Calibrate Torch forecast thresholds

crypto_spot_bot/config.py

@@ -108,6 +108,8 @@ class Settings:
     time_series_min_candles: int
     time_series_forecast_horizon: int
     time_series_min_edge_percent: float
+    time_series_min_probability_up: float
+    time_series_min_confidence: float
     time_series_max_adjustment: float
     time_series_lstm_enabled: bool
     time_series_lstm_model_path: Path
@@ -185,6 +187,7 @@ def load_settings(env_file: str | Path | None = None) -> Settings:
         top_symbols_count = len(FIXED_SPOT_SYMBOLS)
         symbols = FIXED_SPOT_SYMBOLS
     forecast_enabled_default = strategy_mode == "torch_forecast"
+    min_signal_confidence = _float_env("MIN_SIGNAL_CONFIDENCE", 0.64)
     settings = Settings(
         trading_mode=mode,
         host=os.getenv("HOST", "127.0.0.1"),
@@ -207,7 +210,7 @@ def load_settings(env_file: str | Path | None = None) -> Settings:
         fast_entry_cooldown_seconds=_int_env("FAST_ENTRY_COOLDOWN_SECONDS", 20),
         max_entries_per_minute=_int_env("MAX_ENTRIES_PER_MINUTE", 12),
         websocket_enabled=_bool_env("WEBSOCKET_ENABLED", True),
-        min_signal_confidence=_float_env("MIN_SIGNAL_CONFIDENCE", 0.64),
+        min_signal_confidence=min_signal_confidence,
         max_spread_percent=_float_env("MAX_SPREAD_PERCENT", 0.18),
         min_24h_turnover_usdt=_float_env("MIN_24H_TURNOVER_USDT", 1000000.0),
         pattern_analysis_enabled=_bool_env("PATTERN_ANALYSIS_ENABLED", False),
@@ -247,7 +250,9 @@ def load_settings(env_file: str | Path | None = None) -> Settings:
         time_series_forecast_enabled=_bool_env("TIME_SERIES_FORECAST_ENABLED", forecast_enabled_default),
         time_series_min_candles=_int_env("TIME_SERIES_MIN_CANDLES", 120),
         time_series_forecast_horizon=_int_env("TIME_SERIES_FORECAST_HORIZON", 3),
-        time_series_min_edge_percent=_float_env("TIME_SERIES_MIN_EDGE_PERCENT", 0.04),
+        time_series_min_edge_percent=_float_env("TIME_SERIES_MIN_EDGE_PERCENT", 0.10),
+        time_series_min_probability_up=_float_env("TIME_SERIES_MIN_PROBABILITY_UP", 0.64),
+        time_series_min_confidence=_float_env("TIME_SERIES_MIN_CONFIDENCE", 0.72),
         time_series_max_adjustment=_float_env("TIME_SERIES_MAX_ADJUSTMENT", 0.08),
         time_series_lstm_enabled=_bool_env("TIME_SERIES_LSTM_ENABLED", True),
         time_series_lstm_model_path=Path(os.getenv("TIME_SERIES_LSTM_MODEL_PATH", "runtime/lstm_forecaster.json")),

crypto_spot_bot/dashboard.py

@@ -224,6 +224,8 @@ def _safe_config(settings: Settings) -> dict[str, Any]:
         "time_series_min_candles": settings.time_series_min_candles,
         "time_series_forecast_horizon": settings.time_series_forecast_horizon,
         "time_series_min_edge_percent": settings.time_series_min_edge_percent,
+        "time_series_min_probability_up": settings.time_series_min_probability_up,
+        "time_series_min_confidence": settings.time_series_min_confidence,
         "time_series_max_adjustment": settings.time_series_max_adjustment,
         "time_series_lstm_enabled": settings.time_series_lstm_enabled,
         "time_series_lstm_model_path": str(settings.time_series_lstm_model_path),
@@ -1062,6 +1064,9 @@ HTML = r"""
         ['Лимит на пару', money(config.max_symbol_exposure_usdt)],
         ['Риск на сделку', `${num((config.risk_per_trade_percent || 0) * 100, 2)}% equity`],
         ['RSI входа', `${num(config.trend_rsi_min, 1)} - ${num(config.trend_rsi_max, 1)}`],
+        ['Torch min edge', `${num(config.time_series_min_edge_percent, 3)}%`],
+        ['Torch min P роста', `${num((config.time_series_min_probability_up || 0) * 100, 1)}%`],
+        ['Torch min confidence', `${num(config.time_series_min_confidence, 3)}`],
         ['Лимит в позициях', money(config.max_total_exposure_usdt)],
         ['Лимит позиций', `${config.max_open_positions} всего / ${config.max_positions_per_symbol} на пару`],
         ['Стоп', `${num(config.stop_loss_percent * 100, 2)}%`],

crypto_spot_bot/strategy.py

@@ -644,7 +644,7 @@ def _torch_forecast_entry_signal(
         "expected_edge_ok": expected_return >= min_edge,
         "probability_ok": probability_up >= min_probability,
         "skill_ok": skill > 0.0,
-        "confidence_ok": confidence >= settings.min_signal_confidence,
+        "confidence_ok": confidence >= settings.time_series_min_confidence,
         "spread_ok": spread_ok,
         "liquidity_ok": liquidity_ok,
         "risk_size_ok": position_notional >= settings.min_position_usdt,
@@ -661,6 +661,7 @@ def _torch_forecast_entry_signal(
         "min_edge_percent": min_edge,
         "probability_up": probability_up,
         "min_probability_up": min_probability,
+        "min_confidence": settings.time_series_min_confidence,
         "skill": skill,
         "spread_percent": round(ticker.spread_percent, 5),
         "turnover_24h": ticker.turnover_24h,
@@ -766,7 +767,7 @@ def _is_torch_forecast(forecast: dict) -> bool:
 
 
 def _torch_min_probability(settings: Settings) -> float:
-    return round(_clamp(settings.min_signal_confidence - 0.08, 0.52, 0.68), 4)
+    return round(_clamp(settings.time_series_min_probability_up, 0.45, 0.75), 4)
 
 
 def _torch_forecast_confidence(settings: Settings, forecast: dict) -> float: