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OpenFactsheet

Free, independent investment analysis

Your investment has a sales pitch. Get a second opinion.

See what a performance chart might leave out: the biggest historical losses, how long recovery took, and what the numbers can—and cannot—tell you. Explore a free example, or analyze an investment's monthly returns.

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  • Transparent methodology
Watch the explainer video

Investment snapshot

Sample fund, Jan 2015 to Dec 2024

Consistent, steady growth

Except here: -27.32%, and still below its June 2020 high 54 months later.

Growth over 10 years
+37.02%
Every 100 invested became 137.
Biggest historical drop
-27.32%
From its June 2020 high to June 2022.
Time to recover
Not yet
Still below its June 2020 high when the data ends, 54 months later.
Illustration, synthetic data: not a real fund or a real pitch.Open this example in the tool

An illustrative, synthetic example

See what a headline return leaves out.

Explore the full sample

The same made-up fund, two ways: the figures a pitch might quote, and the historical measurements a second opinion adds. The full sample in the tool is a different synthetic fund, analyzed the same way.

What the pitch shows

Investor presentation
  • 8.78% a year
  • Smooth and steady growth
  • Sharpe ratio of 2.38

Growth over 8 years, as a pitch would chart it.

What a second opinion adds

Same fund, full record
Biggest historical drop
-8.85%, from its March 2020 high to June 2020.
Time to get back to the previous high
17 months, back at its March 2020 level in August 2021.
Worth a closer look
The returns look smoothed: each month tends to repeat the one before. That can make an investment look steadier than it really is, so its risk figures are probably understated. 4 months were also extreme compared with the rest of the record.
Allowing for the smoothing, the headline score the pitch quotes falls from 2.38 to 1.57.
What does this mean?

The Sharpe ratio is a popular score: return earned for each unit of ups and downs. When returns are smoothed, part of the ups and downs is hidden, so the score looks better than it should.

OpenFactsheet also reports a version adjusted for this (Lo, 2002). The smoothing shows up as a month-to-month correlation of 0.54 (values near zero are typical for investments priced daily by a market). Both versions use a 0% risk-free rate.

Illustrative example, not a real fund. Built from synthetic returns; every figure is computed by the openfactsheet library from its 96 monthly returns.

Who chose these figures?

Why get a second opinion?

A fund factsheet can also be used as a marketing document. Ask who selected the figures and periods. EU regulators list factsheets as marketing communications.E1 That doesn't make them false, but it does mean someone chose what to show you, from which date, and compared with what.

More than 9 in 10

US large-cap active funds that did worse than the S&P 500 over the 20 years to 2025.

Source: SPIVA U.S. Year-End 2025, published March 2026.

0%

of 2021's top-quartile US large-cap funds stayed in the top quarter every year through 2025.

Source: U.S. Persistence Scorecard, Year-End 2025.

$29,000

less after 20 years on $100,000 with a 1% yearly fee instead of 0.25%, in the SEC's own example.

Source: U.S. SEC, Office of Investor Education and Advocacy. Investor Bulletin: How Fees and Expenses Affect Your Investment Portfolio (updated July 2025).

More research, with editions and dates, is on the evidence page.

Watch the explainer

OpenFactsheet, explained.

What OpenFactsheet does, and why a factsheet is worth a second opinion.

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How it works.

Explore our sample in about a minute, with no file. When you want to check a real investment, bring its monthly returns. No account, no finance degree, no coding.

  1. 1

    Try our example

    See a complete report built from synthetic monthly returns. Nothing to find, prepare or upload.

    Run the example
  2. 2

    Use monthly returns to check your investment

    Find the investment's monthly returns, then upload a CSV or Excel file or paste the table. It's analyzed on your device.

    Where do I find them?
  3. 3

    Read the result and its limitations

    Plain language first, every detail if you want it, and a clear note on what the numbers can't tell you.

Three common factsheet traps.

See all 10 tricks

1The lucky start date

A return quoted "since" a date that happens to be a low point.

Example Growth FundFactsheet, page 1

Illustration, not a real fund

  • 6.91% a year since July 2022

    Measured from just after the bottom of its biggest fall. Over the full 10 years it grew 3.20% a year, and its worst 12 months were -19.61%.

Synthetic sample fund. Both figures computed by the openfactsheet library from the same monthly returns.

How to spot it

3Before-fee returns

Gross figures look better than what an investor actually receives.

Example Growth FundFactsheet, page 1

Illustration, not a real fund

  • Strong long-term growth*

    *“Gross” means before fees, not what an investor received. In the SEC's own example, a 1% yearly fee instead of 0.25% leaves about $29,000 less after 20 years on $100,000.E4

*Performance shown gross of fees.

How to spot it

7The too-smooth line

Hard-to-value assets can report returns smoother than reality, so risk looks low.

Example Growth FundFactsheet, page 1

Illustration, not a real fund

  • Smooth and steady growth

  • Sharpe ratio of 2.38

    Returns look smoothed: each month tends to repeat the last (autocorrelation 0.54). Corrected for that, the score is 1.57.

Illustrative smoothed series. Figures computed by the openfactsheet library.

How to spot it

What we show.

The standard report includes every applicable measure, and explains any that can't be calculated from your data.

Make them prove it.

If an investment charges more than a low-cost index alternative, it should show you, in after-fee, risk-adjusted terms, that the extra fee bought something.

Not an outlook. Not a theme. Not a story. Evidence.

  • After costs, the average actively managed dollar must earn less than the market.E5
  • Research has found that few active funds earn enough extra to cover their costs, and that skill is hard to tell apart from luck.E6
  • One study estimates investors earned about 1.2 percentage points a year less than the funds they owned, largely because of when they bought and sold.E7
  • Investors react to visible upfront charges but largely ignore ongoing yearly fees.E12

The debate

What should every factsheet show?

Our proposed checklist has these, and five more. Should they be required? Tell people what you think.

  1. 1Returns after all feesWhat an investor actually received, shown alongside any before-fee figure.
  2. 2The full history, and every calendar yearFrom launch to today, plus each complete calendar year, not a chosen start date.
  3. 3Yearly returns next to any cumulative figureA total over many years means little without the return per year.
  4. 4The worst fall, and how long it took to recoverThe biggest drop from a previous high, when it happened, and the months it took to get back.
  5. 5Risk-adjusted return, with the method statedReturn per unit of risk, and exactly how it was calculated.
See all 10 points and download the checklist

Why trust the calculations?

The same conventions, every time

Every investment is measured with the same published rules, decided in advance. Nobody picks the flattering period or the convenient ratio, including us.

Open methodology

The formulas, conventions and code are public and versioned, so anyone can check how each number was produced.

Data-quality warnings

Gaps, smoothed or stale returns and unusual months are flagged before anything is measured, and a short track record is labelled as such.

Honest about its limits

OpenFactsheet analyzes the returns you supply. It can't verify that they are complete or correct, and it never says whether an investment is right for you.

  • No advertising
  • No affiliation with any fund manager or seller
  • No data collection

OpenFactsheet does not rate, rank or recommend investments, and it is not investment advice. It shows the historical evidence, laid out the same way every time.

Explore all 102 measurements in the methodology

Open-source Python library

For developers & finance professionals

The same calculations as this site, in an open-source Python library (Apache-2.0) for due diligence, reproducible research and integrations, under one versioned methodology.

Your money deserves more than a sales pitch.

Explore our sample in about a minute, then check an investment you're considering. Free, and no account.

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