feat: add backtesting functionality with UI and API endpoints

- Introduced backtesting page and fragment in the dashboard for running backtests and viewing recent reports.
- Implemented backtest run logic with configuration options including event path, starting balances, trade capital, and fee profiles.
- Added recent backtest reports storage and retrieval.
- Created a new strategy module for statistical arbitrage experiments with validation on configuration parameters.
- Updated settings to include parameters for the statistical arbitrage strategy.
- Enhanced dashboard controls to support the new strategy mode.
- Added unit tests for backtesting functionality and strategy validation.
- Updated templates for backtesting UI integration.

tests/unit/test_settings_validation.py

@@ -53,3 +53,20 @@ def test_valid_security_configuration_passes() -> None:
     )
 
     assert settings.kraken_api_key_permissions == "query,trade"
+
+
+def test_stat_arb_entry_zscore_must_exceed_exit_zscore() -> None:
+    with pytest.raises(ValidationError):
+        Settings(
+            _env_file=None,
+            STRATEGY_STAT_ARB_ENTRY_ZSCORE="0.5",
+            STRATEGY_STAT_ARB_EXIT_ZSCORE="0.5",
+        )
+
+
+def test_stat_arb_lookback_window_must_be_at_least_two() -> None:
+    with pytest.raises(ValidationError):
+        Settings(
+            _env_file=None,
+            STRATEGY_STAT_ARB_LOOKBACK_WINDOW="1",
+        )

tests/unit/test_stat_arb_experiment.py

@@ -0,0 +1,66 @@
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+
+from arbitrade.strategy.stat_arb import StatArbExperiment, StatArbExperimentConfig
+
+
+def test_stat_arb_experiment_warmup_then_entry_and_exit() -> None:
+    started_at = datetime(2026, 6, 2, 12, 0, tzinfo=UTC)
+    experiment = StatArbExperiment(
+        StatArbExperimentConfig(
+            pair_a="BTC/USD",
+            pair_b="ETH/USD",
+            lookback_window=5,
+            entry_zscore=1.5,
+            exit_zscore=0.2,
+            max_holding_seconds=0.5,
+        )
+    )
+
+    # Warmup with nearly stationary spread around 0.
+    for idx in range(5):
+        signal = experiment.observe(
+            price_a=100.0 + (0.02 * idx),
+            price_b=100.0,
+            observed_at=started_at + timedelta(seconds=idx),
+        )
+
+    assert signal.action in {"warmup", "hold"}
+
+    # Large positive spread should trigger short-spread entry.
+    entry = experiment.observe(
+        price_a=104.0,
+        price_b=100.0,
+        observed_at=started_at + timedelta(seconds=10),
+    )
+    assert entry.action == "enter_short_spread"
+    assert entry.position == "short"
+    assert entry.zscore is not None
+
+    # Mean reversion toward center should trigger exit.
+    exit_signal = experiment.observe(
+        price_a=100.05,
+        price_b=100.0,
+        observed_at=started_at + timedelta(seconds=11),
+    )
+    assert exit_signal.action == "exit_position"
+    assert exit_signal.position == "flat"
+
+
+def test_stat_arb_experiment_rejects_invalid_prices() -> None:
+    experiment = StatArbExperiment(
+        StatArbExperimentConfig(
+            pair_a="BTC/USD",
+            pair_b="ETH/USD",
+            lookback_window=5,
+        )
+    )
+
+    at = datetime(2026, 6, 2, 12, 0, tzinfo=UTC)
+    try:
+        experiment.observe(price_a=0.0, price_b=100.0, observed_at=at)
+    except ValueError as exc:
+        assert "prices must be > 0" in str(exc)
+    else:
+        raise AssertionError("Expected ValueError for non-positive price")