tested difficult edge cases following bug fix from PR #113 (thanks!)

cvxportfolio/result.py

@@ -24,6 +24,7 @@
 from __future__ import annotations, print_function
 
 import collections
+import logging
 from typing import Dict
 
 import matplotlib.pyplot as plt
@@ -63,8 +64,13 @@ def __init__(self, universe, trading_calendar, costs):
         self._current_universe = pd.Index(universe)
         self._indexer = np.arange(len(universe), dtype=int)
 
+    @property
+    def _current_full_universe(self):
+        """Helper property used by _change_universe."""
+        return self._h.columns
+
     def _change_universe(self, new_universe):
-        """Change current universe (columns of dataframes) during backtest."""
+        """Change current universe (columns of dataframes) during back-test."""
 
         # print('new universe')
         # print(new_universe)
@@ -83,9 +89,12 @@ def _change_universe(self, new_universe):
                 joined = new_universe
 
             # otherwise we lose the ordering :(
-            else: #TODO: write testcase for this
+            else:
+                logging.info(
+                    f"{self.__class__.__name__} joining new universe with old")
                 joined = pd.Index(
-                    sorted(set(self._current_universe[:-1]
+                    # need to join with full, not current!
+                    sorted(set(self._current_full_universe[:-1]
                         ).union(new_universe[:-1])))
                 joined = joined.append(new_universe[-1:])
 

cvxportfolio/tests/test_simulator.py

@@ -59,6 +59,38 @@ def test_simulator_raises(self):
                 columns=['X', 'USDOLLAR']),
                 volumes=pd.DataFrame([[0.]]))
 
+    def test_backtest_with_difficult_universe_changes(self):
+        """Test back-test with assets that both enter and exit at same time."""
+        rets = pd.DataFrame(self.returns.iloc[:, -10:], copy=True)
+        volumes = pd.DataFrame(self.volumes.iloc[:, -9:], copy=True)
+        prices = pd.DataFrame(self.prices.iloc[:, -9:], copy=True)
+        rets.iloc[15:25, 1:3] = np.nan
+        rets.iloc[9:17, 3:5] = np.nan
+        rets.iloc[8:15, 5:7] = np.nan
+        rets.iloc[17:29, 7:8] = np.nan
+        print(rets.iloc[10:20])
+
+        modified_market_data = cvx.UserProvidedMarketData(
+            returns=rets, volumes=volumes, prices=prices,
+            cash_key='cash',
+            min_history=pd.Timedelta('0d'))
+
+        simulator = cvx.StockMarketSimulator(market_data=modified_market_data)
+
+        policy = cvx.SinglePeriodOptimization(
+            cvx.ReturnsForecast() - 10 * cvx.FullCovariance(),
+            [cvx.LongOnly(), cvx.LeverageLimit(1)])
+
+        bt_result = simulator.backtest(policy, start_time = rets.index[10],
+            end_time = rets.index[20])
+
+        print(bt_result.w)
+
+        self.assertTrue(set(bt_result.w.columns) == set(rets.columns))
+        self.assertTrue(
+            np.all(bt_result.w.iloc[:-1].isnull() == rets.iloc[
+                10:20].isnull()))
+
     def test_prepare_data(self):
         simulator = MarketSimulator(['ZM', 'META'], base_location=self.datadir)
         self.assertTrue(simulator.market_data.returns.shape[1] == 3)