Prevent torch forecast fee churn exits

crypto_spot_bot/strategy.py

@@ -901,6 +901,9 @@ def _torch_forecast_exit_signal(
         "estimated_exit_net_percent": round(estimated_exit_net_percent, 4),
         "atr_14": latest.atr_14 if latest else None,
     }
+    hold_seconds = (utc_now() - position.opened_at).total_seconds()
+    diagnostics["hold_seconds"] = hold_seconds
+    diagnostics["min_hold_seconds"] = settings.min_hold_seconds
     if effective_stop_loss is not None and price <= effective_stop_loss:
         return Signal(position.symbol, "SELL", 1.0, "torch_forecast: stop-loss hit", diagnostics)
     if price >= position.take_profit:
@@ -928,12 +931,33 @@ def _torch_forecast_exit_signal(
             )
         return Signal(position.symbol, "SELL", 0.78, "torch_forecast: no valid PyTorch forecast to hold", diagnostics)
     if bool(forecast.get("block_entry", False)) or expected_return <= 0.0 or probability_up <= 0.50:
+        if hold_seconds < settings.min_hold_seconds:
+            diagnostics["forecast_exit_blocked_by_min_hold"] = True
+            return Signal(
+                position.symbol,
+                "HOLD",
+                0.46,
+                "torch_forecast: minimum hold protects against fee churn",
+                diagnostics,
+            )
+        forecast_exit = _forecast_exit_signal(
+            forecast=forecast,
+            position=position,
+            price=price,
+            estimated_exit_net_percent=estimated_exit_net_percent,
+            stop_loss_percent=stop_loss_percent,
+            min_edge_percent=min_edge,
+        )
+        if forecast_exit is not None:
+            action, confidence, reason = forecast_exit
+            return Signal(position.symbol, action, confidence, reason, diagnostics)
+        diagnostics["forecast_exit_blocked_by_cost"] = True
         return Signal(
             position.symbol,
-            "SELL",
+            "HOLD",
-            0.86,
+            0.44,
             (
-                "torch_forecast: PyTorch forecast turned negative; "
+                "torch_forecast: forecast weakened, but exit is not worth fees; "
                 f"p_up={probability_up:.3f}, expected={expected_return:.4f}%"
             ),
             diagnostics,

tests/test_strategy.py

@@ -826,7 +826,18 @@ def test_torch_forecast_rebound_fallback_can_be_disabled(make_settings, tmp_path
 def test_torch_forecast_exits_when_forecast_turns_negative(make_settings, tmp_path) -> None:
     settings = make_settings(tmp_path, strategy_mode="torch_forecast", stop_loss_percent=0.04)
     strategy = SpotStrategy(settings)
-    position = Position(1, "SOLUSDT", 1, 100, 100, 0.1, 96, 120, 103)
+    position = Position(
+        1,
+        "SOLUSDT",
+        1,
+        100,
+        100,
+        0.1,
+        96,
+        120,
+        103,
+        opened_at=utc_now() - timedelta(seconds=600),
+    )
     ticker = Ticker("SOLUSDT", 101, 100.99, 101.01, 10_000_000, 1000, 1.0)
 
     signal = strategy.exit_signal(
@@ -844,7 +855,66 @@ def test_torch_forecast_exits_when_forecast_turns_negative(make_settings, tmp_pa
     )
 
     assert signal.action == "SELL"
-    assert "torch_forecast" in signal.reason
+    assert "прогноз" in signal.reason
+
+
+def test_torch_forecast_holds_negative_forecast_during_min_hold(make_settings, tmp_path) -> None:
+    settings = make_settings(tmp_path, strategy_mode="torch_forecast", min_hold_seconds=180)
+    strategy = SpotStrategy(settings)
+    position = Position(1, "SOLUSDT", 1, 100, 100, 0.1, 96, 120, 103)
+    ticker = Ticker("SOLUSDT", 101, 100.99, 101.01, 10_000_000, 1000, 1.0)
+
+    signal = strategy.exit_signal(
+        position,
+        _trend_entry_candles(),
+        ticker,
+        forecast={
+            "usable": True,
+            "model": "torch_lstm",
+            "expected_return_percent": -0.08,
+            "probability_up": 0.43,
+            "skill": 0.18,
+            "block_entry": True,
+        },
+    )
+
+    assert signal.action == "HOLD"
+    assert signal.diagnostics["forecast_exit_blocked_by_min_hold"] is True
+
+
+def test_torch_forecast_holds_fee_churn_exit_after_min_hold(make_settings, tmp_path) -> None:
+    settings = make_settings(tmp_path, strategy_mode="torch_forecast", min_hold_seconds=60)
+    strategy = SpotStrategy(settings)
+    position = Position(
+        1,
+        "BTCUSDT",
+        1,
+        100,
+        100,
+        0.1,
+        96,
+        120,
+        100.1,
+        opened_at=utc_now() - timedelta(seconds=600),
+    )
+    ticker = Ticker("BTCUSDT", 99.99, 99.98, 100.0, 10_000_000, 1000, 1.0)
+
+    signal = strategy.exit_signal(
+        position,
+        _trend_entry_candles(),
+        ticker,
+        forecast={
+            "usable": True,
+            "model": "torch_lstm",
+            "expected_return_percent": -0.01,
+            "probability_up": 0.499,
+            "skill": 0.18,
+            "block_entry": False,
+        },
+    )
+
+    assert signal.action == "HOLD"
+    assert signal.diagnostics["forecast_exit_blocked_by_cost"] is True
 
 
 def test_torch_forecast_rebound_fallback_holds_without_model(make_settings, tmp_path) -> None: