feat: add Nailong Fund advisor capabilities

tests/unit/service/test_dynamic_allocation_optimizer.py

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+from decimal import Decimal
+
+from app.service.dynamic_allocation_optimizer import (
+    AssetClassMarketMetric,
+    DynamicAllocationOptimizer,
+)
+
+
+def metric(
+    asset_class: str, trailing_return: str, drawdown: str, turnover: str
+) -> AssetClassMarketMetric:
+    return AssetClassMarketMetric(
+        asset_class=asset_class,
+        trailing_120d_return_pct=Decimal(trailing_return),
+        max_drawdown_pct=Decimal(drawdown),
+        average_daily_turnover_amount=Decimal(turnover),
+        product_count=2,
+    )
+
+
+def test_optimizer_tilts_strategic_weights_using_return_drawdown_and_liquidity() -> None:
+    result = DynamicAllocationOptimizer.optimize(
+        {"cash_management_etf": 15, "bond_etf": 45, "equity_etf": 40},
+        [
+            metric("cash_management_etf", "1", "0", "50000000"),
+            metric("bond_etf", "5", "-3", "8000000"),
+            metric("equity_etf", "15", "-20", "10000000"),
+        ],
+        return_target_lower_pct=Decimal("6"),
+        max_drawdown_pct=Decimal("15"),
+        liquidity_requirement="within_30_days",
+    )
+
+    assert result.dynamic is True
+    assert result.metric_coverage_pct == Decimal("100")
+    assert result.weights["bond_etf"] > 45
+    assert result.weights["cash_management_etf"] < 15
+    assert sum(result.weights.values()) == 100
+    assert {item["asset_class"] for item in result.factors} == {
+        "cash_management_etf", "bond_etf", "equity_etf"
+    }
+
+
+def test_optimizer_applies_drawdown_cap_even_when_equity_metrics_are_strong() -> None:
+    result = DynamicAllocationOptimizer.optimize(
+        {"cash_management_etf": 5, "bond_etf": 15, "equity_etf": 80},
+        [
+            metric("cash_management_etf", "1", "0", "50000000"),
+            metric("bond_etf", "2", "-1", "5000000"),
+            metric("equity_etf", "30", "-5", "100000000"),
+        ],
+        return_target_lower_pct=Decimal("8"),
+        max_drawdown_pct=Decimal("10"),
+        liquidity_requirement="within_30_days",
+    )
+
+    assert result.weights["equity_etf"] <= 20
+    assert sum(result.weights.values()) == 100