Performance leaderboards are the most-searched and least-useful genre of investing content. This one tries to be different: all returns are long-horizon, all numbers are published net of fees, and every ranking is paired with a risk-adjusted view. Past performance still doesn’t guarantee the future — but the pattern of results across a decade tells you a lot about what a fund actually does.
How to read a performance table (before you get fooled)
- One-year returns are noise. Any screen ranked on 1Y will be topped by whatever sector had a bull run. Rank on 10Y to see skill and strategy.
- Always look at volatility.A 25% CAGR at 40% volatility is a different product from a 15% CAGR at 15% volatility — even though one “beat” the other on returns.
- Expense ratio matters more than it looks.0.5% vs 0.05% compounds to a ~10% drag over 20 years.
- Strip AUM-weighting from your rankings. “Biggest fund” and “best fund” are not the same question.
Broad-market index funds
These are the core holdings most passive investors should anchor to. They all own essentially the same US equity risk premium — differences are in breadth and cost.
| Ticker | Fund | Expense | 10Y CAGR | 10Y Volatility | Max drawdown |
|---|---|---|---|---|---|
| VTI | Vanguard Total US Market | 0.03% | ~12.4% | ~16% | -34% (2020) |
| SPY | SPDR S&P 500 | 0.09% | ~12.8% | ~15% | -34% (2020) |
| IVV | iShares S&P 500 | 0.03% | ~12.8% | ~15% | -34% (2020) |
| VOO | Vanguard S&P 500 | 0.03% | ~12.8% | ~15% | -34% (2020) |
| VT | Vanguard Total World | 0.07% | ~9.6% | ~15% | -33% (2020) |
| VXUS | Vanguard ex-US | 0.07% | ~5.2% | ~15% | -30% (2020) |
Factor index funds
Rules-based tilts towards the factors the academic literature supports: value, quality, size, momentum, low-volatility.
| Ticker | Tilt | Expense | CAGR (window) | vs SPY |
|---|---|---|---|---|
| QUAL | Quality | 0.15% | ~11.8% (10Y) | -1.0pp |
| MTUM | Momentum | 0.15% | ~11.4% (10Y) | -1.4pp |
| USMV | Low volatility | 0.15% | ~10.2% (10Y) | -2.6pp |
| VLUE | Value | 0.15% | ~8.7% (10Y) | -4.1pp |
| AVUV | Small-cap value | 0.25% | ~9.6% (since 2019) | varies |
| MOAT | Wide-moat (discretionary) | 0.46% | ~12.1% (10Y) | -0.7pp |
The notable pattern: factors allunderperformed the cap-weighted S&P 500 over the specific decade that ended in early 2026. That’s not evidence factors are dead — it’s evidence that large-cap growth had a historically exceptional run, and factor strategies are designed precisely to not bet the house on whatever ran last decade.
Sector index funds
| Ticker | Sector | 10Y CAGR | Max drawdown |
|---|---|---|---|
| XLK | Technology | ~19.8% | -34% (2022) |
| XLV | Health Care | ~10.6% | -22% (2022) |
| XLF | Financials | ~11.2% | -41% (2020) |
| XLY | Consumer Discretionary | ~12.1% | -38% (2022) |
| XLP | Consumer Staples | ~7.8% | -17% (2020) |
| XLE | Energy | ~4.1% | -56% (2020) |
| XLU | Utilities | ~8.4% | -22% (2020) |
| XLI | Industrials | ~10.3% | -29% (2020) |
| XLB | Materials | ~9.6% | -31% (2020) |
| XLRE | Real Estate | ~6.9% | -30% (2022) |
| XLC | Communication | ~9.2% (since 2018) | -44% (2022) |
Tech wins the decade, energy bottoms it. This is the rule not the exception in sector rankings: the winner of the last ten years is rarely the winner of the next. The bottom-quartile sector of the 2010s (energy) was top-quartile of 2021–2022.
Country / region index funds
| Ticker | Region | 10Y CAGR (USD) | Notes |
|---|---|---|---|
| SPY | USA | ~12.8% | reference |
| EWJ | Japan | ~6.9% | strong 2023–2024 |
| EWU | UK | ~4.8% | FTSE 100 headwind |
| EWG | Germany | ~4.2% | exporter-weighted |
| INDA | India | ~9.1% | top EM performer |
| MCHI | China | ~1.2% | regulatory drag |
| EWZ | Brazil | ~1.8% | commodity-cyclical |
| EWA | Australia | ~5.4% | resource-heavy |
Currency matters. A Japanese equity basket returning 14% in yen can translate to 7% in dollars after a currency move. All numbers above are in USD — the UK investor seeing sterling returns will see a different league table.
Thematic index funds
Thematic ETFs are the most-marketed and most-shuttered category in the industry. Some deliver against a long-term trend; many were top-of-ticker in 2020–2021 and down 60% by 2023.
| Ticker | Theme | Since-inception CAGR | Drawdown from peak |
|---|---|---|---|
| SOXX | Semiconductors | ~19.4% | -35% |
| SMH | Semiconductors | ~21.8% | -32% |
| ICLN | Clean energy | ~3.9% | -54% (from 2021 peak) |
| ARKK | Disruptive innovation | ~5.1% | -69% (from 2021 peak) |
| ITA | Aerospace & defence | ~11.2% | -18% |
| ROBO | Robotics / automation | ~9.6% | -38% |
| HACK | Cybersecurity | ~14.3% | -27% |
| KWEB | China internet | ~-4.8% | -74% (from 2021 peak) |
The risk-adjusted view — what changes when you penalise volatility
Raw returns tell half the story. The Sharpe ratio (return per unit of total volatility) and the Sortino ratio (return per unit of downsidevolatility) tell the other half — they answer “how much heartache per basis point of return.”
| Ticker | CAGR | Vol | Sharpe | Sortino |
|---|---|---|---|---|
| SPY | 12.8% | 15% | 0.65 | 1.02 |
| QQQ | 17.1% | 19% | 0.74 | 1.18 |
| RSP | 11.2% | 16% | 0.51 | 0.78 |
| QUAL | 11.8% | 14% | 0.63 | 0.97 |
| USMV | 10.2% | 12% | 0.60 | 0.93 |
| AVUV | 9.6% | 22% | 0.30 | 0.46 |
USMV earns 2.6pp lower CAGR than SPY — but earns it at meaningfully lower volatility, so per-unit-of-risk the two are close. AVUV has the highest expected return but the worst Sharpe on this horizon: the small-cap value premium demands a lot of patience before it pays off.
What wins vs what persists
The last decade was exceptional for US large-cap growth. That doesn’t necessarily predict the next decade. A few patterns are worth noticing before you extrapolate:
- Mean reversion across regions. US equities dominated the 2010s. European and emerging-market equities dominated the 2000s. Ten-year winner → next-ten-year winner has no statistical relationship.
- Mean reversion across sectors.Tech → Energy → Tech is a roughly decadal cycle. Sector rotation is real, slow, and impossible to time precisely.
- Factor premia persist, in episodes.Value, size, and quality all have decades where they’re flat. They’re compensation for a real risk, not a free lunch — the long-run edge requires sitting through stretches where the factor doesn’t work.
How to benchmark your own index
The point of a leaderboard isn’t bragging rights — it’s to know whether your custom index is earning its keep. The minimum checks:
- CAGR vs a passive reference.If you’re building a US large-cap index, compare to SPY. International? VT. If you can’t beat the passive reference after costs, the custom rules aren’t paying for themselves.
- Sharpe and Sortino vs the reference. Lower CAGR + much lower volatility = better risk-adjusted outcome. Always check both.
- Alpha, not absolute return.Your index might be down 20% in 2026 — but if the benchmark is down 30%, you’re earning positive alpha. That’s the number the custom rules should be judged on.
- Attribution. Was the out- or under- performance driven by sector selection (you held more of sector X than the benchmark did) or stock picking(your sector X holdings beat the benchmark’s sector X holdings)? The Brinson model answers this.
On Arithmos every index comes with this full view — benchmark overlay, risk-adjusted metrics, and a sector-attribution factsheet in one click. Build one and see your own numbers.
FAQ
What’s the best-performing index fund of all time?
Measured on total compounded return, it depends entirely on the window. Since-inception for long-lived funds, QQQ (1999) and VGT (2004) lead the US set. Over rolling 10Y windows, the tech-heavy indices and thematic semiconductor ETFs have been top of the table through the 2020s.
Why do index funds beat most active funds?
Three structural reasons: lower fees, lower turnover (so lower tax drag), and the mathematical fact that the average active investor, by definition, gets the market return minus costs. After fees, most active managers have to underperform — an index fund just removes the “after fees” part.
Is a higher-return fund always better?
No. Higher return almost always comes with higher volatility and deeper drawdowns. A fund that returns 15% with 35% drawdowns is worse for most investors than a fund that returns 11% with 20% drawdowns — because the first one gets sold at the bottom and the second one doesn’t.
How do I tell if past performance is just luck?
Look at the shape of the returns, not just the number. A strategy with a believable economic rationale, a Sharpe above 0.6 across multiple market regimes, and a drawdown profile you can read without flinching is probably the real thing. A strategy whose entire return comes from two good years is probably luck.