feat: add _run_dcf, _run_ev_ebitda, _run_ev_revenue, _run_price_to_book

1 files changed, 104 insertions, 0 deletions

diff --git a/backend/tests/test_api.py b/backend/tests/test_api.py
index a5c4eb5..8c7edb8 100644
--- a/backend/tests/test_api.py
+++ b/backend/tests/test_api.py
@@ -684,3 +684,107 @@ def test_dcf_capped_growth_rate_skips_sign_flip() -> None:
     series = pd.Series([-10.0, 20.0], index=pd.to_datetime(["2022", "2023"]))
     result = data_service._dcf_capped_growth_rate(series)
     assert result is None
+
+
+def test_run_dcf_happy_path() -> None:
+    import pandas as pd
+    fcf = pd.Series(
+        [70.0, 80.0, 90.0, 100.0],
+        index=pd.to_datetime(["2021", "2022", "2023", "2024"]),
+    )
+    result = data_service._run_dcf(fcf, shares_outstanding=1_000_000_000.0)
+    assert "intrinsic_value_per_share" in result
+    assert result["intrinsic_value_per_share"] > 0
+    assert "growth_rate_used" in result
+    assert "enterprise_value" in result
+    assert "net_debt" in result
+
+
+def test_run_dcf_negative_base_fcf() -> None:
+    import pandas as pd
+    # last (most recent) FCF is negative
+    fcf = pd.Series(
+        [100.0, 90.0, 80.0, -50.0],
+        index=pd.to_datetime(["2021", "2022", "2023", "2024"]),
+    )
+    result = data_service._run_dcf(fcf, shares_outstanding=1_000_000_000.0)
+    assert "error" in result
+    assert result["error"]
+
+
+def test_run_dcf_insufficient_history() -> None:
+    import pandas as pd
+    fcf = pd.Series([100.0], index=pd.to_datetime(["2024"]))
+    result = data_service._run_dcf(fcf, shares_outstanding=1_000_000_000.0)
+    assert result == {}
+
+
+def test_run_dcf_zero_shares() -> None:
+    import pandas as pd
+    fcf = pd.Series([100.0, 110.0], index=pd.to_datetime(["2023", "2024"]))
+    result = data_service._run_dcf(fcf, shares_outstanding=0.0)
+    assert result == {}
+
+
+def test_run_ev_ebitda_happy_path() -> None:
+    result = data_service._run_ev_ebitda(
+        ebitda=100.0,
+        total_debt=50.0,
+        total_cash=20.0,
+        preferred_equity=0.0,
+        minority_interest=0.0,
+        shares_outstanding=10.0,
+        target_multiple=15.0,
+    )
+    # implied_ev = 100 * 15 = 1500; net_debt = 50-20 = 30; equity = 1470; per_share = 147
+    assert result["implied_price_per_share"] == 147.0
+    assert result["implied_ev"] == 1500.0
+    assert result["net_debt"] == 30.0
+
+
+def test_run_ev_ebitda_zero_ebitda() -> None:
+    result = data_service._run_ev_ebitda(
+        ebitda=0.0, total_debt=0.0, total_cash=0.0,
+        preferred_equity=0.0, minority_interest=0.0,
+        shares_outstanding=10.0, target_multiple=15.0,
+    )
+    assert result == {}
+
+
+def test_run_ev_revenue_happy_path() -> None:
+    result = data_service._run_ev_revenue(
+        revenue=500.0,
+        total_debt=50.0,
+        total_cash=20.0,
+        preferred_equity=0.0,
+        minority_interest=0.0,
+        shares_outstanding=10.0,
+        target_multiple=5.0,
+    )
+    # implied_ev = 500*5 = 2500; net_debt = 30; equity = 2470; per_share = 247
+    assert result["implied_price_per_share"] == 247.0
+
+
+def test_run_ev_revenue_zero_revenue() -> None:
+    result = data_service._run_ev_revenue(
+        revenue=0.0, total_debt=0.0, total_cash=0.0,
+        preferred_equity=0.0, minority_interest=0.0,
+        shares_outstanding=10.0, target_multiple=5.0,
+    )
+    assert result == {}
+
+
+def test_run_price_to_book_happy_path() -> None:
+    result = data_service._run_price_to_book(
+        book_value_per_share=20.0, target_multiple=3.0
+    )
+    assert result["implied_price_per_share"] == 60.0
+    assert result["target_multiple_used"] == 3.0
+    assert result["book_value_per_share"] == 20.0
+
+
+def test_run_price_to_book_zero_bvps() -> None:
+    result = data_service._run_price_to_book(
+        book_value_per_share=0.0, target_multiple=3.0
+    )
+    assert result == {}