Home/Methodology
Scoring Methodology · v2.1

Every score. Fully explained. No exceptions.

ETFCheck scores are rules-based and free from commercial influence. No ETF provider pays for placement. No algorithm is hidden. This page explains exactly how every number on this site is generated.

Zero paid placements
Open formula
Updated nightly
101 ASX ETFs scored

One score. Four pillars. Fixed weights.

Every ETF receives a composite score from 0 to 100. That score is built from exactly four measurable factors, each scored independently on a 0–100 scale, then combined using the weights shown here.

Fees receive the highest weight because they are the most reliable predictor of long-term outcomes. They are certain, compounding, and entirely within an investor's control. Size and liquidity protect against operational and trading risks. Yield receives the lowest weight because high yield alone does not indicate superior total return.

40%
25%
20%
15%
Fees
Fund Size
Liquidity
Yield
Combined Formula
Score = (Fees × 0.40)
+ (Size × 0.25)
+ (Liquidity × 0.20)
+ (Yield × 0.15)
Each component is 0–100. Final score is rounded to the nearest integer.
Green: ≥80 · Amber: 60–79 · Orange: <60

How each pillar is calculated

FeesMER40%
Score = 100 − (MER × 150)

Fees are the single most impactful variable in long-term ETF outcomes. A 1% annual fee compounds to a 26% return drag over 30 years. We weight fees most heavily because, unlike returns, they are certain and predictable.

Fee score curve — score vs MER
0501000.0%0.2%0.4%0.6%0.8%1.0%0.80% → score 0A200/IVVVGSNDQFANGSEMI
Worked examples
A200 / IVV
0.04%
94
VGS
0.18%
73
NDQ
0.22%
67
FANG
0.35%
48
SEMI
0.57%
15
Edge cases
MER ≥ 0.67%: score floors at 0
Funds with performance fees: we use total all-in MER from the most recent annual report
Buy/sell spreads are NOT included here — they are captured in the Liquidity score
Fund SizeAUM25%
Score = ((log₁₀(AUM_M) − 1.7) / 2.7) × 100

Larger funds are less likely to close (forced redemptions are a real cost for investors), benefit from better institutional support, and tend to have tighter bid-ask spreads. We use a logarithmic scale because the marginal benefit of additional AUM diminishes at scale.

Worked examples
VAS
$14B
91
VGS
$8.2B
82
A200
$4.8B
73
PMGOLD
$980M
48
Small fund
$50M
0
Edge cases
AUM is measured in AUD millions from provider fact sheets
Scores below $50M AUM approach 0 — closure risk is material at this size
The score does not penalise ETFs with a short track record if AUM is already substantial
LiquidityDaily Volume20%
Score = ((log₁₀(volume) − 3.5) / 2.3) × 100

Higher trading volume means tighter bid-ask spreads and easier entry and exit without moving the market. We use average daily share volume from ASX market data. Poor liquidity directly increases your transaction costs in a way MER does not capture.

Worked examples
VAS
~3M/day
100
A200
~1.2M/day
100
NDQ
~380k/day
100
PMGOLD
~65k/day
57
Small ETF
~5k/day
9
Edge cases
Volume measured in shares traded per day (ASX reported, 30-day average)
ETFs with in-specie creation/redemption mechanisms may trade lightly but still have tight spreads — volume is an imperfect proxy
New ETFs with short history: we use available data from listing date
Dividend YieldIncome15%
yield ÷ category max × 100

Yield expectations differ dramatically by asset class: cash ETFs should yield more than growth ETFs. Scoring yield on an absolute scale would penalise every international equity ETF. Instead, we score yield proportionally within each of our 26 categories: a fund's yield is divided by the highest yield in its category to give a score from 0–100. The highest-yielding fund in a category scores 100; truly zero-yield funds score 0. Funds with a positive yield always score above 0, even if they are the lowest yielder in their category.

Worked examples
SYI
~11.9%
100
VHY
~7.3%
61
VAS
~2.9%
64
NDQ
~1.0%
16
PMGOLD
0%
0
Edge cases
Physical gold, crypto ETFs (PMGOLD, GOLD, EBTC, EETH) are assigned zero yield regardless of any incidental distributions
Non-distributing fund structures (some accumulation-class ETFs) score 0 within their category
Category assignment affects this score — a 3% yield may score 64 in a category where the best fund yields 4.7%, or 100 where the best fund yields 2.9%

Worked example: how A200 gets its score

BetaShares Australia 200 ETF (ASX: A200), category: Australian Large Cap Equities

PillarRaw InputFormulaComponent ScoreWeight
Fees (MER)0.04%100 − (0.04 × 150)
94
37.6
Fund Size$4.8B AUM((log₁₀(4800)−1.7)/2.7)×100
73
18.3
Liquidity~1.2M/day((log₁₀(1.2M)−3.5)/2.3)×100
100
20.0
Yield~3.0% yield3.0 ÷ cat_max × 100
64
9.6
Total Score87
38.0 + 18.3 + 20.0 + 10.8 = 87.1 → rounded to 87. Score band: green.

Try it yourself

Enter any ETF's characteristics and see how the component scores react in real time.

Live Calculator

Adjust the sliders to see how component scores react in real time. Yield is assumed at 50 (mid-range within category) for a neutral estimate.

Try a real ETF
Inputs
Annual fee (MER %)0.18%
$180/yr per $100,000
Fund size (AUM)$1.0B
Daily trading volume200k shares
Component Scores
Fees40%
78
Fund Size25%
48
Liquidity20%
78
Yield15%
50
Estimated total score66
Score band: amber (moderate)

Where the data comes from

Scores are only as reliable as their inputs. Here is exactly what data feeds each pillar.

01
Provider PDSs
MER, fund structure, and investment objective sourced from the current Product Disclosure Statement on file with ASIC. Updated when providers publish amendments.
02
ASX Market Data
Daily trading volume (30-day average) from ASX official market statistics. Updates at end of each trading day.
03
Yahoo Finance Prices
End-of-day price and NAV data for all 101 ETFs. Used for AUM estimation (where direct provider data is unavailable) and price history charts.
04
Provider Fact Sheets
Monthly AUM, top holdings, and distribution history from provider fact sheets. BetaShares, Vanguard, BlackRock, and others publish these on the 1st–5th business day of each month.
05
Score Computation
Scores are recomputed nightly from the latest available data. Each pillar formula is deterministic: the same inputs always produce the same output.

What we deliberately exclude

Choosing what to leave out of a scoring model is as important as what to include. Each exclusion is a deliberate decision.

Historical returns
Past performance is not a reliable predictor of future performance. Including returns would systematically bias scores towards recently hot sectors. A fund that returned 95% in 2023 due to AI hype would score high — which is not information that helps long-term investors.
Tracking error
Detailed, audited tracking error data is not consistently available across all 101 ETFs in our database. MER serves as the primary cost proxy. Where an ETF has a known tracking error issue, we note it in the ETF detail page.
Tax efficiency
Australian tax treatment varies substantially by investor type: accumulation vs pension phase super, marginal tax rate, and foreign income tax offsets all affect the after-tax return from any given ETF. We cannot score tax efficiency fairly without knowing each investor's situation.
ESG / ethical ratings
Ethical preferences are deeply personal and not universally agreed upon. We score ETFs on objective financial metrics only. Use the Sectors filter to find ESG and socially responsible ETF categories.
Fund manager reputation
Qualitative assessments introduce subjectivity and bias. Vanguard, BetaShares, and BlackRock each have different reputations across different investor communities. The formula is blind to the issuer.

Our transparency commitments

No paid rankings
ETF providers cannot pay for higher scores or better placement. The formula is the only arbiter.
No affiliate links
We earn no commission from ETF purchases. There are no referral arrangements with any broker or provider.
Public formula
The exact scoring formula is on this page and in our scoring source code. Nothing is hidden or approximated.
Versioned methodology
When we update the scoring model, we publish what changed and why. The current version is v2.1.
No editorial scores
No human overrides any score. The formula runs identically for every ETF in every category.
ASIC compliance
ETFCheck holds no AFSL. All content is general information only. We link to PDS documents on every ETF page.

Disclaimer

ETFCheck scores are provided for informational and educational purposes only. They do not constitute financial advice, a recommendation to buy or sell any security, or an assessment of suitability for any particular investor. Past performance is not indicative of future results. Always read the Product Disclosure Statement before investing. Consider your personal financial circumstances and consult a licensed financial adviser if required. ETFCheck.com.au does not hold an Australian Financial Services Licence (AFSL).