Qs649 update backtest target allocations (#397)

* Changed datetime to date in get_target_allocations method

* Updated pypi package to qstrader 0.2.8

Author: juliettejames

Diff for: CHANGELOG.md

@@ -1,3 +1,8 @@
+# 0.2.8
+
+* Updates BacktestTradingSession.get_target_allocations() to use burn_in_dt.date() instead of burn_in_dt Timestamp. Previous method compared a Timestamp to a datetime.date.
+* Adds an integration test to check that target allocations match the expected output, including a date index.
+
 # 0.2.7
 
 * Updates the execution handler to update final orders ensuring an execution order is created in the event of a single submission without a further rebalance.

Diff for: pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "qstrader"
-version = "0.2.7"
+version = "0.2.8"
 dependencies = [
     "click>=8.1",
     "matplotlib>=3.8",

Diff for: qstrader/trading/backtest.py

@@ -362,7 +362,7 @@ def get_target_allocations(self):
         alloc_df.index = alloc_df.index.date
         alloc_df = alloc_df.reindex(index=equity_curve.index, method='ffill')
         if self.burn_in_dt is not None:
-            alloc_df = alloc_df[self.burn_in_dt:]
+            alloc_df = alloc_df[self.burn_in_dt.date():]
         return alloc_df
 
     def run(self, results=False):

Diff for: tests/integration/trading/test_backtest_e2e.py

@@ -159,4 +159,39 @@ def test_backtest_buy_and_hold(etf_filepath, capsys):
 
     expected_execution_text = "(2015-11-09 14:30:00+00:00) - executed order:"
     captured = capsys.readouterr()
-    assert expected_execution_text in captured.out 
+    assert expected_execution_text in captured.out
+
+
+def test_backtest_target_allocations(etf_filepath,):
+    """
+    """
+    settings.print_events=True
+    os.environ['QSTRADER_CSV_DATA_DIR'] = etf_filepath
+
+    assets = ['EQ:ABC', 'EQ:DEF']
+    universe = StaticUniverse(assets)
+    signal_weights = {'EQ:ABC': 0.6, 'EQ:DEF': 0.4}
+    alpha_model = FixedSignalsAlphaModel(signal_weights)
+
+    start_dt = pd.Timestamp('2019-01-01 00:00:00', tz=pytz.UTC)
+    end_dt = pd.Timestamp('2019-01-31 23:59:00', tz=pytz.UTC)
+    burn_in_dt = pd.Timestamp('2019-01-07 14:30:00', tz=pytz.UTC)
+
+    backtest = BacktestTradingSession(
+        start_dt,
+        end_dt,
+        universe,
+        alpha_model,
+        portfolio_id='000001',
+        rebalance='weekly',
+        rebalance_weekday='WED',
+        long_only=True,
+        cash_buffer_percentage=0.05,
+        burn_in_dt = burn_in_dt
+    )
+    backtest.run(results=False)
+
+    target_allocations = backtest.get_target_allocations()
+    expected_ta = pd.DataFrame(data={'EQ:ABC': 0.6, 'EQ:DEF': 0.4}, index=pd.date_range("20190125", periods=5, freq='B'))
+    actual_ta = target_allocations.tail()
+    assert expected_ta.equals(actual_ta)