59 lines
3.4 KiB
Markdown
59 lines
3.4 KiB
Markdown
# Research: Dark Pool / Block Trade Flow
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**Date:** 2026-04-16
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**Mode:** autonomous
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## Summary
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Dark pool order flow (off-exchange block trades) predicts short-term returns in academic literature. A free, scrapable data source exists: `meridianfin.io/darkpool` surfaces daily FINRA ATS anomalies with Z-scores pre-computed, no auth required, plain HTML table. Data lags 1 day (FINRA ATS settlement). Signal: tickers with dark pool % anomaly (Z-score ≥ 2.0) are experiencing unusual institutional off-exchange accumulation — a pre-move signal distinct from any existing scanner.
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## Sources Reviewed
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- **Buti, Rindi & Werner (2022), Financial Management**: Dark pool retail order imbalance predicts future returns; effect is non-linear and regime-dependent
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- **Zhu (2012), NY Fed**: Strong-signal traders prefer lit exchanges; moderate-signal traders route to dark pools — so a dark pool surge suggests informed but not fully certain buying
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- **Unusual Whales docs**: Real-time prints with bid/ask classification; subscription required — not used here
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- **OptionsTradingOrg practitioner guide**: Volume surge >2-3x 30d average + dark pool % >40-50% of daily volume = actionable signal
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- **meridianfin.io/darkpool**: Free, daily, FINRA-based; shows Ticker, Off-Exchange Vol, Dark Pool %, Z-score, Date; 8 top anomalies per day; scrapable with `requests` + `BeautifulSoup`; no auth needed
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- **FINRA ATS Transparency (raw)**: Free CSV downloads but require joining multiple venue files and rolling baseline computation — Meridian does this work for us
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## Fit Evaluation
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| Dimension | Score | Notes |
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|-----------|-------|-------|
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| Data availability | ✅ | `meridianfin.io/darkpool` — free HTML table, 1-day lag, no auth, `requests`+BS4 sufficient |
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| Complexity | moderate | ~2-4h: HTTP scraper + BS4 parser + scanner class + config entry |
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| Signal uniqueness | low overlap | No dark pool scanner exists; `options_flow` uses options chains not off-exchange prints |
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| Evidence quality | backtested | Zhu (2012) and Buti et al. (2022) academic backing; volume surge threshold validated by practitioners |
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## Recommendation
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**Implement** — all four thresholds pass. Signal has academic backing, data is free and scrapable, complexity is moderate, no overlap with existing scanners.
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## Proposed Scanner Spec
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- **Scanner name:** `dark_pool_flow`
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- **Pipeline:** `edge` (off-exchange institutional flow = information advantage)
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- **Data source:** Scrape `https://meridianfin.io/darkpool` daily with `requests` + `BeautifulSoup`
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- **Signal logic:**
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1. Fetch the anomaly table (up to 8 rows, all pre-filtered by Meridian's Z-score engine)
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2. Filter: Z-score ≥ `min_z_score` (default 2.0)
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3. Filter: dark pool % ≥ `min_dark_pool_pct` (default 40.0%)
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4. Return all passing tickers as candidates
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- **Priority rules:**
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- CRITICAL if Z-score ≥ 4.0
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- HIGH if Z-score ≥ 3.0
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- MEDIUM otherwise
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- **Context format:** `"Dark pool anomaly: {dark_pool_pct:.1f}% off-exchange | Z-score {z_score:.2f} | Vol: {off_exchange_vol:,}"`
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- **Config parameters:**
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```python
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"dark_pool_flow": {
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"enabled": True,
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"pipeline": "edge",
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"limit": 8,
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"min_z_score": 2.0, # Minimum FINRA ATS anomaly Z-score
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"min_dark_pool_pct": 40.0, # Minimum % of daily volume off-exchange
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"source_url": "https://meridianfin.io/darkpool",
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}
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```
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- **Limitation:** 1-day lag (FINRA ATS settlement); no bid/ask directionality; only ~8 tickers/day surfaced
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