ETFs

The 193

There are roughly 4,600 ETFs listed in US markets. The set we cover is 193 — chosen to span the investable opportunity set without the redundancy of near-duplicates or the noise of inactive, illiquid, or just-launched names. Together they represent about 96% of what investors are actually trading.

ETFs matter for this site because they reach asset classes the S&P 500 and Russell 1000 don't: bonds across the duration curve, gold and silver, spot bitcoin, single-country and regional equity, sector concentrates, factor tilts, the income tier. A stock universe alone misses the rotation.

The curation went through hierarchical clustering and principal component analysis on factor and exposure profiles; the top three from each cluster were kept, ranked primarily by size. Leveraged and inverse vehicles were dropped — they're trading instruments, not asset-class exposures, and the percentile signals on this site don't translate cleanly to them.

The goal was not a "best ETFs" list. It's a basis — small enough to scan, broad enough that any sector rotation, factor regime, geography, or asset class has a representative wrapper inside it.

Shape of the universe

The 193 wrappers hold about $5.3 trillion in aggregate AUM, but the distribution is dramatically uneven. SPY alone is 11.7% of the universe. The top 5 ETFs hold 40%. The top 10 hold 51%. The top 50 — barely a quarter of the names — hold 85%.

The median ETF in the set holds $6.8B; SPY is 91× that. The bottom 100 names — more than half the count — together account for just 5.2% of AUM.

That shape isn't peculiar to our selection. It's the structure of the ETF industry: a small head of broad-market and core-bond wrappers that absorb the vast majority of assets, a body of sector and international funds, and a long tail of thematic, country-specific, and specialty vehicles that exist mostly as narrative completeness rather than as where money lives.

The contrast becomes sharper category by category. Broad-market ETFs are 31 names but hold 51% of AUM. Sector ETFs are larger by count (50 names) but only 11% of AUM — sector bets are smaller bets. Thematic wrappers (18 names — cannabis, tail risk, vol premium, AI baskets) are loud in financial press but quiet in dollars: 1% of AUM. Crypto is three ETFs and 1.3% — still small in this frame, but IBIT alone is $67B, more than every commodity ETF combined.

That asymmetry is the first thing to know before reading any of the per-ETF signals: when XLK and SPY both register a high percentile, they aren't peers in size — XLK is a sliver of the size of SPY, and the money behind each is moving for different reasons.

What each ETF is a bet on

An ETF is a thesis you can buy. The thesis might be "the US stock market," "the US bond market," "the energy sector," "Brazilian equities," "covered calls on the Nasdaq," or "bitcoin." Reading any percentile signal on an ETF means first knowing which thesis you're looking at. The 193 wrappers fall into eight categories.

Broad (31 ETFs)

Beta on a wide equity index. SPY, VOO, and IVV span the S&P 500 — the three giants are nearly identical, existing mostly as State Street, Vanguard, and iShares each wanting their own version of the same exposure. VTI extends to the total US market; QQQ to the NASDAQ-100; IWM to small-cap; IJH to mid-cap. Inside the bucket sit the factor tilts — RSP (equal-weight), MTUM (momentum), QUAL (quality), USMV (low volatility), VLUE (value), MOAT (wide moat), COWZ (free-cash-flow yield). These slice the same large-cap universe by different academic factors.

A high persistence signal here tells you the equity regime has held — not that some company is compounding.

Sector (50 ETFs)

A single US sector. The State Street SPDR Select Sector family is the standard — XLK (technology), XLF (financials), XLE (energy), XLV (health care), XLI (industrials), XLU (utilities), XLP (consumer staples), XLY (consumer discretionary), XLB (materials), XLC (communication services), XLRE (real estate). Eleven sectors, eleven wrappers, all liquid, all multi-billion-dollar. Below them sit more concentrated reads: SMH (semiconductors), GDX (gold miners), XBI (biotech), KRE (regional banks), ITB (home construction), KIE (insurance), JETS (airlines), ITA (aerospace and defense).

A sector ETF's percentile is a relative-rotation signal: which slice of the US economy is leading, lagging, or pivoting right now.

Income (25 ETFs)

Yield from equity, in three flavors. Dividend growers (VIG, SCHD, DGRO, NOBL) pick companies with long records of raising payouts — the thesis is quality-tilted compounding, not maximum yield. High-yield (VYM, DVY, HDV) is current-yield focused, often tilted toward financials and utilities. Option overlay (JEPI, JEPQ, DIVO, QYLD) writes covered calls against equity portfolios; the trade is steady premium income for capped upside. Preferred securities (PFF, FPE, PFXF) and MLPs (AMLP) sit at the edge — fixed-income-like cash flows wrapped in equity vehicles.

Bond (19 ETFs)

Fixed income across the duration curve. The line from cash to long-duration Treasuries is the cleanest way to read the bucket:

Beside the ladder sit aggregate funds (BND, AGG, GOVT), credit (LQD investment grade, HYG and JNK high yield), TIPS (TIP), municipals (MUB), international (BNDX, EMB), and senior loans (SRLN, JAAA). A persistence signal on TLT is mostly an interest-rate-regime read; on HYG it's a credit-spread read; on BIL it's barely more than a yield-level read.

Commodity (11 ETFs)

Physical or futures-based exposure to raw materials. Gold dominates the bucket — GLD ($75B) and SLV ($15B) together are most of it. Below them: industrial metals via mining baskets (XME, PICK), uranium (URA, URNM, NLR), oil (USO), agriculture (DBA), and broad commodity indexes (PDBC, DBC). GUNR rolls global upstream natural resources into one wrapper.

The physical trusts (GLD, SLV) behave very differently from the futures-rolling ones (USO, DBA, PDBC), which carry contango drag. Persistence signals are cleaner on the physical wrappers because the price is the asset, not a rolled contract chain.

Crypto (3 ETFs)

Spot bitcoin and ether trusts plus one miner basket. IBIT (iShares Bitcoin Trust, $67B, listed January 2024) is by far the largest — the spot-BTC ETFs that launched in early 2024 produced one of the most successful ETF debuts in history. ETHA covers ether. WGMI is bitcoin miners — a leveraged-to-BTC equity proxy, not crypto directly.

This category exists today only because the SEC approved spot Bitcoin ETFs in January 2024. Two years ago, this row of the universe was empty.

International (36 ETFs)

Non-US equity, also in three flavors. Broad ex-US wraps developed markets or the whole world (VXUS, EFA, VEA, VT). Regional baskets cover continents or aggregates (VGK Europe, VWO/EEM emerging markets, AIA Asia 50). Single-country is the long tail: EWJ (Japan), EWZ (Brazil), MCHI (China), INDA (India), EWY (Korea), EWT (Taiwan), EWG (Germany), EWU (UK), EWC (Canada), and down to EIDO (Indonesia) and ECH (Chile).

The signal-reading shift here is currency. A country ETF's return is the local market's return plus or minus the dollar's move against that currency. A persistent decline in EWJ when Japanese equities are flat in yen terms is a yen story, not a TOPIX story.

Thematic (18 ETFs)

Narrow narratives, hedges, vol strategies, basket plays. Innovation (ARKK, ARKQ, ARKX), AI baskets (IVES, MAGS — the Magnificent Seven as a wrapper, QTUM for quantum), blockchain (BLOK, DAPP), genomics (ARKG), infrastructure (PAVE, IGF, GRID), defined-outcome buffers (BALT), managed futures (DBMF), vol strategies (SVOL, IVOL), tail hedges (TAIL, PFIX), and the cannabis pair (MSOS, YOLO).

This is where the most noise lives relative to AUM. Half the bucket is below $2B. A high percentile here often tells you the narrative is hot — not that the underlying business is winning. Which can be useful or misleading depending on what you're trying to read.

Eight categories, 193 wrappers, $5.3T in aggregate AUM. The categorization is the prior; the per-ETF percentiles are how you read what each thesis is doing right now. The next thing to know is that the dashboard's signals — designed for individual stocks — don't always mean the same thing when the underlying is a basket.

Reading signals on a basket

The dashboard's percentile tiles were built for individual companies. On a stock, Money Flow is institutional accumulation in that company; Persistence is the company's relative-strength ranking holding its trajectory; Drawdown Ratio is the company's downside relative to its drawdown norm. On an ETF, the same tiles still compute — but they mean something different because the underlying is a basket, not a business.

Money Flow on TLT isn't accumulation in a company. It's positioning in long-duration Treasuries, which is mostly a bet on falling rates. A high reading tells you institutional dollars are flowing into duration. A negative reading tells you they're flowing out. Same math as on AAPL — completely different signal.

Persistence on XLK isn't a single firm compounding. It's the technology sector regime holding. A high rank-persistence on XLK over 52 weeks tells you tech has been beating the market consistently for a year — a regime read, not a company read. When that regime breaks, it tends to break for many tickers at once.

Drawdown Ratio on JEPI behaves differently than on a stock because the covered-call overlay clips the right tail. JEPI's drawdowns are smaller than the underlying S&P 500 in size, but they also rarely recover as fast. A high drawdown-ratio percentile on JEPI is a normal feature of the strategy, not a stress signal.

Vol Ratio on bond ETFs is dominated by duration, not by company specifics. TLT's vol versus SPY shows you "how much do long Treasuries swing relative to stocks" — which moves with the rate-vol regime. A vol-ratio spike on TLT is a rates-volatility story, not a flight-to-quality story.

Market Beat is the one signal that reads almost identically across stocks and ETFs. A high 1-year market-beat percentile on either says "this has outperformed SPY over the trailing year." The only adjustment for ETFs: a sector ETF beating SPY by 15 points usually means the underlying sector led the market, not that the ETF picked the right stocks within it.

The cross-sectional tables below all use 12-month excess return vs SPY (Market Beat 1Y) as the ranking signal. It's the metric that translates cleanest from a stock universe to an ETF universe.

Top 25 by 1-year vs SPY

Highest 12-month excess-return percentiles in the ETF cohort.

Bottom 25

The ETFs that have lagged SPY the most over the trailing year. A laggard might be a melting ice cube or an out-of-favor exposure that's poised to mean-revert — the percentile doesn't tell you which.

1-month rotation

ETFs whose 12-month-vs-SPY ranking shifted the most over the last month. Climbers (left) saw the biggest improvement in their relative position — typically the asset class catching a regime change. Decliners (right) saw the biggest deterioration.

Steady leaders

ETFs where the 12-month-vs-SPY percentile is high (≥ 70) and barely moved over the last month (|Δ| ≤ 10) — exposures that have been quietly outperforming without rotating in or out of leadership. The boring compounders of the ETF universe.