learn(iterate): 2026-04-13 — automated iteration run

docs/iterations/LEARNINGS.md

@@ -1,6 +1,6 @@
 # Learnings Index
 
-**Last analyzed run:** 2026-04-12
+**Last analyzed run:** 2026-04-13
 
 | Domain | File | Last Updated | One-line Summary |
 |--------|------|--------------|-----------------|
@@ -13,7 +13,7 @@
 | early_accumulation | scanners/early_accumulation.md | 2026-04-12 | Sub-threshold (score=60); no catalyst → structurally score-capped by ranker |
 | social_dd | scanners/social_dd.md | 2026-04-12 | Sub-threshold (score=56); BUT 55% 30d win rate — diverges from social_hype; ranker may be suppressing it incorrectly |
 | volume_accumulation | scanners/volume_accumulation.md | — | No data yet |
-| short_squeeze | scanners/short_squeeze.md | — | No data yet — new scanner, research: high SI (>20%) + catalyst = squeeze risk; not a directional signal alone |
+| short_squeeze | scanners/short_squeeze.md | 2026-04-13 | First real data: 60% 7d win rate, +2.15% avg 7d (n=10) — best 7d performer; DTC now surfaced in context |
 
 ## Research
 

docs/iterations/scanners/short_squeeze.md

@@ -3,18 +3,35 @@
 ## Current Understanding
 Identifies stocks with structurally high short interest (>15% of float by default, CRITICAL at >30%)
 where short sellers are vulnerable to forced covering on any positive catalyst. The scanner uses
-Finviz for discovery (screener filters) + Yahoo Finance for exact SI% verification.
+Finviz for discovery (screener filters) + Yahoo Finance for exact SI% and days-to-cover (shortRatio)
+verification.
 
 Key distinction: High SI alone predicts *negative* long-term returns on average (academic consensus).
-The scanner is a squeeze-risk flag, not a directional buy signal. Value comes from cross-scanner
-confluence: a stock appearing here AND in options_flow or earnings_calendar is significantly stronger
-than either signal alone.
+However, first real P&L data (n=10) shows 60% 7d win rate and +2.15% avg 7d — best 7d performer in
+the pipeline. This may reflect that discovery-pipeline filtering (technical confirmation, enrichment)
+already adds the catalyst signal needed to convert squeeze-risk into a directional trade. Cross-scanner
+confluence (short_squeeze + options_flow or earnings_calendar) remains a stronger signal than either
+alone and is the primary confluence hypothesis under test.
 
 ## Evidence Log
 
-_(populated by /iterate runs)_
+### 2026-04-13 — P&L review (first real outcome data)
+- 10 tracked recommendations, 5/10 1d wins (50% win rate), 6/10 7d wins (60% win rate).
+- Avg 7d return: +2.15%. This makes short_squeeze the **best 7d performer** among scanners with ≥5 samples.
+- Outperforms analyst_upgrade (50% 7d), insider_buying (46.4% 7d), options_flow (45.6% 7d).
+- The scanner is producing positive outcomes as a standalone signal, not only as a cross-scanner modifier.
+- However, ranker prompt says "Focus on days to cover" but context string only shows SI%. DTC value is available in Yahoo Finance (`shortRatio`) but was not being fetched or passed through — gap confirmed.
+- Confidence: medium (small sample n=10; 30d data will be more conclusive; DTC gap has been fixed)
+
+### 2026-04-13 — Code fix: days_to_cover surfaced in context
+- Added `days_to_cover` extraction (`shortRatio` from Yahoo Finance) to `finviz_scraper.py`.
+- Applied `min_days_to_cover` filter (previously accepted as parameter but never enforced).
+- Updated `short_squeeze.py` context string to include DTC value so ranker can use "days to cover" criterion.
+- Confidence: high (this is a clear context gap between ranker criteria and available data)
 
 ## Pending Hypotheses
 - [ ] Does short_squeeze + options_flow confluence produce better 7d win rate than either scanner alone?
 - [ ] Does short_squeeze + earnings_calendar (SI>20%) produce better outcomes than earnings alone? (See earnings_calendar.md pending hypothesis)
 - [ ] Is there a volume threshold (e.g., market cap <$2B small-cap) that sharpens the signal?
+- [ ] Does DTC >5 (now surfaced in context) predict better outcomes than DTC 2-5 within the scanner?
+- [ ] Does standalone short_squeeze (no cross-scanner confluence) continue to outperform at 7d as sample grows?

tradingagents/dataflows/discovery/scanners/short_squeeze.py

@@ -67,6 +67,7 @@ class ShortSqueezeScanner(BaseScanner):
                     continue
 
                 si_pct = item.get("short_interest_pct", 0)
+                dtc = item.get("days_to_cover", 0.0)
                 signal = item.get("signal", "low_squeeze_potential")
                 label = _SIGNAL_LABELS.get(signal, signal)
 
@@ -78,8 +79,9 @@ class ShortSqueezeScanner(BaseScanner):
                 else:
                     priority = Priority.MEDIUM.value
 
+                dtc_str = f"{dtc:.1f}" if dtc else "N/A"
                 context = (
-                    f"Short interest {si_pct:.1f}% of float — {label}"
+                    f"Short interest {si_pct:.1f}% of float, {dtc_str} days to cover — {label}"
                     " | squeeze risk elevates if catalyst arrives"
                 )
 
@@ -91,6 +93,7 @@ class ShortSqueezeScanner(BaseScanner):
                         "priority": priority,
                         "strategy": self.strategy,
                         "short_interest_pct": si_pct,
+                        "days_to_cover": dtc,
                         "squeeze_signal": signal,
                     }
                 )

tradingagents/dataflows/finviz_scraper.py

@@ -115,6 +115,15 @@ def get_short_interest(
                     market_cap = info.get("marketCap", 0)
                     volume = info.get("volume", info.get("regularMarketVolume", 0))
 
+                    # Days to cover (short ratio): shares short / avg daily volume
+                    days_to_cover = info.get("shortRatio")
+                    if days_to_cover is None or not isinstance(days_to_cover, (int, float)):
+                        days_to_cover = 0.0
+
+                    # Apply days-to-cover filter
+                    if days_to_cover < min_days_to_cover:
+                        return None
+
                     # Categorize squeeze potential
                     if short_pct >= 30:
                         signal = "extreme_squeeze_risk"
@@ -131,6 +140,7 @@ def get_short_interest(
                         "market_cap": market_cap,
                         "volume": volume,
                         "short_interest_pct": short_pct,
+                        "days_to_cover": days_to_cover,
                         "signal": signal,
                     }
             except Exception: