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 MaximumDrawdownPercentPerSecurity(RiskManagementModel):
+    '''Provides an implementation of IRiskManagementModel that limits the drawdown per holding to the specified percentage'''
+
+    def __init__(self, maximum_drawdown_percent = 0.05):
+        '''Initializes a new instance of the MaximumDrawdownPercentPerSecurity class
+        Args:
+            maximum_drawdown_percent: The maximum percentage drawdown allowed for any single security holding'''
+        self.maximum_drawdown_percent = -abs(maximum_drawdown_percent)
+
+    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'''
+        targets = []
+        for kvp in algorithm.securities:
+            security = kvp.value
+
+            if not security.invested:
+                continue
+
+            pnl = security.holdings.unrealized_profit_percent
+            if pnl < self.maximum_drawdown_percent:
+                symbol = security.symbol
+
+                # Cancel insights
+                algorithm.insights.cancel([symbol])
+
+                # liquidate
+                targets.append(PortfolioTarget(symbol, 0))
+
+        return targets