/ 01 · SECTION
The record
June 23, 2026 set all-time highs across notional, share volume, and trade count in the three-venue overnight ATS dataset. BlueOcean alone printed its largest of 157 sessions in the proprietary pipeline.
BlueOcean (BOATS) alone printed $13.52B / 487M shares on June 23, ranking #1 of 157 sessions since September 2, 2025 on both metrics. The prior BlueOcean peak was $11.95B on June 8. This deep-dive isolates the ETF subset of the night and runs four independent analyses against it.
/ 02 · SECTION
The ETF subset
Of the 1,093 distinct symbols that printed on BlueOcean, 419 are ETFs. They moved $5.55B — 41% of the night's notional.
Single-name equities carried the remaining $7.97B, led by Micron (MU) at $2.69B and SanDisk, Marvell, Intel, NVIDIA behind it. The ETF complex was the second leg of the same trade: leveraged and thematic vehicles expressing the semis/memory thesis. The rest of this report is the ETF subset only.
/ 03 · SECTION
Issuer dominance
One fund family — Direxion — accounted for nearly half of all ETF notional. Five issuers carried 83% of the night.
Direxion's 3x semis bull/bear suite (SOXL and SOXS) was the night's expression vehicle. Roundhill's single-stock leveraged products (MUU on Micron, MULL on Marvell) carried the memory-thematic flow. Vanguard — the largest ETF issuer in the world — was a rounding error here at 0.8%. The overnight ETF tape is a different product universe than the one that dominates daytime AUM rankings.
/ 04 · SECTION
ETF type breakdown
Two-thirds of the ETF notional was in leveraged or inverse products. Broad-market ETFs were 13%. This was a tactical-trading night, not a passive-allocation night.
| ETF Type | Notional | Volume | ETFs | % of ETF tape |
|---|---|---|---|---|
| Leveraged 3x | $1,929M | 8.9M | 17 | 34.8% |
| Leveraged 2x | $1,247M | 20.5M | 164 | 22.5% |
| Sector / Thematic | $990M | 9.9M | 114 | 17.9% |
| Broad Market | $732M | 1.7M | 28 | 13.2% |
| Inverse 3x | $418M | 72.9M | 12 | 7.5% |
| Commodities | $112M | 1.4M | 15 | 2.0% |
| Inverse 2x | $61M | 8.2M | 33 | 1.1% |
| Inverse 1x | $36M | 2.6M | 19 | 0.7% |
| Fixed Income | $19M | 0.2M | 9 | 0.3% |
Highlighted rows: leveraged + inverse 3x = 64.8% of ETF notional, with 11.1% added by 2x leveraged.
One row is worth pausing on: Inverse 3x carried 72.9M shares against only $418M notional. That's SOXS (semis bear 3x) at $25-share prices being hammered with massive lot sizes as a hedge wrap on the long-semis trade. The share-count leaderboard and the dollar leaderboard tell different stories — which is why we rank by notional throughout the rest of this report.
/ 05 · SECTION
K-Means clusters
K-Means on standardized log-feature space (notional, volume, AUM, habitual activity, leverage, inverse flag, RVOL). Silhouette-selected k=6 from candidates [3..7]. Two clusters carry the night.
| Cluster | Profile | ETFs | Notional | Median AUM | Avg Lev | Inverse% | Exemplars |
|---|---|---|---|---|---|---|---|
| C3 | Moderate-leverage (1.9x avg) — the trade | 17 | $3.35B | $1.9B | 1.9× | 6% | SOXL, MUU, DRAM |
| C4 | Large cap-weighted broad | 41 | $1.21B | $39.2B | 1.0× | 0% | QQQ, EWY, SPY |
| C1 | Moderate-leverage (2.1x avg) | 75 | $0.79B | $0.4B | 2.1× | 1% | TQQQ, SQQQ, INTW |
| C0 | Inverse / hedging ETFs | 62 | $0.12B | $0.0B | 1.9× | 100% | MUD, ZSL, MSTZ |
| C2 | Mid-tier core | 126 | $0.04B | $2.9B | 1.0× | 0% | XBI, AIPO, GPIQ |
| C5 | Moderate-leverage (2.1x), small AUM | 98 | $0.04B | $0.0B | 2.1× | 0% | LABU, SMCL, LABX |
Silhouette score 0.33 — moderate cluster separation. C3 has only 17 ETFs but holds 60% of the ETF notional.
The structure is sharper than the silhouette implies. Cluster C3 — only 17 ETFs — captures the actual trade: mid-leverage (~1.9x average) names like SOXL, MUU, KORU, DRAM that printed $3.35B. Cluster C4 is the large broad-index hedge layer (QQQ, SPY, EWY) for another $1.21B. Everything else — 361 ETFs across the four other clusters — added up to $0.99B combined. Sixty percent of the ETF notional fits in a basket of seventeen ETFs.
/ 06 · SECTION
Random Forest — what predicts overnight notional?
Regression model: predict each ETF's log-notional on 6/23 from its static features. 300 trees, max_depth=8, min_samples_leaf=5. R² = 0.81 in-sample (n=419).
| Feature | Importance | Interpretation |
|---|---|---|
| log(habitual avg overnight notional) | 88.5% | An ETF's existing overnight franchise dominates |
| log(AUM) | 6.0% | Fund size adds a little signal |
| days traded overnight | 4.1% | Regularity of overnight presence |
| leverage factor | 1.1% | Surprisingly small once activity is controlled |
| inverse flag | 0.3% | Negligible |
Catalyst events don't recruit new ETFs to the overnight tape — they amplify the names already there. The model is unambiguous: 88.5% of the explainable variance in overnight notional comes from each ETF's typical level of overnight activity. Leverage and inverse exposure barely move the needle once you control for habit. The reason leveraged ETFs dominate the tape isn't because their leverage attracts overnight flow on catalyst nights. It's because they are the ETFs that live on the overnight tape every night.
Methodological note: R² is in-sample. The point of this analysis is feature attribution, not forecasting. An out-of-sample fit would be lower; ranking of feature importance would be stable.
/ 07 · SECTION
Hierarchical correlation tree
Ward linkage on (1 - Pearson) distance over the 60-session log-notional panel of the top-30 ETFs by 6/23 notional. Five groups emerge.
The trade. These 14 ETFs move on the same overnight catalyst structure: memory and broader semis with a Korea (Samsung/SK Hynix) tilt via EWY and KORU.
Macro hedge cluster — the broad-index and inverse-semi pair that risk-balances Group 4.
Memory-thesis vehicles that correlate with each other but not with broader semis.
Risk-balance cluster. TSLL grouping with metals is unintuitive but emerges from co-movement.
The correlation tree is one of the strongest results in this report. The 14 ETFs in Group 4 don't share an obvious surface attribute (different issuers, different leverage factors, different geographic exposures) but their overnight activity moves together. When semis catch a catalyst, that whole basket lights up as one trade — which is precisely what June 23 looked like.
/ 08 · SECTION
Overnight vs daytime — head to head
Same 4-week window (2026-04-06 to 2026-05-03), ETFs only. FINRA publishes 43 ETF-reporting ATSes under Rule 4552, three of which are the overnight venues (BlueOcean + Bruce + Moon); we set those three side by side with the other 40 daytime institutional dark pools (UBS-ATS, MS-Pool, JPM-X, Sigma X, BIDS, Barclays, and the rest). Numerator and denominator are drawn from the same FINRA file and the same 1,137-ETF universe, so the share is a clean apples-to-apples ratio.
/ Weekly run-rate
| Week | Overnight (BLUE+BOSS+MOON) | FINRA daytime (40 ATSes) | Combined | Overnight Share |
|---|---|---|---|---|
| 2026-04-06 | $8.46B | $157.55B | $166.01B | 5.1% |
| 2026-04-13 | $6.16B | $176.47B | $182.63B | 3.4% |
| 2026-04-20 | $6.84B | $152.19B | $159.03B | 4.3% |
| 2026-04-27 | $7.57B | $153.38B | $160.95B | 4.7% |
| 4-week Total | $29.03B | $639.60B | $668.63B | 4.3% |
ETF notional only (1,137-symbol universe from etf_enriched). All figures from the FINRA Rule 4552 ATS Weekly file, offset-paginated to the full symbol tail. Overnight = the three overnight ATSes FINRA publishes under their own MPIDs (BLUE / BOSS / MOON); daytime = every other FINRA-reporting ATS over the same weeks. Because numerator and denominator come from one file and one definition, the share is a clean same-source ratio.
/ Tier 1 vs Tier 2 breakdown
/ Ticker-level head-to-head
The aggregate 4.3% figure averages across the full 1,137-ETF universe. Looking only at the ETFs that are actively traded overnight, the picture is more textured: leveraged and inverse Tier 2 vehicles run the highest overnight shares, topping out near 38% for SOXL, while the mega-cap broad-index complex (SPY, QQQ, IWM) stays in the low single digits because its daytime dark-pool volume is enormous. Across the top 25 ETFs by 4-week overnight notional, none exceeds 40% overnight share, and the broad-index names sit at 1 to 5%.
| ETF | Tier | Overnight 4-wk | FINRA daytime 4-wk | O/N Share | Type / Family |
|---|---|---|---|---|---|
| SOXL | T2 | $5,087M | $8,128M | 38% | Leveraged 3x · Direxion |
| QQQ | T1 | $2,901M | $73,239M | 4% | Broad · Invesco |
| TQQQ | T2 | $1,937M | $5,860M | 25% | Leveraged 3x · ProShares |
| SPY | T1 | $1,536M | $149,748M | 1% | Broad · State Street |
| SQQQ | T2 | $1,342M | $3,829M | 26% | Inverse 3x · ProShares |
| SOXS | T2 | $1,213M | $2,473M | 33% | Inverse 3x · Direxion |
| SLV | T1 | $999M | $2,515M | 28% | Commodity · iShares |
| USO | T1 | $896M | $4,380M | 17% | Commodity · USCF |
| GLD | T1 | $892M | $7,185M | 11% | Commodity · SPDR |
| SNXX | T2 | $540M | $1,352M | 29% | Leveraged 2x · Tradr |
| EWY | T1 | $492M | $6,747M | 7% | Korea · iShares |
| TSLL | T2 | $479M | $1,469M | 25% | Leveraged 2x · Direxion |
| AGQ | T2 | $424M | $843M | 33% | Leveraged 2x · ProShares |
| VOO | T1 | $376M | $7,548M | 5% | Broad · Vanguard |
| MUU | T2 | $373M | $911M | 29% | Leveraged 2x · Direxion |
| IBIT | T1 | $373M | $3,011M | 11% | Bitcoin · iShares |
| SGOV | T1 | $364M | $3,091M | 11% | Treasury · iShares |
| IWM | T1 | $329M | $23,418M | 1% | Broad · iShares |
| SOXX | T1 | $315M | $7,913M | 4% | Sector · iShares |
| SMH | T1 | $272M | $13,854M | 2% | Sector · VanEck |
| KORU | T2 | $247M | $670M | 27% | Leveraged 3x · Direxion |
| QQQM | T1 | $215M | $1,425M | 13% | Broad · Invesco |
| NVDL | T2 | $195M | $928M | 17% | Leveraged 2x · Graniteshares |
| QLD | T2 | $178M | $698M | 20% | Leveraged 2x · ProShares |
| DRAM | T2 | $174M | $1,154M | 13% | Memory · Roundhill |
Top 25 ETFs ranked by overnight 4-week notional (4/6 - 5/3), all figures from the FINRA Rule 4552 ATS Weekly file. Overnight = BLUE + BOSS + MOON; FINRA daytime = every other FINRA-reporting ATS over the same 4 weeks. Tier from FINRA classification. Highlighted rows: the highest overnight-share Tier 2 names (SOXL, SOXS, AGQ).
Three structural findings emerge from running the comparison at the venue level rather than the per-symbol level:
(a) In absolute terms the overnight tape is already large; as a share of all FINRA ETF dark-pool flow it is a single-digit slice.
Over the 4-week April window, the three overnight ATSes processed $29.0B in ETF notional while the full set of daytime FINRA-reporting dark pools processed $639.6B. Combined that is $668.6B in FINRA ETF dark-pool flow; the overnight share is 4.3%. Thirty billion dollars in four weeks is a serious tape in its own right, but the daytime dark-pool complex is roughly twenty times larger, so overnight is a low-single-digit share of the whole. The story is the absolute scale and the speed of growth, not a claim of parity with daytime.
(b) The overnight concentration is entirely in Tier 2 (leveraged, inverse and single-stock ETFs), where its share is roughly one dollar in four.
Tier 2 is where leveraged ETFs (SOXL, TQQQ), inverse ETFs (SOXS, SQQQ), single-stock leveraged ETFs (MUU, MULL, MVLL, NVDL, TSLL), and thematic/niche products live. Over the 4-week window the three overnight venues processed $16.9B in T2 ETF dark-pool flow against the daytime venues' $53.8B. The overnight share of Tier 2 ETF dark-pool flow is 23.9%, nearly one dollar in four, and far above the all-ETF average. This is the product category where the overnight session is structurally meaningful.
(c) In Tier 1 mega-cap broad indexes the overnight share is negligible; daytime dark pools dominate.
For Tier 1 ETFs (SPY, QQQ, QQQM, VOO, IWM, SMH, SOXX, GLD, SLV, EWY), the daytime dark pools lead overwhelmingly: $585.8B daytime vs $12.2B overnight, an overnight share of just 2.0%. The structural pattern matches the per-symbol findings in Section 06 (Random Forest): overnight flow concentrates in the leveraged and single-stock names that already live on the overnight tape, not in the mega-cap indexes whose dark-pool liquidity is anchored in daytime hours. For ETF flow desks, the takeaway is that overnight routing matters most for the Tier 2 leverage complex, where it is a genuine liquidity peer, and least for the broad-index names.
/ 09 · SECTION
Thesis
What this analysis means for institutional desks, beyond the headline record.
- 01
The overnight ETF tape is a tactical venue, not an allocation venue.
Two-thirds of notional was in 2x and 3x products. Issuer HHI of 2,619 is at the DOJ “highly concentrated” threshold, and the concentration is not in the Vanguards and BlackRocks. It is in Direxion, ProShares, and Roundhill — the leveraged and single-stock-thematic issuers.
- 02
Catalyst nights amplify existing names. They do not recruit new ones.
The Random Forest is unambiguous: 88.5% of the predictive signal for overnight notional is the ETF's own habitual overnight activity. Building a franchise on the overnight tape on normal nights is what captures the catalyst nights. Issuers absent from the overnight tape during quiet periods will not appear when the trade ignites.
- 03
Levered and single-stock ETFs are a separate liquidity universe.
SOXL, MUU, TQQQ, DRAM, KORU all trade lit and on overnight ATSes. Their daytime dark-pool presence in UBS, Morgan Stanley, JPMorgan and the rest of the FINRA venue set is thin relative to the mega-cap indexes. This is a structural distinction by product type, not just by time of day. Workflow desks routing levered ETF flow that overweight conventional dark-pool sourcing will understate where the inventory actually is.
- 04
The overnight ATSes are a large and fast-growing tape, and in Tier 2 ETFs they are a real liquidity peer to the daytime dark-pool complex.
Same 4-week window, head to head on one FINRA source: the three overnight venues processed $29.0B in ETF notional against $639.6B across the full daytime FINRA dark-pool set. That is 4.3% of all FINRA ETF dark-pool flow — a low-single-digit share of a market roughly twenty times larger, but a meaningful and rising absolute tape. In the Tier 2 category specifically (leveraged, inverse, single-stock, niche), the three overnight venues moved $16.9B against daytime's $53.8B — 23.9% overnight share, nearly one dollar in four. For ETF flow desks the implication is targeted: overnight routing is a first-order concern for the Tier 2 leverage complex and a minor one for mega-cap broad indexes.
/ 10 · SECTION
Subscriber data download
Every analysis on this page in a 10-sheet Excel workbook. Bring the data into your own models.
ETF Overnight Record · June 23, 2026 — Full Dataset
Cover, Topline stats, all 419 ETFs (with cluster assignment, RVOL, leverage, AUM, family), Issuer breakdown with HHI, ETF-type rollup, K-Means cluster profiles with exemplars, Random Forest feature importance, Ward correlation groups, FINRA cross-reference table, and a Glossary. Same source data we used to write this report.
Download requires an active Sapinover session (any tier including free trial). Anonymous requests are redirected to the subscribe page.
/ 11 · SECTION
Methodology
Sources, model specs, and the caveats baked into each result.
Data sources
- BlueOcean Master Historical parquet — proprietary 3-venue pipeline (BlueOcean, Bruce, Moon), GitHub Release
pipeline-data - ETF enrichment file (1,137 ETFs with family, category, AUM, leverage, expense ratio) — yfinance + bespoke leverage parser
- FINRA Rule 4552 ATS Weekly file — the full set of FINRA-reporting ATSes (43 venues, including the three overnight ATSes BLUE / BOSS / MOON) across a 28-day window 2026-04-06 to 2026-05-03 (4 contiguous weeks, the most recent stretch with both Tier 1 and Tier 2 published; FINRA's 5/4 and 5/11 weeks are T1-only and excluded for cleanliness). The file is offset-paginated across the full symbol tail so no venue is truncated.
Models
- K-Means clustering — silhouette-optimized k across [3..7] on standardized log-feature space (log-notional, log-volume, log-AUM, log-habitual, leverage factor, inverse flag, RVOL)
- Random Forest regression — 300 trees, max_depth=8, min_samples_leaf=5, target = log10(overnight notional). Feature attribution only; in-sample R² 0.81
- Hierarchical correlation tree — Ward linkage on (1 - Pearson) distance matrix over 60-session log-notional panel of the top-30 ETFs by 6/23 notional. Cut at k=5
- Head-to-head venue comparison — same 4-week window (4/6-5/3), ETF flow only, drawn entirely from one FINRA Rule 4552 source for internal consistency. Overnight = the three overnight ATSes FINRA publishes under their own MPIDs (BLUE / BOSS / MOON); daytime = every other FINRA-reporting ATS. Both sides filtered to the 1,137-symbol ETF universe (1,121 of which appear in the FINRA file) and summed across the 4 weeks, T1 + T2 combined. Tier breakdown uses FINRA's NMS Tier_ID classification per symbol. All notional = totalNotionalSum.
Caveats
- The ETF subset in Sections 01-07 is BlueOcean pipeline data only; Bruce + Moon ETF-level detail is not in those analyses. The Section 08 head-to-head is a separate, single-source FINRA analysis
- Random Forest R² is in-sample. Out-of-sample fit would be lower. The analysis is for feature attribution, not forecasting
- K-Means silhouette of 0.33 is moderate — cluster boundaries are real but soft
- FINRA window is 4 weeks 4/6 - 5/3 (most recent T1+T2-complete stretch). May weeks 5/4 and 5/11 are T1-only in FINRA's publication and excluded from the head-to-head for cleanliness
- Overnight and daytime are both measured within the full, offset-paginated FINRA Rule 4552 ETF dark-pool set (43 ATSes, complete across the symbol tail with no venue truncated), so the 4.3% overall and 23.9% Tier 2 shares are same-source point estimates. Figures reflect the full-venue coverage as of the 2026-07-02 methodology update
- The overnight side of the head-to-head uses only the overnight venues FINRA itself publishes (BLUE / BOSS / MOON). Our proprietary pipeline captures additional internalized overnight flow beyond what FINRA reports, so the pipeline-measured overnight dollar total (~$32.6B) runs somewhat above the pure-FINRA overnight figure (~$29.0B); the head-to-head uses the FINRA figure on both sides for consistency
- All notional figures are dollar volume, not share-count
SAPINOVER LLC · 2026-06-24 · NOT INVESTMENT ADVICE · INFORMATIONAL ONLY
This report is for informational purposes only. Past trading patterns do not predict future activity. All numbers are derived from public market structure data and the proprietary Sapinover 3-venue overnight ATS pipeline. The report contains no investment recommendations, ratings, or implied views on securities. See disclaimer.