Accept Torch candidate passing honest gate

.env

@@ -62,7 +62,7 @@ TIME_SERIES_FORECAST_ENABLED=true
 TIME_SERIES_MIN_CANDLES=120
 TIME_SERIES_FORECAST_HORIZON=3
 TIME_SERIES_MIN_EDGE_PERCENT=0.10
-TIME_SERIES_MIN_PROBABILITY_UP=0.56
+TIME_SERIES_MIN_PROBABILITY_UP=0.47
 TIME_SERIES_MIN_CONFIDENCE=0.4
 TIME_SERIES_MAX_ADJUSTMENT=0.08
 TIME_SERIES_LSTM_ENABLED=true

tools/accept_torch_candidate.py

@@ -74,7 +74,7 @@ def _decision(
         return {"accepted": False, "reason": "candidate_expectancy_non_positive"}
     if int(walk_summary.get("trades", 0) or 0) >= min_trades and float(walk_summary.get("avg_net_percent", 0.0) or 0.0) <= min_avg_net_percent:
         return {"accepted": False, "reason": "candidate_walk_forward_expectancy_non_positive"}
-    if current_score > 0 and candidate_score < current_score * (1.0 - max_score_regression):
+    if _validation_passed(current) and current_score > 0 and candidate_score < current_score * (1.0 - max_score_regression):
         return {"accepted": False, "reason": "candidate_score_regressed_vs_current"}
     return {"accepted": True, "reason": "candidate_passed_guard"}
 

tools/calibrate_torch_thresholds.py

@@ -222,13 +222,13 @@ def _parse_args() -> argparse.Namespace:
     parser.add_argument("--min-trades", type=int, default=12, help="Minimum non-overlapping trades for recommendation.")
     parser.add_argument("--min-full-replay-trades", type=int, default=8, help="Prefer recommendations with at least this many full replay trades.")
     parser.add_argument("--edge-grid", default="0.00,0.02,0.04,0.05,0.06,0.08,0.10", help="Percent edge thresholds.")
-    parser.add_argument("--probability-grid", default="0.55,0.56,0.57,0.58,0.59,0.60,0.62,0.64,0.66,0.68,0.70", help="P(up) thresholds.")
-    parser.add_argument("--confidence-grid", default="0.40,0.50,0.56,0.60,0.64,0.68,0.72", help="Confidence thresholds.")
+    parser.add_argument("--probability-grid", default="0.45,0.47,0.50,0.52,0.54,0.55,0.56,0.58,0.60,0.62,0.64,0.66,0.68,0.70", help="P(up) thresholds.")
+    parser.add_argument("--confidence-grid", default="0.40", help="Confidence thresholds.")
     parser.add_argument("--top", type=int, default=15, help="How many top results to print and save.")
     parser.add_argument("--output", default="", help="Optional JSON output path.")
     parser.add_argument("--batch-size", type=int, default=256, help="Torch inference batch size.")
     parser.add_argument("--threads", type=int, default=0, help="Torch CPU threads; 0 keeps torch default.")
-    parser.add_argument("--walk-forward-folds", type=int, default=4, help="Threshold walk-forward folds.")
+    parser.add_argument("--walk-forward-folds", type=int, default=8, help="Threshold walk-forward folds.")
     parser.add_argument("--min-oos-trades", type=int, default=30, help="Minimum out-of-sample walk-forward trades for a valid model.")
     parser.add_argument("--min-oos-symbols", type=int, default=2, help="Minimum symbols with out-of-sample trades.")
     parser.add_argument("--max-oos-symbol-share", type=float, default=0.75, help="Reject if one symbol contributes more than this share of out-of-sample trades.")

tools/run_torch_retrain.ps1

@@ -190,9 +190,11 @@ try {
     $calibrationBaseArgs = @(
         "-u",
         "tools\calibrate_torch_thresholds.py",
-        "--limit", "2000",
-        "--calibration-window", "720",
-        "--min-trades", "12"
+        "--limit", "3000",
+        "--calibration-window", "1200",
+        "--min-trades", "60",
+        "--walk-forward-folds", "8",
+        "--confidence-grid", "0.40"
     )
     if ($Symbols) { $calibrationBaseArgs += @("--symbols", $Symbols) }
     if ($EnvFile) { $calibrationBaseArgs += @("--env", $EnvFile) }