Calculator
Jensen's Alpha (per year)
+2.09 pp
Market Premium
6.20 pp
Actual vs Fair
12.8% vs 10.7%
Skill vs Exposure Analysis
The CAPM fair return for a beta of 1.05 was 10.71% (4.2% risk-free + 1.05 x 6.20% market premium), but the portfolio delivered 12.8%. Jensen's alpha of +2.09 percentage points per year is genuine risk-adjusted outperformance — return the strategy did not need market exposure to explain.
Jensen's alpha applies the CAPM single-factor model, which is a simplification of how returns are generated. It is a backward-looking estimate from the inputs you provide, not a guarantee of manager skill or future performance.
When a fund beats its benchmark, the natural question follows: was that outperformance earned by skill, or was it just the expected reward for taking more market risk? Jensen's alpha, introduced by Michael Jensen in 1968, answers that question with more rigour than a raw return comparison. It starts from the Capital Asset Pricing Model (CAPM), which defines the fair return for any given level of market risk (beta), then measures the gap between the return actually delivered and the return that risk level should have produced. That gap is the alpha — positive if the fund outdid its risk-adjusted expectation, negative if it fell short. The distinction matters enormously for Australian investors choosing between active funds and low-cost index options in or out of super. A fund returning 18% in a year the ASX 200 returned 13% sounds impressive — until you learn it ran a beta of 1.5, in which case CAPM says it 'should' have returned about 17.5%, and true alpha is barely half a point, likely less than its management fee. Conversely, an income fund returning 9% against a 12% market can still earn positive alpha if its beta was low. Jensen's alpha converts the vague impression of beating the index into a number that has already been priced for risk, and it remains the most cited statistic for deciding whether an active manager deserves their fee.
Jensen's alpha is computed in two steps. First, CAPM calculates the fair (expected) return for the portfolio's beta: Expected Return = Risk-Free Rate + Beta × (Benchmark Return − Risk-Free Rate). The term (Benchmark − Risk-Free) is the market risk premium — the reward for carrying one full unit of market risk. Multiplying it by beta scales that reward to the actual exposure taken, and adding the risk-free rate restores the no-risk baseline. Second, alpha is simply the difference: Actual Return − Expected Return. Earn more than your beta-priced fair share and alpha is positive; earn less and it is negative. The calculator shows every leg of that arithmetic so nothing hides inside the headline. One caveat is built into CAPM itself: it attributes all return to a single factor — the market. In reality size, value and momentum exposures also shape results, so a 'skilled' manager may simply be harvesting a known factor premium. For Australian inputs, a sensible risk-free rate is the 10-year Australian Government bond yield or the bank bill rate, and franking credits should be included in returns where they form part of what you actually compare.
A published fund return is post-fee, but claimed skill must exceed the fee to be worth anything. A fund with alpha of +0.6% charging a 0.9% management fee contributes negative value against a passive index at the same beta. Subtract the fee from the alpha before crediting the manager — fee-adjusted alpha is the only alpha you keep.
An alpha of 0.3% over three years is not evidence of skill; it sits well inside the noise band of return volatility. Most short-horizon fund alphas are statistically indistinguishable from zero. Treat any alpha smaller than roughly a point per year with scepticism, and require persistence across market cycles before calling it repeatable ability.
Alpha is defined relative to the benchmark used, and a mismatch manufactures fake alpha. An Australian small-cap fund judged against the S&P/ASX 200 shows phantom alpha whenever small caps run hot; a global fund benchmarked only against the ASX looks artificially uncorrelated. Use the index the manager genuinely invests against.
For each actively managed fund in your super or trading account, enter its average annual return, the matching benchmark's return, the fund's beta and the current Australian Government bond yield. Subtract the management fee from the resulting alpha. Funds failing that test have been quantifiably outdone by a cheaper passive alternative at identical risk.
One calculation is one data point from one model. Screen first with alpha, then check consistency across years, factor exposures and turnover before acting. The goal is a shortlist rewarding deeper diligence — not an instant switch triggered by a single good or bad year.
The risk-free rate anchors CAPM's fair-return bar, so re-run the numbers whenever the RBA cycle or bond yields move materially. A fund's apparent alpha can shrink or expand purely because the risk-free assumption moved — keeping that input current keeps the verdict honest.
Nate held an aggressive resources-heavy fund that beat the ASX 200 by four points last year and resisted moving to an index option in his super. The calculator showed the fund's beta was 1.4, meaning CAPM's fair return sat above the index itself — alpha was negative. The outperformance was amplified market risk, and Nate switched to a low-cost index fund delivering the same exposure without the active-fee markup.
Paula's fully franked income fund trailed the market by three points and she considered selling. Its beta was just 0.65, so the expected return for the risk carried was far below the market's result — alpha was strongly positive. The fund was capturing income with minimal market exposure exactly as designed. She kept it and stopped benchmarking a shield by the standards of a sword.
The Nguyens interviewed two advisers, each brandishing strong recent performance. The first's alpha vanished after subtracting a 1.1% fee; the second's smaller alpha stayed positive net of 0.4%. The maths cut through the marketing: the second delivered more risk-adjusted value after cost, and that is where the family's SMSF money went.
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Financial Chaos Analyst
Ivy Sinclair-Wren is a Financial Chaos Analyst covering investing, AI, wealth psychology, and the emotional consequences of opening finance apps during market crashes. Based in Melbourne, she specializes in demystifying the Australian tax code and helping users navigate the intersection of spreadsheet logic and human irrationality.