Strategy Fix Deploy A: confidence tiering, entry-momentum readout, dynamic TP, synthetic-instrument filter

- F1a: Telegram alerts tier 'TRADE-GRADE' (conf>=9.0) vs 'WATCH ONLY' (8.8-9.0); alert threshold and dedup unchanged
- F2a/2b: card.entry_momentum (m5/m15 ROC%, aligned) - zero extra API calls; alert line shows 15m momentum + alignment
- F3a: card.levels.tp_dyn additive field (0.7R via TP_DYN_R env); alert line under TP3; TP1/2/3 unchanged
- F5b: exclude BingX synthetic/CFD instruments (oil, forex, metals, index proxies) from scan universe; /api/scan reports synthetics_excluded count

Source: analysis/signal_verdict.md (n=40, Jul 8-11) + automation-docs/STRATEGY-FIX-PLAN.md
All additive/display-only, zero change to scoring weights or trading logic.

main.py

@@ -9,7 +9,7 @@ Endpoints:
 All computation is deterministic — no AI in the data path.
 """
 from __future__ import annotations
-import math, statistics, time, os
+import math, statistics, time, os, re
 from pathlib import Path
 from functools import lru_cache
 from datetime import datetime, timezone
@@ -37,6 +37,28 @@ logger = logging.getLogger("main")
 
 ALERT_INTERVAL = 300  # 5 minutes
 
+# ── Synthetic-instrument hygiene (Strategy Fix Plan F5b) ───────────────────
+# BingX lists non-crypto CFD proxies (oil, forex, metals, index futures) on the
+# same USDT-M perpetual endpoint as real crypto. 10/50 alerts in the Jul 8-11
+# batch were these — unanalyzable (no independent data source) and off-mission.
+# Patterns below are derived from the 7 confirmed synthetic symbols found in
+# analysis/replay_results.csv (NO_DATA rows), not guessed:
+#   CO1OILBRENT2USD-USDT, NCCO1OILWTI2USD-USDT, NCCOGOLD2USD-USDT,
+#   NCCOXAG2USD-USDT, NCFXGBP2JPY-USDT, NCSISP5002USD-USDT, SINASDAQ1002USD-USDT
+# The 3rd pattern (digit + 3-letter fake-FX code immediately before "-USDT")
+# alone catches all 7 observed cases and is low-false-positive: real crypto
+# tickers (BTC-USDT, 1000PEPE-USDT, etc.) never end in <digit><3 letters>-USDT.
+EXCLUDE_SYNTHETICS = os.environ.get("EXCLUDE_SYNTHETICS", "true").lower() == "true"
+_SYNTHETIC_PATTERNS = [
+    re.compile(r"^(CO1|NCFX|NCS|NCCO|SIN)", re.IGNORECASE),                # known prefixes
+    re.compile(r"(XAU|XAG|NGAS|NATGAS|BRENT|WTI|GOLD|SILVER|NASDAQ|SP500)", re.IGNORECASE),  # commodity/index keywords
+    re.compile(r"\d[A-Z]{3}-USDT$"),                                       # embedded fake-FX quote suffix
+]
+
+
+def is_synthetic(symbol: str) -> bool:
+    return any(p.search(symbol) for p in _SYNTHETIC_PATTERNS)
+
 async def _alert_loop():
     """Background task: scan every 5 min and fire Telegram alerts for high-confidence cards."""
     from telegram_alert import send_alert, prune_sent_cache, send_raw_message
@@ -56,7 +78,7 @@ async def _alert_loop():
         try:
             src = get_source()
             secondary = get_secondary()
-            candidates = rank_universe(src, src.min_vol, 30)
+            candidates, _synth_excluded = rank_universe(src, src.min_vol, 30)
             for c in candidates:
                 try:
                     card = score_symbol(src, c["symbol"], alert_account, 1.0,
@@ -143,20 +165,27 @@ def get_secondary():
     return _binance if _binance_ok else None
 
 
-def rank_universe(src, min_volume: float, top_n: int) -> list[dict]:
+def rank_universe(src, min_volume: float, top_n: int) -> tuple[list[dict], int]:
+    """Returns (picked_candidates, synthetics_excluded_count)."""
     perps = src.universe()
     rows = []
+    synth_excluded = 0
     for t in src.tickers():
         if t["symbol"] not in perps:
             continue
+        if EXCLUDE_SYNTHETICS and is_synthetic(t["symbol"]):
+            synth_excluded += 1
+            continue
         qv = t["quote_volume_usd"]
         lo, hi = t.get("low", 0), t.get("high", 0)
         if qv < min_volume or lo <= 0:
             continue
         t["range_24h_pct"] = (hi - lo) / lo * 100
         rows.append(t)
+    if synth_excluded:
+        logger.info("rank_universe: %d synthetic instruments excluded", synth_excluded)
     if len(rows) < 3:
-        return [{"symbol": s} for s in src.anchors]
+        return [{"symbol": s} for s in src.anchors], synth_excluded
 
     log_vols = [math.log(r["quote_volume_usd"]) for r in rows]
     ranges = [r["range_24h_pct"] for r in rows]
@@ -174,7 +203,7 @@ def rank_universe(src, min_volume: float, top_n: int) -> list[dict]:
             if extra:
                 extra["anchor"] = True
                 picked.append(extra)
-    return picked
+    return picked, synth_excluded
 
 
 # ── API routes ─────────────────────────────────────────────────────────────
@@ -196,7 +225,7 @@ def scan(top: int = 8, min_volume: float = None, account: float = 100000,
     try:
         src = get_source()
         floor = min_volume or src.min_vol
-        candidates = rank_universe(src, floor, top)
+        candidates, synth_excluded = rank_universe(src, floor, top)
         secondary = get_secondary()
         cards = []
         for c in candidates:
@@ -229,7 +258,8 @@ def scan(top: int = 8, min_volume: float = None, account: float = 100000,
                 cards.append({"symbol": c["symbol"], "error": str(e)[:120]})
         cards.sort(key=lambda c: c.get("confidence", 0), reverse=True)
         return {"fetched_at": datetime.now(timezone.utc).isoformat(),
-                "source": src.name, "market": src.market_note, "cards": cards}
+                "source": src.name, "market": src.market_note, "cards": cards,
+                "synthetics_excluded": synth_excluded}
     except Exception as e:
         raise HTTPException(503, str(e))
 

scorer.py

@@ -14,13 +14,35 @@ PA is loaded lazily — if patterns.py / chart_patterns.py / order_blocks.py /
 confluence.py are missing, falls back to 40/20/20/20 (old formula).
 """
 from __future__ import annotations
-import math, statistics
+import math, statistics, os
 import pandas as pd
 from indicators import analyze_timeframe
 from exchange import pick_source, INTERVAL_MS
 from catalyst import score_catalyst as _catalyst_score
 import time
 
+# ── Strategy Fix Plan config (F2a, F3a) — additive, no scoring-engine change ──
+# TP_DYN_R: dynamic-TP distance in R multiples, evidence zone 0.5-0.8R (default 0.7).
+TP_DYN_R = float(os.environ.get("TP_DYN_R", "0.7"))
+
+
+def _roc_pct(df, n: int) -> float | None:
+    """% change from the closed candle n bars back to the latest closed candle.
+
+    Used for entry-momentum readout (Strategy Fix Plan F2a) — no extra API calls,
+    reuses the already-fetched 5m/15m raw OHLCV DataFrames.
+    """
+    if df is None or len(df) < n + 1:
+        return None
+    try:
+        prev = float(df["close"].iloc[-1 - n])
+        cur = float(df["close"].iloc[-1])
+        if prev == 0:
+            return None
+        return round((cur - prev) / prev * 100, 4)
+    except Exception:
+        return None
+
 # Markov + HMM — imported lazily to avoid startup errors if not yet installed
 try:
     from markov import analyze_symbol as _markov_analyze
@@ -691,6 +713,19 @@ def score_symbol(src, symbol: str,
     else:
         direction = "long" if m15.get("rsi14", 50) < 50 else "short"
 
+    # ── Entry momentum (Strategy Fix Plan F2a) — data only, no scoring change ──
+    # Reuses the 5m/15m raw DataFrames already fetched above — zero extra API calls.
+    m5_roc_pct = _roc_pct(_raw_dfs.get("5m"), 3)    # ~last 15 min on 5m tf
+    m15_roc_pct = _roc_pct(_raw_dfs.get("15m"), 1)  # last closed 15m candle
+    entry_momentum = {
+        "m5_roc_pct": m5_roc_pct,
+        "m15_roc_pct": m15_roc_pct,
+        "aligned": bool(
+            (direction == "long" and m5_roc_pct is not None and m5_roc_pct > 0) or
+            (direction == "short" and m5_roc_pct is not None and m5_roc_pct < 0)
+        ),
+    }
+
     s_pos, n_pos = _score_positioning(funding_primary, oi_primary,
                                        funding_secondary, oi_secondary,
                                        taker_ratio=taker_ratio,
@@ -717,6 +752,15 @@ def score_symbol(src, symbol: str,
     close = m15.get("close", 0)
     atr_pct = m15.get("atr_pct", 0)
     levels = _stop_target(tf_data, direction) if close > 0 else {}
+
+    # ── Dynamic TP (Strategy Fix Plan F3a) — additive field only; TP1/2/3 unchanged ──
+    if levels:
+        sl_dist = abs(close - levels.get("sl", close))
+        levels["tp_dyn"] = round(
+            close + TP_DYN_R * sl_dist if direction == "long" else close - TP_DYN_R * sl_dist,
+            6,
+        )
+
     sizing = _size_suggestion(account, risk_pct, close, levels.get("sl", close), user_leverage)
 
     # ── New: probability, leverage, duration ─────────────────────────────
@@ -888,6 +932,7 @@ def score_symbol(src, symbol: str,
         "close": close,
         "levels": levels,
         "sizing": sizing,
+        "entry_momentum": entry_momentum,
         # ── Probability & EV ──
         "probability": {
             "p_win":       p_win,

telegram_alert.py

@@ -103,6 +103,31 @@ def _rr(card: dict) -> str:
 
 # ── Message builder ───────────────────────────────────────────────────────────
 
+def _tier_line(conf: float) -> str:
+    """Confidence tier prefix (Strategy Fix Plan F1a).
+
+    Alert threshold stays 8.8 (data collection continues); this only labels
+    the message so Utkarsh can tell trade-grade from watch-only at a glance.
+    Auto-trade gate (CONF_MIN=9.0, per ADDENDUM) is a separate, later concern.
+    """
+    if conf >= 9.0:
+        return "💎 <b>TRADE-GRADE</b>"
+    if conf >= 8.8:
+        return "🔭 <b>WATCH ONLY</b> — below auto-trade bar"
+    return ""
+
+
+def _momentum_line(card: dict) -> str:
+    """Entry-momentum line (Strategy Fix Plan F2b). Empty if data unavailable."""
+    mom = card.get("entry_momentum") or {}
+    m15v = mom.get("m15_roc_pct")
+    if m15v is None:
+        return ""
+    mark = "✓ aligned" if mom.get("aligned") else "⚠ AGAINST direction"
+    sign = "+" if m15v >= 0 else ""
+    return f"⚡ Momentum 15m: {sign}{m15v:.2f}% ({mark})"
+
+
 def _order_flow_line(card: dict) -> str:
     """Format the taker buy/sell ratio line for Telegram. Returns '' if unavailable."""
     taker_ratio = (
@@ -158,8 +183,12 @@ def build_message(card: dict, tv_sym: str) -> str:
         else f"{state_emoji} HMM  <b>{state}</b>"
     )
     flow_line = _order_flow_line(card)
+    tier_line = _tier_line(float(conf))
+    momentum_line = _momentum_line(card)
+    tp_dyn = lvl.get("tp_dyn")
 
     lines = [
+        *([tier_line] if tier_line else []),
         f"{dir_emoji} <b>{sym}  {direction}  ·  {conf:.1f}/10</b>",
         "",
         f"📍 <b>Entry</b>  <code>{_fmt_price(card.get('close'))}</code>",
@@ -167,6 +196,8 @@ def build_message(card: dict, tv_sym: str) -> str:
         f"🎯 <b>TP1</b>    <code>{_fmt_price(lvl.get('tp1'))}</code>   R/R {_rr(card)}",
         f"   <b>TP2</b>    <code>{_fmt_price(lvl.get('tp2'))}</code>",
         f"   <b>TP3</b>    <code>{_fmt_price(lvl.get('tp3'))}</code>",
+        *([f"   <b>TP-dyn</b> <code>{_fmt_price(tp_dyn)}</code>  (0.7R)"] if tp_dyn is not None else []),
+        *([momentum_line] if momentum_line else []),
         "",
         f"⚙️  Leverage  <b>{lev.get('user_leverage', '—')}x</b>   Margin  <b>{_money(lev.get('margin_to_post'))}</b>",
         f"💸 Loss@SL   <b>{_money(lev.get('loss_at_stop'))}</b>   Risk  <b>{_money(sz.get('risk_usd'))}</b>",