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 *
+
+### <summary>
+### Regression algorithm testing GH feature 3790, using SetHoldings with a collection of targets
+### which will be ordered by margin impact before being executed, with the objective of avoiding any
+### margin errors
+### </summary>
+class SetHoldingsMultipleTargetsRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+
+        self.set_start_date(2013,10, 7)
+        self.set_end_date(2013,10,11)
+
+        # use leverage 1 so we test the margin impact ordering
+        self._spy = self.add_equity("SPY", Resolution.MINUTE, Market.USA, False, 1).symbol
+        self._ibm = self.add_equity("IBM", Resolution.MINUTE, Market.USA, False, 1).symbol
+
+        # Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
+        # Commented so regression algorithm is more sensitive
+        #self.settings.minimum_order_margin_portfolio_percentage = 0.005
+
+    def on_data(self, data):
+        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+
+        Arguments:
+            data: Slice object keyed by symbol containing the stock data
+        '''
+        if not self.portfolio.invested:
+            self.set_holdings([PortfolioTarget(self._spy, 0.8), PortfolioTarget(self._ibm, 0.2)])
+        else:
+            self.set_holdings([PortfolioTarget(self._ibm, 0.8), PortfolioTarget(self._spy, 0.2)])