. Beta may be zero or negative. The displayed coefficient bands are below 0.8, 0.8 through 1.2, and above 1.2; these labels do not judge suitability or total risk.

The scenario table multiplies the portfolio beta by benchmark changes from negative 20% to positive 20%. The custom slider applies the same linear calculation to a selected change. Negative beta produces a modeled move in the opposite direction. Neither output predicts what the portfolio will actually return.

For a meaningful comparison, use beta estimates built from the same benchmark, observation window, return frequency, and return basis. The calculator does not retrieve historical price series or recalculate individual betas. It stores the ticker, weight, and beta values in this browser; current prices are not part of its inputs.

Enter one holding with a 60% weight and beta 1.10, and another with a 40% weight and beta 0.30. The weighted beta is 0.78: 0.60 × 1.10 plus 0.40 × 0.30. In the linear scenario, a benchmark rise of 10% maps to a portfolio change of 7.8%, while a benchmark fall of 20% maps to a change of negative 15.6%.

The displayed sensitivity relative to beta 1 is negative 22%. If the second holding beta changes from 0.30 to 0.60, the weighted beta becomes 0.90. These are arithmetic scenarios, not forecasts of portfolio returns.

Use this calculation to combine holding beta estimates into one portfolio coefficient when checking allocation changes or comparing proposed mixes against the same benchmark. The result is interpretable only when the underlying beta estimates are comparable.

Use drawdown or volatility measures when the question concerns observed loss depth or total variation. Use concentration and overlap measures when repeated exposures matter. Portfolio beta is one benchmark sensitivity measure, not a complete risk assessment.

Do not combine estimates measured against different benchmarks, periods, frequencies, or return bases without noting the mismatch. Enter weights as percentages, such as 60 rather than 0.60. Check that every row has a distinct ticker and that all weights add to 100% within the stated tolerance.

Do not treat a beta of 0.78 as a promise that every decline will be 22% smaller. It is a coefficient used in a linear scenario. Review drawdowns, volatility, concentration, liquidity, and nonlinear exposures separately. A negative beta can imply a large modeled move in the opposite direction.

The model assumes a linear relationship to one common benchmark and treats supplied beta estimates as comparable and stable. Historical estimates depend on benchmark, observation window, return frequency, return basis, and data quality. The tool does not estimate alpha, a risk free return, total volatility, residual risk, liquidity, credit risk, fees, taxes, or nonlinear exposure. Correlations and beta can change, especially during market stress. Negative beta is permitted and does not mean low total risk.

Portfolio beta summarizes benchmark sensitivity. Maximum Drawdown measures the depth of observed losses, while Sharpe Sortino Ratio compares returns with volatility or downside deviation. These measures describe different properties.

Use Portfolio Rebalancer to estimate trades for a target allocation, or ETF Overlap Detector to identify repeated fund holdings. Those tools examine allocation and overlap, not the beta calculation itself.