FINRA-reported dark pool prints reveal institutional accumulation and distribution before it moves the public market. Stop guessing. Start seeing.
Every data point flows from FINRA Trade Reporting Facilities — the same feed institutions use.
Off-exchange block trades from FINRA Trade Reporting Facilities. See the prints that never touch the lit market.
Automatically identifies block prints (10,000+ shares). The largest institutional footprints surface first.
Bull/bear scoring based on trade-at-ask vs trade-at-bid ratios. Know which side institutions are leaning.
Volume clustered by price level reveals where accumulation and distribution is concentrated.
The dark pool tape shows every FINRA-reported off-exchange print with trade direction (at-ask = bullish, at-bid = bearish), size, and notional value. Block trades over 10,000 shares are highlighted automatically.
Four timeframe windows (1H, 2H, 4H, full session) let you zoom into the activity that matters for your trading horizon.
Dark pools are private exchanges where institutional investors trade large blocks of stock without revealing their orders to the public market. About 40% of all U.S. equity volume executes off-exchange.
Hedge fund wants to buy 500,000 shares of AAPL
Trade executes privately. No market impact.
Print appears on TRF tape. We capture it for you.
By the time the print hits the tape, the trade is done — but the pattern of prints reveals where big money is building positions.
Everything you need to read institutional flow — in one panel.
Large block trades are routed through dark pools (Alternative Trading Systems) to avoid market impact. These trades are reported to FINRA.
Our system ingests FINRA TRF data via Databento, normalizes prices, identifies block trades, and computes bull/bear sentiment from trade direction.
Price level clustering, VWAP, block highlights, and sentiment scores give you a complete picture of where institutions are positioned.
See the institutional footprints that move markets. Dark Pool data is available on the Pro plan.
