Harden Telegram bot, add EUR/GBP strategies, parallelize scans

Telegram reliability: rate-limited sends (1 msg/s), dashboard lock,
WebSocket JSON/price error handling, markdown escaping, level cache
TTL, cooldown cleanup, breach task tracking, graceful shutdown.

Telegram speed: parallelize 3-pair scans with asyncio.gather(),
increase thread pool 2→4, parallelize boot-up initial scan.

Strategy: add EUR/USD and GBP/USD pullback-buy strategies with
per-pair configs, optimize XAU TP to 0.9×ATR, block hours 8/9
for XAU and hour 17 for GBP.

Backtest: add --max-hours flag to evaluate.py for time-exit support.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backtest/evaluate.py

@@ -269,6 +269,7 @@ def evaluate_outcomes(
     trades: List[Trade],
     m5_data: Dict[str, pd.DataFrame],
     max_bars: int = 500,
+    max_hours: int = 0,
 ) -> List[Trade]:
     """
     For each trade, scan forward in M5 data to check if TP1 or SL hit first.
@@ -305,7 +306,9 @@ def evaluate_outcomes(
                 continue
 
             start = int(start_indices[0])
-            end = min(start + max_bars, len(highs_gpu))
+            time_limit = max_hours * 12 if max_hours > 0 else max_bars
+            effective_max = min(time_limit, max_bars)
+            end = min(start + effective_max, len(highs_gpu))
 
             if start >= end:
                 continue
@@ -532,6 +535,8 @@ def main():
                         help="Max M5 bars to scan for SL/TP hit (default: 1000 = ~83h)")
     parser.add_argument("--pair", default=None,
                         help="Single pair to evaluate (EURUSD, USDJPY, GBPUSD, XAUUSD)")
+    parser.add_argument("--max-hours", type=int, default=0,
+                        help="Max hours to hold a trade before time-exit (0 = disabled)")
     args = parser.parse_args()
 
     eval_tfs = EVAL_TIMEFRAMES
@@ -599,7 +604,7 @@ def main():
     m5_data = {k: v for k, v in m5_data.items() if v is not None}
 
     t2 = time.time()
-    all_trades = evaluate_outcomes(all_trades, m5_data, max_bars=args.max_outcome_bars)
+    all_trades = evaluate_outcomes(all_trades, m5_data, max_bars=args.max_outcome_bars, max_hours=args.max_hours)
     print(f"  Outcomes evaluated in {time.time() - t2:.3f}s")
 
     # ── 4. Report ────────────────────────────────────────────────