Prevent torch forecast fee churn exits

This commit is contained in:
Codex
2026-06-30 14:37:00 +03:00
parent 0cfd89980e
commit 56701d02f1
2 changed files with 99 additions and 5 deletions
+27 -3
View File
@@ -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",
0.86,
"HOLD",
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,
+72 -2
View File
@@ -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: