44 lines
3.8 KiB
Markdown
44 lines
3.8 KiB
Markdown
# Social DD Scanner
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## Current Understanding
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Identifies speculative momentum setups driven by high social sentiment scores and
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elevated short interest (potential short squeeze). Despite a speculative surface-level
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profile, early P&L data shows 55% 30d win rate and the only scanner positive at 30d
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(+0.94% avg 30d return). This DIVERGES from `social_hype` (14.3% 7d win rate) —
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`social_dd` likely includes more fundamental corroboration (short interest, OBV, MACD)
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versus pure social sentiment. Current ranker prompt groups them together, which may be
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incorrect. Setups currently score below 65 and are filtered by the score threshold.
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## Evidence Log
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### 2026-04-12 — Fast-loop (2026-04-08 run)
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- Single appearance: GME, score=56, conf=5, risk_level=speculative.
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- Thesis: Social DD score 75/100 + 15.7% short interest + bullish MACD crossover.
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- Score sub-threshold (56 < 65). Negative signals in thesis: weak fundamentals (-13.9% revenue growth), insider selling $330k.
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- **Critical context from scoring.md P&L review**: social_dd historically shows 55% 30d win rate, +0.94% avg 30d — the only scanner positive at 30d. This suggests the scanner has real edge but requires a longer holding period than 1-7 days.
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- Current ranker prompt groups social_dd with social_hype as "SPECULATIVE" — this may cause social_dd to be systematically under-scored, suppressing a legitimate slow-win strategy.
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- 0 mature recommendations from discovery pipeline (no recommendation generated from this appearance).
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- Confidence: medium (outcome data from scoring.md gives P&L context, but very few appearances in discovery pipeline)
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### 2026-04-13 — Statistical analysis (n=25 picks)
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- Avg score: 71.5 — most picks (22/25) already score ≥65. Ranker suppression is an outlier case, not systematic.
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- 7d win rate: 41.7%, avg 7d return: -1.92% — poor short-term.
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- 30d win rate: 60.0%, avg 30d return: +2.32% — confirmed slow-win profile.
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- High-conf (≥7, n=9): 30d win rate 55.6% — high confidence does not add meaningful edge over base rate.
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- **Key insight**: the evaluation horizon mismatch is the real issue. Downstream recommendation scoring and ranker calibration use 7d outcomes, which penalize social_dd unfairly. The scanner works — but only at 30d.
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- Confidence: high (n=25, consistent with prior 55% 30d finding)
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### 2026-04-14 — P&L review (updated statistics, n=26)
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- 30d win rate: 57.1% (12/21 wins), avg 30d return: +1.41% — confirmed improvement from prior 55%/+0.94% reading.
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- 7d win rate: 44.0%, avg 7d return: -1.47% — poor at shorter horizon as expected.
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- 1d win rate: 46.2%, avg 1d return: +0.66% — slight positive 1d signal (new observation).
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- social_dd remains the **only scanner positive at 30d** across all strategies.
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- Apr 3-9 mature recs: GME (Apr 8, score=56, conf=5) was the only social_dd pick. Sub-threshold, no recommendation generated. Score reflects weak fundamentals (-13.9% rev growth, insider selling) — appropriate.
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- Confidence: high (n=26, consistent 30d outperformance confirmed across two analysis cycles)
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## Pending Hypotheses
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- [x] Does the ranker's "social_dd / social_hype → SPECULATIVE" grouping suppress social_dd scores? → **Partially false**: avg score is 71.5, suppression affects only 3/25 picks. Not the primary issue.
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- [ ] Should social_dd get a separate ranker treatment from social_hype, given divergent 30d outcomes? → Still open. social_hype 7d win rate 18.2% vs social_dd 30d 57.1% — they are fundamentally different signals.
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- [ ] Fix evaluation horizon: ranker and recommendation system should assess social_dd at 30d, not 7d. This may require a scanner-level `eval_horizon` config field.
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- [ ] At what social score threshold (>75? >85?) does the setup reliably score ≥65 to generate recommendations? → Lower priority now that suppression is not the main issue.
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