3.8 KiB
Research: Short Interest Squeeze Scanner
Date: 2026-04-12 Mode: autonomous
Summary
Stocks with high short interest (>20% of float) and high days-to-cover (DTC >5) face elevated squeeze risk when a positive catalyst arrives — earnings beat, news, or unusual options activity. Academic literature confirms that decreases in short interest predict positive future returns (14.6% annualized for distressed firms), while raw high SI alone is actually a negative long-term indicator. The edge here is not buying high-SI blindly, but using high SI + catalyst as a squeeze-risk scanner: a discovery tool that surfaces stocks where short sellers are structurally vulnerable.
Sources Reviewed
- QuantifiedStrategies (short squeeze backtest): Short squeeze strategies alone backtested poorly — rarity and randomness of squeezes prevent a reliable standalone edge
- Alpha Architect (DTC & short covering): DTC is a better predictor of poor returns than raw SI; long-short strategy using DTC generated 1.2% monthly return; short covering (SI decrease) signals informed belief change
- QuantPedia / academic: SI decrease in distressed firms predicts +14.6% annualized risk-adjusted return; short sellers are informed traders whose exit signals conviction shift
- Scanz / practitioner screeners: Consensus thresholds — SI% of float > 10% (moderate), >20% (high), DTC > 5 (high squeeze pressure)
- tosindicators.com: "Upcoming earnings with high short interest" scan is a common institutional approach — validates the earnings_calendar pending hypothesis
- earnings_calendar.md (internal): Pending hypothesis that SI > 20% pre-earnings produces better outcomes; APLD (30.6% SI, score=75) was the strongest recent earnings setup
- social_dd.md (internal): GME scan (15.7% SI, score=56) showed 55% 30d win rate — best 30d performer in pipeline
Fit Evaluation
| Dimension | Score | Notes |
|---|---|---|
| Data availability | ✅ | get_short_interest(return_structured=True) in finviz_scraper.py fully integrated |
| Complexity | trivial | Wrap existing function, map to {ticker, source, context, priority} format |
| Signal uniqueness | low overlap | No existing standalone short-interest scanner; social_dd uses SI as one factor among many |
| Evidence quality | qualitative | Academic support for DTC as predictor; practitioner consensus on thresholds |
Recommendation
Implement — The data source is already integrated and the signal fills a genuine gap. The scanner should NOT simply buy high-SI stocks (negative long-term returns). Instead, it surfaces squeeze candidates for downstream ranker scoring: stocks where short sellers are structurally vulnerable and any catalyst could force rapid covering. The ranker then assigns final conviction based on cross- scanner signals (options flow, earnings, news). This directly addresses the earnings_calendar pending hypothesis (SI > 20% pre-earnings).
Proposed Scanner Spec
- Scanner name:
short_squeeze - Data source:
tradingagents/dataflows/finviz_scraper.py→get_short_interest(return_structured=True) - Signal logic:
- Fetch Finviz tickers with SI > 15% of float, verified by Yahoo Finance
- CRITICAL: SI >= 30% (extreme squeeze risk — one catalyst away from violent covering)
- HIGH: SI >= 20% (high squeeze potential — elevated squeeze risk)
- MEDIUM: SI >= 15% (moderate squeeze potential — worth watching)
- Context string includes: SI%, DTC if available, squeeze signal label
- Priority rules:
- CRITICAL if
short_interest_pct >= 30(extreme_squeeze_risk) - HIGH if
short_interest_pct >= 20(high_squeeze_potential) - MEDIUM otherwise (moderate_squeeze_potential)
- CRITICAL if
- Context format:
"Short interest {SI:.1f}% of float — {signal_label} | squeeze risk if catalyst arrives" - Strategy tag:
short_squeeze