Use Torch forecast as primary strategy

tests/test_config.py

@@ -77,7 +77,40 @@ def test_default_symbols_are_fixed_trend_pairs(tmp_path, monkeypatch) -> None:
     assert settings.auto_select_symbols is False
     assert settings.top_symbols_count == 3
     assert settings.symbols == FIXED_SPOT_SYMBOLS
-    assert settings.strategy_mode == "trend_macd"
+    assert settings.strategy_mode == "torch_forecast"
     assert settings.base_interval == "60"
     assert settings.trend_interval == "D"
     assert settings.risk_per_trade_percent == 0.01
+    assert settings.time_series_forecast_enabled is True
+
+
+def test_torch_forecast_forces_fixed_three_symbols(tmp_path, monkeypatch) -> None:
+    for key in (
+        "AUTO_SELECT_SYMBOLS",
+        "TOP_SYMBOLS_COUNT",
+        "SYMBOLS",
+        "STRATEGY_MODE",
+        "TIME_SERIES_FORECAST_ENABLED",
+    ):
+        monkeypatch.delenv(key, raising=False)
+    monkeypatch.setenv("TRADING_MODE", "paper")
+    env_file = tmp_path / ".env"
+    env_file.write_text(
+        "\n".join(
+            [
+                "TRADING_MODE=paper",
+                "STRATEGY_MODE=torch_forecast",
+                "AUTO_SELECT_SYMBOLS=true",
+                "TOP_SYMBOLS_COUNT=9",
+                "SYMBOLS=DOGEUSDT,XRPUSDT",
+            ]
+        ),
+        encoding="utf-8",
+    )
+
+    settings = load_settings(env_file)
+
+    assert settings.auto_select_symbols is False
+    assert settings.top_symbols_count == 3
+    assert settings.symbols == FIXED_SPOT_SYMBOLS
+    assert settings.time_series_forecast_enabled is True

tests/test_execution.py

@@ -160,6 +160,31 @@ def test_trend_macd_broker_blocks_dca_for_same_symbol(make_settings, tmp_path) -
     assert len(broker.open_positions()) == 1
 
 
+def test_torch_forecast_broker_blocks_dca_for_same_symbol(make_settings, tmp_path) -> None:
+    settings = make_settings(
+        tmp_path,
+        strategy_mode="torch_forecast",
+        min_position_usdt=1,
+        max_position_usdt=20,
+        max_symbol_exposure_usdt=20,
+        max_total_exposure_usdt=80,
+        max_open_positions=3,
+        max_positions_per_symbol=20,
+        max_entries_per_minute=0,
+    )
+    storage = Storage(settings.database_path)
+    broker = PaperBroker(settings, storage)
+    ticker = Ticker("BTCUSDT", 100, 99.9, 100.1, 10_000_000, 100, 0)
+    instrument = Instrument("BTCUSDT", "BTC", "USDT", "Trading", 0.01, 0.000001, 0.000001, 1)
+
+    first = broker.buy(Signal("BTCUSDT", "BUY", 0.8, "first", {"position_notional_usdt": 2}), ticker, instrument, {"BTCUSDT": 100})
+    second = broker.buy(Signal("BTCUSDT", "BUY", 0.8, "second", {"position_notional_usdt": 2}), ticker, instrument, {"BTCUSDT": 100})
+
+    assert first is not None
+    assert second is None
+    assert len(broker.open_positions()) == 1
+
+
 def test_trend_macd_closes_old_paper_positions_outside_symbol_universe(make_settings, tmp_path) -> None:
     settings = make_settings(
         tmp_path,

tests/test_strategy.py

@@ -233,6 +233,81 @@ def test_trend_macd_exits_on_atr_trailing_stop(make_settings, tmp_path) -> None:
     assert "ATR trailing" in signal.reason
 
 
+def test_torch_forecast_buys_only_from_positive_torch_edge(make_settings, tmp_path) -> None:
+    settings = make_settings(
+        tmp_path,
+        strategy_mode="torch_forecast",
+        max_position_usdt=25,
+        stop_loss_percent=0.04,
+        risk_per_trade_percent=0.01,
+    )
+    strategy = SpotStrategy(settings)
+    ticker = Ticker("BTCUSDT", 105, 104.99, 105.01, 10_000_000, 1000, 1.0)
+
+    signal = strategy.entry_signal(
+        "BTCUSDT",
+        [],
+        ticker,
+        open_positions_for_symbol=0,
+        forecast={
+            "usable": True,
+            "model": "torch_gru",
+            "expected_return_percent": 0.24,
+            "probability_up": 0.63,
+            "skill": 0.22,
+            "block_entry": False,
+        },
+        account={"equity": 100.0},
+    )
+
+    assert signal.action == "BUY"
+    assert signal.diagnostics["strategy_mode"] == "torch_forecast"
+    assert signal.diagnostics["checks"]["torch_model_ok"] is True
+    assert signal.diagnostics["position_notional_usdt"] == 25.0
+
+
+def test_torch_forecast_blocks_without_valid_torch_model(make_settings, tmp_path) -> None:
+    settings = make_settings(tmp_path, strategy_mode="torch_forecast")
+    strategy = SpotStrategy(settings)
+    ticker = Ticker("ETHUSDT", 105, 104.99, 105.01, 10_000_000, 1000, 1.0)
+
+    signal = strategy.entry_signal(
+        "ETHUSDT",
+        _trend_entry_candles(),
+        ticker,
+        open_positions_for_symbol=0,
+        forecast={"usable": True, "model": "none", "expected_return_percent": 0.5, "probability_up": 0.7},
+        account={"equity": 100.0},
+    )
+
+    assert signal.action == "HOLD"
+    assert signal.diagnostics["checks"]["torch_model_ok"] is False
+
+
+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)
+    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 == "SELL"
+    assert "torch_forecast" in signal.reason
+
+
 def test_strategy_emits_buy_when_score_passes_threshold(make_settings, tmp_path) -> None:
     settings = make_settings(tmp_path)
     strategy = SpotStrategy(settings)