What Is a Good Alpha in Investing? Stocks and Funds

A good alpha is any positive number, because alpha above zero means you beat the benchmark after adjusting for the risk you took. In practice, an alpha of 1% to 3% per year is respectable for an active fund, 3% to 5% is strong, and anything above 5% sustained over a decade is rare enough to deserve suspicion before applause. Most active managers deliver negative alpha after fees.

That benchmark is easy to state and easy to misuse, because alpha is a comparison, and a comparison is only as honest as the thing you compare against. Change the benchmark and you change the alpha without changing a single trade. Here is the practical version: what alpha actually measures, what counts as good in the four places people ask about it, and why the alpha you measure in a backtest is usually larger than the alpha you will live with.

What does alpha measure in investing?

Alpha measures the return a portfolio earned beyond what its exposure to the market alone would predict. If a fund returned 12% while its benchmark returned 10%, and the fund carried exactly average market risk, its alpha is roughly 2%. That excess is the part attributed to skill, selection, or timing rather than to simply being invested.

The word carries an implicit claim, which is why it gets abused in marketing. Alpha says the return came from something the manager did, not from the market rising. A fund that beat the S&P 500 by 4% in a strong year while holding far riskier stocks did not necessarily generate alpha. It took more risk and got paid for it, which is a different thing and a much cheaper thing to replicate.

How do you calculate alpha?

The standard form is Jensen's alpha, which uses the capital asset pricing model to set the expected return, then subtracts it from what actually happened:

Alpha = Actual return - [Risk-free rate + Beta x (Benchmark return - Risk-free rate)]

Work an example. A fund returns 14% over a year. The risk-free rate is 4%, the benchmark returns 11%, and the fund's beta is 1.2. Expected return is 4% + 1.2 x (11% - 4%) = 12.4%. Alpha is 14% - 12.4% = 1.6%. Note what beta did to the answer: the raw excess over the benchmark was 3%, but because the fund carried 20% more market risk than the benchmark, most of that excess was simply compensation for risk. Only 1.6% was unexplained.

Two inputs decide the result, and both are choices rather than facts. Beta is estimated from a sample of past returns and moves depending on the window you use. The benchmark is selected. A small-cap value fund measured against the S&P 500 will show flattering alpha in years when small-cap value outperforms, and the alpha vanishes the moment you switch to a small-cap value index. This is the single most common way alpha figures are inflated, and it is usually not deliberate.

What is a good alpha for a stock?

For a single stock, alpha above zero over a multi-year period means the stock outperformed what its beta predicted, but the number is far noisier than it looks. One company's return over a few years is dominated by company-specific events: a product cycle, a lawsuit, an acquisition, a change of management. Attributing that to skill makes little sense when you are the one who picked the ticker.

Treat single-stock alpha as description rather than evidence. A stock with 6% annualized alpha over five years tells you the past was good. It says nothing reliable about the next five, and the figure will be dominated by whichever handful of quarters happened to break the company's way.

What is a good alpha for a mutual fund?

For a mutual fund, judge alpha after fees and across at least a full market cycle, and set expectations low, because the base rate is unkind. Positive net alpha of 1% to 2% per year sustained over ten years or more puts a fund in a small minority. The majority of active funds show negative alpha once the expense ratio is subtracted, and the persistence of positive alpha from one decade to the next is weak.

The arithmetic behind that is simple and unforgiving. A fund charging 0.75% annually needs 0.75% of gross alpha just to break even against a cheap index fund. It has to be genuinely skilled to arrive at zero. This is why an alpha figure quoted before fees is close to meaningless for a buyer, and why the fee is the first number to check.

What is a good alpha for a portfolio?

For your own portfolio, the honest bar is different, because you should compare against the portfolio you would otherwise have held rather than against a headline index. If your realistic alternative is a total market index fund, that is your benchmark. Measured that way, sustained alpha of even 1% a year on your own decisions is a real achievement.

Benchmark selection is where most personal alpha calculations quietly go wrong. If you hold a concentrated basket of large-cap technology names, the S&P 500 is not your benchmark and a technology sector index is closer to the truth. Building the comparison basket that actually reflects your strategy is worth the effort, and if you want to weight one deliberately rather than borrow an off-the-shelf index, you can bundle the holdings into your own weighted benchmark and measure against that instead. The moment the benchmark matches the strategy, most apparent alpha disappears, and what remains is the part worth knowing about.

What is a good Jensen's alpha?

Jensen's alpha is the specific CAPM-based calculation above, so the same ranges apply: positive is good, 1% to 3% annually is respectable, and above 5% sustained is exceptional and worth auditing. What distinguishes it is that it explicitly adjusts for beta, so it will not credit a manager for taking more market risk.

Its weakness is that CAPM uses one factor. A fund loading on small-cap, value, momentum, or quality can post positive Jensen's alpha for years while doing nothing a factor model would call skill. Multi-factor alpha, measured against a three-factor or five-factor model, is a stricter test, and many funds with attractive Jensen's alpha show close to zero once size and value are accounted for.

Alpha benchmarks at a glance

These are ranges for judging a track record, not targets to aim at. Alpha is not a dial you can turn.

What does negative alpha mean?

Negative alpha means the portfolio returned less than its risk exposure predicted, so you were not compensated for the active decisions taken. A fund with -1.5% alpha did worse than simply holding the benchmark at the same beta, and in most cases the fee explains a large part of the gap.

Negative alpha is not automatically a reason to sell. A strategy deliberately built to reduce drawdowns may show negative alpha in a strong bull market and still be doing exactly the job you hired it for. What matters is whether the shortfall is explained by the mandate or by cost and poor execution. A defensive fund lagging a roaring market is behaving as designed. A fund with the same benchmark, the same beta, and a persistent gap is not.

Is alpha better than beta?

Neither is better, because they answer different questions. Beta tells you how much market risk you are carrying, and alpha tells you what you earned beyond what that risk should have paid. You need beta to compute alpha at all, which makes the comparison a category error.

Alpha needs at least one risk measure beside it. A 4% alpha earned through a 60% drawdown is not the same product as 4% earned through a 20% one, and alpha alone cannot tell those apart.

Why the alpha you measure shrinks after you find it

This is the part that matters most if you are testing your own ideas, and it is measured rather than theoretical. McLean and Pontiff, writing in the Journal of Finance in 2016, examined 97 published stock-return predictors and found that returns to those signals were 26% lower out of sample and 58% lower after publication. The edge did not vanish entirely, but more than half of it went away once the strategy was widely known.

There is a second effect that has nothing to do with other people trading against you. Bailey, Borwein, Lopez de Prado and Zhu showed in the Notices of the American Mathematical Society in 2014 that with only five years of daily data, testing more than roughly 45 independent configurations is near-certain to produce an in-sample Sharpe ratio of 1.0 whose expected out-of-sample Sharpe is zero. Search hard enough over a short history and you will find alpha that was never there.

Put those two findings together and you get a practical rule. Expect the alpha in your backtest to be the optimistic case. Halve it before you decide anything, be more skeptical the more variations you tried, and treat a strategy you found by sweeping parameters very differently from one you reasoned your way to first. Is backtesting accurate goes through the six specific leaks that inflate these numbers and how to detect each one.

How to check the alpha on a rule you already believe

The useful version of this question is rarely about a fund. It is about your own idea: does the rule you are about to follow actually beat holding the index, once you account for risk and costs? That is a testable question, and it takes minutes rather than quarters.

State the rule in one sentence, pick the benchmark you would genuinely hold instead, run it across a long enough history to include at least one bad market, charge realistic trading costs, and then compare. The bench at the top of this page does that: you type the thesis in plain English, it restates the rule for you to confirm before running, tests it on 20+ years of split- and dividend-adjusted daily data with a 0.1% cost per trade assumed by default, plots it against buy-and-hold with the worst drawdown shaded, and stamps an honest verdict, including UNDERPERFORMED when the idea loses to simply holding.

Two habits make the answer trustworthy. Set the benchmark before you look at the result, because choosing it afterward is how flattering alpha gets manufactured. And keep the number of variations you try small, for the reason Bailey and colleagues quantified. If you want the deeper method, how long you should backtest a strategy covers the window, walk-forward analysis covers testing on data you did not fit to, and buy-and-hold versus active trading is the comparison most active ideas ultimately have to win.

The short answer

What is a good alpha? Positive, and 1% to 3% per year after fees is genuinely good, with 3% to 5% strong and anything above 5% sustained over a decade rare enough to check the benchmark before believing it. Most active funds post negative alpha once fees are counted. Because alpha is defined against a benchmark and a beta estimate, the figure is only as honest as those two choices, so set them before you measure rather than after. And expect decay: more than half the measured edge in published predictors did not survive publication.

If you want to know whether your own rule produces alpha rather than just returns, test it against the portfolio you would otherwise hold. Stock backtesting covers doing that on a single ticker, portfolio backtesting covers a whole basket, and the best backtesting software roundup compares every platform that can run the test, with list prices verified in August 2026.