chanmacro: Signal Expectancy Engine V1 — Market Memory System

Phase A-C complete: 4 core factors, regime detection, signal tracking, Bayesian expectancy.

chanmacro/ (32 files, ~4000 lines):
- models: 12 enums + 15 Pydantic v2 models (DateAwareModel, MarketStateVector, etc.)
- fetchers: OHLCV + Breadth (from data_provider) + Derivatives (new endpoint)
- scoring: Price Structure / Breadth (quantile buckets) / OI Matrix (5 discrete states) / Volatility Regime
- regime_detector: 3-state (TREND/RANGE/PANIC), factor-locked (Price+Breadth+Vol), versioned, 2-day confirmation
- expectancy: SignalTracker (record+outcomes), TimeDecay (half-life=180d), BayesianExpectancyEngine (Empirical Bayes, Leveled, SufficiencyGuard)
- validation: FactorValidator (IC/ICIR/Hit Ratio), RegimeValidator (MI/KL/ANOVA), TransitionValidator (stability)
- CLI: fetch|score|regime|track|backfill|expectancy|validate|serve
- tests: 52 passing (models, scoring, regime, expectancy)

data_provider:
- /api/derivatives endpoint: funding rate, OI, OI change, basis
- _derivatives storage: same persist pattern as K-line (merge→lock→snapshot→atomic write)
- background refresh every 60s

Co-Authored-By: Claude <noreply@anthropic.com>

ChanMacro/fetchers/derivatives.py

@@ -0,0 +1,66 @@
+"""
+fetchers/derivatives.py — Fetches derivatives data from data_provider API.
+
+Clean consumer: no direct ccxt dependency. Just HTTP GET /api/derivatives.
+"""
+
+from datetime import date as Date
+from typing import Optional
+
+import requests
+
+from .base import BaseFetcher
+from config import config
+
+
+class DerivativesFetcher(BaseFetcher):
+    """Fetches derivatives snapshot from data_provider /api/derivatives."""
+
+    def __init__(self, provider_url: Optional[str] = None):
+        super().__init__(timeout=15, max_retries=3)
+        self.provider_url = provider_url or config.provider_url
+
+    def fetch(self, target_date: Optional[Date] = None) -> list[dict]:
+        """Fetch derivatives data. Returns list with one record dict."""
+        url = f"{self.provider_url}/api/derivatives"
+        params = {"symbol": config.btc_symbol}
+        try:
+            data = self._get(url, params=params)
+            record = {
+                "date": str(target_date or Date.today()),
+                "symbol": config.btc_symbol,
+                "funding_rate": data.get("funding_rate"),
+                "open_interest": data.get("open_interest"),
+                "oi_24h_change_pct": data.get("oi_change_pct"),
+                "basis_annualised_pct": data.get("basis"),
+                "source": "data_provider",
+            }
+            return [record]
+        except Exception:
+            return []
+
+    def store(self, db_path: Optional[str] = None, records: Optional[list[dict]] = None) -> int:
+        """Store derivatives records into SQLite."""
+        import sqlite3
+        db_path = db_path or config.db_path
+        records = records or []
+        conn = sqlite3.connect(db_path)
+        count = 0
+        for r in records:
+            try:
+                conn.execute("""
+                    INSERT OR REPLACE INTO derivatives
+                    (date, symbol, funding_rate, open_interest, oi_24h_change_pct,
+                     long_liquidations, short_liquidations, basis_annualised_pct)
+                    VALUES (?, ?, ?, ?, ?, NULL, NULL, ?)
+                """, (
+                    r["date"], r.get("symbol", config.btc_symbol),
+                    r.get("funding_rate"), r.get("open_interest"),
+                    r.get("oi_24h_change_pct"), r.get("basis_annualised_pct"),
+                ))
+                count += 1
+            except Exception:
+                continue
+        conn.commit()
+        conn.close()
+        return count