Portfolio market risk.

Portfolio beta measures systematic risk vs market: weighted average of individual stock betas. Beta of 1.0 matches market risk. 1.5 = 50% more volatile than market. 0.5 = 50% less volatile. Used to gauge portfolio risk exposure and required return via CAPM model.

Example: 40% Tesla (beta 2.0) + 40% Microsoft (beta 1.0) + 20% Coca-Cola (beta 0.5). Portfolio beta = (0.4 × 2.0) + (0.4 × 1.0) + (0.2 × 0.5) = 0.8 + 0.4 + 0.1 = 1.3. Portfolio is 30% more volatile than market. 10% market drop = 13% portfolio drop expected.

Beta interpretation: 0 = uncorrelated with market (rare). 0-1 = defensive (utilities, consumer staples). 1.0 = market-like (S&P 500 ETF). 1.0-1.5 = above-market risk. 1.5+ = aggressive (tech, biotech, leveraged ETFs). Negative beta = inversely correlated (gold, some hedge strategies). Use beta for: sizing positions, calculating expected returns, hedging market exposure. Limitation: beta is historical and unstable - past beta may not predict future.

Quick example

With stock a weight of 40% and stock a beta of 2 (plus stock b weight of 40% and stock b beta of 1), the result is 1.30. Change any figure and watch the output shift — it's often more useful to see the pattern than to memorise the formula.

Which inputs matter most

You enter Stock A Weight %, Stock A Beta, Stock B Weight %, Stock B Beta, and Stock C Weight %. The rate and the time horizon usually dominate — compounding means a small change in either reshapes the final figure more than a similar shift in contribution size. Test this by doubling one input at a time.

What's happening under the hood

Portfolio beta = sum of (weight × individual beta) across all holdings. The formula is listed in full below. If the number looks off, you can retrace the calculation by hand — that's the point of showing the working.

Where this fits in planning

This is a "what-if" tool, not a forecast. Use it to test ideas before committing: what happens if the rate is 2% lower than hoped, what happens if you add five more years. The value is in the scenarios you run, not the single answer you get from the defaults.

What this doesn't capture

Steady-rate math ignores real-world volatility. Actual returns are lumpy; sequence-of-returns risk matters most in drawdown; fees and taxes drag on compound growth; and behaviour changes in drawdowns can reduce outcomes below the projection. Treat the number as one scenario, not a forecast.