Expected Return Calculator

The expected return calculator computes a probability-weighted average return from investment scenarios. Add each possible outcome, enter its probability, and enter the return for that outcome. The calculator multiplies each return by its probability, adds the contributions, and shows a probability check so you can see whether the scenario set totals 100%.

This page is informational, not investment advice. Expected return is a modeling tool, not a guarantee. It can organize assumptions for a stock, fund, project, or portfolio, but actual results can land outside your scenario range.

What this calculator does

Expected return is an average across possible futures. A scenario with a high probability receives more weight than a scenario with a low probability. A severe downside case can still matter even if it is unlikely, because its return may be large enough to pull the average down. The calculator does not assume a normal distribution and does not ask for volatility; it simply uses the probabilities and returns you provide.

This is different from realized performance in the rate of return calculator, which works backward from initial value, final value, time, and cash flows. It is also different from the Sharpe ratio calculator, Sortino ratio calculator, and Treynor ratio calculator, which compare return with different definitions of risk. Expected return estimates reward before the outcome is known; risk-adjusted ratios evaluate whether that reward is attractive relative to uncertainty.

Formula

For each scenario, convert probability into a decimal and multiply by the return:

$\text{scenario contribution}_i = \frac{p_i}{100} \times r_i$

Then add the scenario contributions:

$E(r) = \sum_i \left(\frac{p_i}{100} \times r_i\right)$

The calculator leaves returns in percentage-point form. If a 60% probability is paired with a 15% return, the contribution is 9 percentage points. Loss scenarios use negative returns, so they subtract from the total.

Example: calculating expected return

The default scenario list has two outcomes: Downside with 40% probability and -5% return, and Upside with 60% probability and 15% return. The first contribution is:

$\frac{40}{100} \times -5\% = -2\%$

The second contribution is:

$\frac{60}{100} \times 15\% = 9\%$

The calculator adds those contributions:

$E(r) = -2\% + 9\% = 7\%$

The primary result is 7% as the probability-weighted average return. The results list shows total probability of 100%, number of scenarios 2, and a probability check that says the entries add to 100%. In the scenario contribution group, the default rows display 40.00% × -5.00% = -2.00% and 60.00% × 15.00% = 9.00%.

How investors interpret it

Expected return is useful for comparing alternatives before the result is known. A project with a 7% expected return may look better than one with a 5% expected return, but the conclusion depends on risk. A 7% expected return built from a small chance of a large gain and a large chance of a loss is not the same as a stable 7% bond-like assumption. The average hides the shape of the distribution.

Use the probability check seriously. If probabilities add to 130%, the weighted average is inflated because the scenario set is overweighted. If they add to 70%, the result is missing 30% of possible outcomes. The calculator warns either way, but it does not normalize probabilities automatically; that preserves your inputs and makes the assumption error visible.

Probability-weighted vs. CAPM expected return

This calculator uses explicit scenarios. CAPM uses a different structure: risk-free return plus beta times the market risk premium. For beta-driven modeling, estimate beta with the stock beta calculator, then compare the required return with your scenario-based expected return.

Scenario analysis is often easier to explain because each row has a narrative: recession, base case, expansion, product success, or failed launch. CAPM is more compact and market-based, but it depends heavily on beta and market premium assumptions. Many analysts use both to test whether a conclusion survives different methods.

Limitations and tips

The hardest part is not the arithmetic; it is choosing realistic probabilities and returns. Overconfident probabilities can make a weak investment look precise. Missing tail risks can make expected return too high. Correlated scenarios can also distort portfolio analysis if every asset is assumed to perform independently during stress.

Use at least three scenarios when possible: downside, base, and upside. Add a severe but plausible stress case if a large loss would change the decision. Keep scenario dates and return horizons consistent. After calculating expected return, review volatility, downside deviation, beta, liquidity, fees, taxes, and position size before comparing investments.

Sources

• FINRA, Risk — investor education on risk types and risk-return trade-offs.
• Corporate Finance Institute, Expected Return — probability-weighted expected return concepts and formulas.