Gesamtempfehlung-Paket: 2 Rollouts, 3 Anzeige-Features, 2 Messungen (v=114)
- Entry-Raum-Gate 0,6→1,0 (Messung lag vor: beide Hälften besser) - Konfidenz-Kalibrierung gemessen (analyze_verdict_calibration.py): conf INVERTIERT zwischen Regimen → keine P(Erfolg)-Aufwertung, kein Konf-Sizing - verdict_votes-Logging (1×/min) für spätere Copilot/Elliott-Entscheidung - Order-Dialog zeigt eigenen Ausrichtungs-Split (36/40 Trades ohne Signal: −423€) - Live-Kosten-Chip (Spread/ATR) im Verdict - P(break)×Entry-Raum-Freigabe gemessen VERWORFEN (Flip in jeder Schwelle, backtest_entryroom_pbreak.py) — 13. verworfener Signal-Eingriff - News-Konflikt-Chip + recommendations.news_score wieder befüllt Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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co-authored by
Claude Opus 4.8
parent
c3c6a8ce5f
commit
d61c4a3634
@@ -138,6 +138,25 @@ SCHEMA = [
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correct INTEGER -- NULL bis ausgewertet, dann 0/1
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)
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""",
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"""
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CREATE TABLE IF NOT EXISTS verdict_votes (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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ts INTEGER, -- lokale Epoch
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headline TEXT, -- Wave-Signal (LONG/SHORT/WARTEN)
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conf INTEGER, -- conf_pct der Welle
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bias REAL, -- gewichteter Konsens-Bias −1..+1
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tf TEXT, -- Zeitebene der Empfehlung
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wave INTEGER, -- Votes je Modul: +1/−1/0
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m30 INTEGER,
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h1 INTEGER,
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ki INTEGER, -- KI-Copilot-Vote (0 auch wenn ohne Aussage)
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ki_w REAL, -- Copilot-Gewicht (0 = hatte keine Aussage)
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elliott INTEGER,
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elliott_w REAL,
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squeeze INTEGER,
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news_score REAL -- News-Sentiment zum Zeitpunkt (Kontext)
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)
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""",
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]
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# Indizes — werden NACH den Migrationen ausgeführt, weil sie Spalten
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@@ -156,6 +175,7 @@ INDEXES = [
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"CREATE INDEX IF NOT EXISTS idx_intended_close ON intended_trades(close_ts)",
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"CREATE INDEX IF NOT EXISTS idx_pbreak_ts ON pbreak_predictions(ts)",
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"CREATE INDEX IF NOT EXISTS idx_pbreak_open ON pbreak_predictions(outcome) WHERE outcome IS NULL",
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"CREATE INDEX IF NOT EXISTS idx_verdict_ts ON verdict_votes(ts)",
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]
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# Migrations: Spalten, die in alten DBs evtl. fehlen.
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@@ -394,6 +414,61 @@ class HistoryLogger:
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"pending": pending,
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}
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def log_verdict_votes(self, *, headline: str, conf: int, bias: float, tf: str,
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wave: int, m30: int, h1: int, ki: int, ki_w: float,
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elliott: int, elliott_w: float, squeeze: int,
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news_score=None) -> None:
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"""Verdict-Modul-Stimmen für die spätere Kalibrier-Auswertung loggen
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(Copilot/Elliott sind unbelegte Stimmen — nach ein paar Wochen kann
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`analyze_verdict_calibration.py`-artig entschieden werden, ob sie
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Gewicht behalten). Intern gedrosselt auf max. 1×/60 s."""
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now = time.time()
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if now - getattr(self, "_verdict_log_ts", 0.0) < 60:
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return
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self._verdict_log_ts = now
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with self._lock, self._connect() as conn:
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conn.execute("""
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INSERT INTO verdict_votes
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(ts, headline, conf, bias, tf, wave, m30, h1, ki, ki_w,
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elliott, elliott_w, squeeze, news_score)
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VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?)
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""", (int(now), headline, conf, bias, tf, wave, m30, h1, ki, ki_w,
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elliott, elliott_w, squeeze, news_score))
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conn.commit()
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def alignment_stats(self, last_n: int = 40) -> dict:
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"""Ausrichtungs-Split der letzten N geschlossenen Trades: liefen sie MIT,
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GEGEN oder OHNE die Empfehlung (rec_signal beim Entry)? Für die ehrliche
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Verhaltens-Anzeige im Order-Bestätigungsdialog (B0 als Software — die
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gemessene Kern-Leckage sind diskretionäre Gegen-Signal-Trades)."""
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with self._connect() as conn:
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rows = conn.execute("""
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SELECT direction, rec_signal, pnl FROM trades
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WHERE exit_time IS NOT NULL AND pnl IS NOT NULL
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ORDER BY exit_time DESC LIMIT ?
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""", (last_n,)).fetchall()
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out = {}
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for key, match in (("with", True), ("against", False)):
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grp = []
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for r in rows:
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rec = (r["rec_signal"] or "").upper()
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if rec not in ("LONG", "SHORT"):
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continue
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aligned = (rec == "LONG") == (r["direction"] == "BUY")
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if aligned == match:
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grp.append(r["pnl"])
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n = len(grp)
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out[key] = {"n": n,
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"wr": round(100 * sum(1 for p in grp if p > 0) / n) if n else None,
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"pnl": round(sum(grp), 2)}
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none_grp = [r["pnl"] for r in rows
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if (r["rec_signal"] or "").upper() not in ("LONG", "SHORT")]
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n = len(none_grp)
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out["none"] = {"n": n,
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"wr": round(100 * sum(1 for p in none_grp if p > 0) / n) if n else None,
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"pnl": round(sum(none_grp), 2)}
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return out
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# ══════════════════════════════════════════
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# STATISTIK-QUERIES
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# ══════════════════════════════════════════
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