Factor Investing Calculator
Factor return decomposition.
Calculate expected portfolio return using a Fama-French style factor model from market return, beta, and small/value factor exposures.
What this tool does
Factor investing models expected returns by breaking down performance into distinct sources: broad market movement, value exposure, and size exposure. This calculator takes your portfolio's sensitivity to each factor—its beta, value loading, and size loading—along with the historical premiums associated with value and size investing, and estimates what portion of expected return comes from each source. The result shows your portfolio's total expected return split into contributions from market beta, value factor exposure, size factor exposure, and alpha. Market return and your portfolio's market beta typically drive the largest portion of the result, while value and size loadings shape returns when those factors are active. This calculation illustrates how diversified factor exposure works in theory and is useful for understanding portfolio construction logic. Note that this models historical factor relationships and does not account for transaction costs, timing shifts in factor performance, or changing market conditions.
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Formula Used
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Disclaimer
Results are estimates for educational purposes only. They do not constitute financial advice. Consult a qualified professional before making financial decisions.
Factor investing calculator estimates expected returns using Fama- factor model: Expected Return = β × Market Return + Value Loading × Value Premium + Size Loading × Size Premium + Alpha. Captures returns beyond simple market exposure (beta) - small-cap and value stocks historically outperform with higher loadings.
Example: market return 7%, beta 1.0 (matches market), value loading 0.5, value premium 3%, size loading 0.3, size premium 2%. Expected return = 7% + (0.5 × 3%) + (0.3 × 2%) + 0% alpha = 9.1%. Tilting toward value and small-cap factors adds 2.1% expected annual return.
Major factors (Fama- 3-factor + momentum + quality + low-vol): (1) Market (beta), (2) Value (book-to-market), (3) Size (small-cap premium), (4) Momentum (winners keep winning), (5) Quality (high ROE), (6) Low Volatility (low-vol stocks beat high-vol). Smart beta ETFs offer factor exposure cheaply (0.10-0.30%). Five Factor Model now standard academic framework. Real factor premiums lower than historical (~1-3% vs 3-5% backtests).
Quick example
With market return of 7% and portfolio beta of 1 (plus value premium of 3% and value factor loading of 0.5), the result is 9.10%. 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 Market Return %, Portfolio Beta, Value Premium %, Value Factor Loading, and Size Premium %. 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
Fama- three-factor model: market beta + value premium + size premium + alpha. 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.
Using this well
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. The number represents one scenario rather than a forecast.
1β×7%+0.5×3%+0.3×2%+0% = 9.10%.
Inputs
This example uses typical values for illustration. Adjust the inputs above to match a specific situation and see how the result changes.
Sources & Methodology
Methodology
Applies the Fama three-factor model: expected return = (beta × market return) + (value loading × value premium) + (size loading × size premium) + alpha.
References
Frequently Asked Questions
What are factor premiums?
Are factor premiums shrinking?
How to access factors?
Single factor vs multi-factor?
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