35 lines
2.6 KiB
Markdown
35 lines
2.6 KiB
Markdown
# Insider Buying Scanner
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## Current Understanding
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Scrapes SEC Form 4 filings. CEO/CFO purchases >$100K are the most reliable signal.
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Cluster detection (2+ insiders buying within 14 days) historically a high-conviction
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setup. Transaction details (name, title, value) must be preserved from scraper output
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and included in candidate context — dropping them loses signal clarity.
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## Evidence Log
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### 2026-04-12 — P&L review (2026-02-18 to 2026-04-07)
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- insider_buying produced 136 recommendations — by far the highest volume scanner.
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- Score distribution is healthy and concentrated: 53 picks in 80-89, 11 in 90-99, only 1 below 60.
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- Confidence calibration is tight: avg score 78.6 (score/10 = 7.9) vs avg confidence 7.5 — well aligned.
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- Cluster detection (2+ insiders → CRITICAL priority) is **already implemented** in code at `insider_buying.py:73`. The hypothesis was incorrect — this is live, not pending.
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- High-conviction cluster examples surfaced: HMH (appeared in 2 separate runs Apr 8-9), FUL (Apr 9 and Apr 12), both with scores 71-82.
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- Confidence: high
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### 2026-04-12 — Fast-loop (2026-04-08 to 2026-04-12)
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- Insider_buying dominates final rankings: 3 of 6 ranked slots on Apr 9, 2 of 5 on Apr 10, contributing highest-ranked picks regularly.
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- Context strings are specific and include insider name, title, dollar value — good signal clarity preserved.
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- Confidence: high
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### 2026-04-12 — P&L update (180 tracked recs, mature data)
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- Win rates are weaker than expected given high confidence scores: 38.1% 1d, 46.4% 7d, 29.7% 30d.
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- Avg returns: -0.01% 1d, -0.4% 7d, -1.98% 30d — negative at every horizon.
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- **Staleness pattern confirmed**: HMH appeared 4 consecutive days (Apr 6-9) with nearly identical scores (72, 85, 71, 82) — same insider filing, no new catalyst. FUL appeared Apr 9 and Apr 12 with identical scores (75). This is redundant signal, not confluence.
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- High confidence (avg 7.1) combined with poor actual win rates = miscalibration — scanner assigns scores optimistically but real outcomes are below 50%.
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- Confidence: high
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## Pending Hypotheses
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- [x] Does cluster detection (2+ insiders in 14 days) outperform single-insider signals? → **Already implemented**: cluster detection assigns CRITICAL priority. Code verified at `insider_buying.py:73-74`. Cannot assess outcome vs single-insider yet (all statuses 'open').
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- [ ] Is there a minimum transaction size below which signal quality degrades sharply? (current min: $25K — candidates with $25K-$50K transactions show up at lower scores but still make final ranking)
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- [ ] Does filtering out repeat appearances of the same ticker from the same scanner within 3 days improve precision?
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