chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from AlgorithmImports import *
+from BaseFrameworkRegressionAlgorithm import BaseFrameworkRegressionAlgorithm
+from Risk.MaximumSectorExposureRiskManagementModel import MaximumSectorExposureRiskManagementModel
+
+### <summary>
+### Regression algorithm to assert the behavior of <see cref="MaximumSectorExposureRiskManagementModel"/>.
+### </summary>
+class MaximumSectorExposureRiskManagementModelFrameworkRegressionAlgorithm(BaseFrameworkRegressionAlgorithm):
+
+    def initialize(self):
+        super().initialize()
+        # Set requested data resolution
+        self.universe_settings.resolution = Resolution.DAILY
+
+        self.set_start_date(2014, 2, 1)  #Set Start Date
+        self.set_end_date(2014, 5, 1)    #Set End Date
+
+        # set algorithm framework models
+        tickers = [ "AAPL", "MSFT", "GOOG", "AIG", "BAC" ]
+        self.set_universe_selection(FineFundamentalUniverseSelectionModel(
+            lambda coarse: [ x.symbol for x in coarse if x.symbol.value in tickers ],
+            lambda fine: [ x.symbol for x in fine ]
+        ))
+
+        # define risk management model such that maximum weight of a single sector be 10%
+        # Number of of trades changed from 34 to 30 when using the MaximumSectorExposureRiskManagementModel
+        self.set_risk_management(MaximumSectorExposureRiskManagementModel(0.1))
+
+    def on_end_of_algorithm(self):
+        pass