BUG: index_base forecasting in the past with "monthly" `index_metho…

…d` (#354)

docs/source/i_whatsnew.rst

@@ -56,6 +56,9 @@ email contact through **[email protected]**.
    * - Bug
      - :class:`~rateslib.instruments.IndexFixedRateBond` now correctly initialises when using a
        :class:`pandas.Series` as ``index_fixings`` argument.
+   * - Bug
+     - :class:`~rateslib.instruments.ZCIS` now raises if an `index_base` cannot be forecast from an *IndexCurve*
+       and the value should be known and input directly, to avoid *Solver* calibration failures.
 
 1.3.0 (9th July 2024)
 ***********************

python/rateslib/instruments.py

@@ -6359,9 +6359,17 @@ def rate(
         )
         if self.leg2_index_base is NoInput.blank:
             # must forecast for the leg
-            self.leg2.index_base = curves[2].index_value(
+            forecast_value = curves[2].index_value(
                 self.leg2.schedule.effective, self.leg2.index_method
             )
+            if abs(forecast_value) < 1e-13:
+                raise ValueError(
+                    "Forecasting the `index_base` for the ZCIS yielded 0.0, which is infeasible.\n"
+                    "This might occur if the ZCIS starts in the past, or has a 'monthly' "
+                    "`index_method` which uses the 1st day of the effective month, which is in the "
+                    "past.\nA known `index_base` value should be input with the ZCIS specification."
+                )
+            self.leg2.index_base = forecast_value
         leg2_npv = self.leg2.npv(curves[2], curves[3])
 
         return self.leg1._spread(-leg2_npv, curves[0], curves[1]) / 100

python/tests/test_instruments.py

@@ -1275,6 +1275,24 @@ def test_leg2_index_base(self, curve):
         result = zcis.rate(curves=[curve, curve, i_curve, curve])
         assert result > (prior + 100)
 
+    def test_solver_failure_unspecified_index_base(self, curve):
+        # GH 349
+        curve = Curve({dt(2022, 1, 15): 1.0, dt(2023, 1, 1): 0.98})
+        i_curve = IndexCurve({dt(2022, 1, 15): 1.0, dt(2023, 1, 1): 0.99}, index_base=200.0)
+        zcis = ZCIS(
+            effective=dt(2022, 1, 15),
+            termination="9m",
+            frequency="A",
+            convention="1+",
+            calendar="nyc",
+            leg2_index_method="monthly",
+            currency="usd",
+            curves=[curve, curve, i_curve, curve],
+            leg2_index_lag=3,
+        )
+        with pytest.raises(ValueError, match="Forecasting the `index_base`"):
+            zcis.rate()
+
 
 class TestValue:
     def test_npv_adelta_cashflows_raises(self):