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 *
+
+class CompositeRiskManagementModel(RiskManagementModel):
+    '''Provides an implementation of IRiskManagementModel that combines multiple risk models
+    into a single risk management model and properly sets each insights 'SourceModel' property.'''
+
+    def __init__(self, *risk_management_models):
+        '''Initializes a new instance of the CompositeRiskManagementModel class
+        Args:
+            risk_management_models: The individual risk management models defining this composite model.'''
+        for model in risk_management_models:
+            for attribute_names in [('ManageRisk', 'manage_risk'), ('OnSecuritiesChanged', 'on_securities_changed')]:
+                if not hasattr(model, attribute_names[0]) and not hasattr(model, attribute_names[1]):
+                    raise Exception(f'IRiskManagementModel.{attribute_names[1]} must be implemented. Please implement this missing method on {model.__class__.__name__}')
+
+        self.risk_management_models = risk_management_models
+
+    def manage_risk(self, algorithm, targets):
+        '''Manages the algorithm's risk at each time step
+        Args:
+            algorithm: The algorithm instance
+            targets: The current portfolio targets to be assessed for risk'''
+        for model in self.risk_management_models:
+            # take into account the possibility of ManageRisk returning nothing
+            risk_adjusted = model.manage_risk(algorithm, targets)
+
+            # produce a distinct set of new targets giving preference to newer targets
+            symbols = [x.symbol for x in risk_adjusted]
+            for target in targets:
+                if target.symbol not in symbols:
+                    risk_adjusted.append(target)
+
+            targets = risk_adjusted
+
+        return targets
+
+    def on_securities_changed(self, algorithm, changes):
+        '''Event fired each time the we add/remove securities from the data feed.
+        This method patches this call through the each of the wrapped models.
+        Args:
+            algorithm: The algorithm instance that experienced the change in securities
+            changes: The security additions and removals from the algorithm'''
+        for model in self.risk_management_models:
+            model.on_securities_changed(algorithm, changes)
+
+    def add_risk_management(self, risk_management_model):
+        '''Adds a new 'IRiskManagementModel' instance
+        Args:
+            risk_management_model: The risk management model to add'''
+        self.risk_management_models.add(risk_management_model)