Merge a47e28d into 77b7d00

Author: bashtage

arch/tests/unitroot/test_unitroot.py

@@ -647,23 +647,27 @@ def test_nc_warning():
 
 
 @pytest.mark.parametrize("nobs", np.arange(1, 11).tolist())
-@pytest.mark.parametrize("stat", [ADF, PhillipsPerron])
+@pytest.mark.parametrize("stat", [ADF, PhillipsPerron, KPSS])
 @pytest.mark.parametrize("trend", ["n", "c", "ct", "ctt"])
 def test_wrong_exceptions(stat, nobs, trend):
-    y = np.random.standard_normal((nobs,))
-    if stat is PhillipsPerron and trend == "ctt":
+    if (stat in (PhillipsPerron, KPSS) and trend == "ctt") or (
+        stat is KPSS and trend == "n"
+    ):
         return
+    y = np.random.standard_normal((nobs,))
     try:
         stat(y, trend=trend).stat
     except InfeasibleTestException:
         pass
 
 
 @pytest.mark.parametrize("nobs", [2, 10, 100])
-@pytest.mark.parametrize("stat", [ADF, PhillipsPerron])
+@pytest.mark.parametrize("stat", [ADF, PhillipsPerron, KPSS])
 @pytest.mark.parametrize("trend", ["n", "c", "ct", "ctt"])
 def test_wrong_exceptions_nearly_constant_series(stat, nobs, trend):
-    if stat is PhillipsPerron and trend == "ctt":
+    if (stat in (PhillipsPerron, KPSS) and trend == "ctt") or (
+        stat is KPSS and trend == "n"
+    ):
         return
     y = np.zeros((nobs,))
     y[-1] = 1.0
@@ -679,6 +683,12 @@ def test_phillips_perron_specifed_lag():
         PhillipsPerron(y, lags=12).stat
 
 
+def test_kpss_legacy():
+    y = np.random.standard_normal(4)
+    with pytest.raises(InfeasibleTestException, match="The number of observations 4"):
+        KPSS(y, lags=-1).stat
+
+
 @pytest.mark.parametrize(
     "x", [np.ones((2, 10)), np.full((20, 2), np.nan), np.ones((20, 2))]
 )

arch/unitroot/unitroot.py

@@ -1261,6 +1261,16 @@ def __init__(
         self._alternative_hypothesis = "The process contains a unit root."
         self._resids: Optional[ArrayLike1D] = None
 
+    def _check_specification(self) -> None:
+        trend_order = len(self._trend)
+        lag_len = 0 if self._lags is None else self._lags
+        required = max(1 + trend_order, lag_len)
+        if self._y.shape[0] < (required):
+            raise InfeasibleTestException(
+                f"A minmum of {required} observations are needed to run an ADF with "
+                f"trend {self.trend} and the user-specified number of lags."
+            )
+
     def _compute_statistic(self) -> None:
         # 1. Estimate model with trend
         nobs, y, trend = self._nobs, self._y, self._trend
@@ -1274,6 +1284,12 @@ def _compute_statistic(self) -> None:
             else:
                 self._autolag()
         assert self._lags is not None
+        if u.shape[0] < self._lags:
+            raise InfeasibleTestException(
+                f"The number of observations {u.shape[0]} is less than the number of"
+                f"lags in the long-run covariance estimator, {self._lags}. You must have "
+                "lags <= nobs."
+            )
         lam = cov_nw(u, self._lags, demean=False)
         s = cumsum(u)
         self._stat = 1 / (nobs ** 2.0) * sum(s ** 2.0) / lam
@@ -1305,6 +1321,12 @@ def _autolag(self) -> None:
             resids_prod /= self._nobs / 2
             s0 += resids_prod
             s1 += i * resids_prod
+        if s0 <= 0:
+            raise InfeasibleTestException(
+                f"Residuals are all zero and so automatic bandwidth selection cannot "
+                f"be used. This is usually an indication that the series being testes "
+                f"is too small or have constant values."
+            )
         s_hat = s1 / s0
         pwr = 1.0 / 3.0
         gamma_hat = 1.1447 * power(s_hat * s_hat, pwr)

doc/source/changes/4.0.txt

@@ -4,8 +4,8 @@ Version 4
 
 Since 4.12
 ==========
-- Improved exceptions in :class:`~arch.unitroot.ADF` and
-  :class:`~arch.unitroot.PhillipsPerron` when test specification is infeasible
+- Improved exceptions in :class:`~arch.unitroot.ADF`,  :class:`~arch.unitroot.KPSS`,
+  and :class:`~arch.unitroot.PhillipsPerron` when test specification is infeasible
   to the time series being too short or the required regression model being
   reduced rank (:issue:`364`).
 - Fixed a bug when using "bca" confidence intervals with ``extra_kwargs`` (:issue:`366`).