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>
+### This example demonstrates how to use the OptionUniverseSelectionModel to select options contracts based on specified conditions.
+### The model is updated daily and selects different options based on the current date.
+### The algorithm ensures that only valid option contracts are selected for the universe.
+### </summary>
+class AddOptionUniverseSelectionModelRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2014, 6, 5)
+        self.set_end_date(2014, 6, 6)
+        self.option_count = 0
+        
+        self.universe_settings.resolution = Resolution.MINUTE
+        self.set_universe_selection(OptionUniverseSelectionModel(
+            timedelta(days=1),
+            self.select_option_chain_symbols
+        ))
+    
+    def select_option_chain_symbols(self, utc_time):
+        new_york_time = Extensions.convert_from_utc(utc_time, TimeZones.NEW_YORK)
+        if new_york_time.date() < datetime(2014, 6, 6).date():
+            return [ Symbol.create("TWX", SecurityType.OPTION, Market.USA) ]
+        
+        if new_york_time.date() >= datetime(2014, 6, 6).date():
+            return [ Symbol.create("AAPL", SecurityType.OPTION, Market.USA) ]
+
+    def on_securities_changed(self, changes):
+        if len(changes.added_securities) > 0:
+            for security in changes.added_securities:
+                symbol = security.symbol.underlying if security.symbol.underlying else security.Symbol
+                if symbol.value != "AAPL" and symbol.value != "TWX":
+                    raise RegressionTestException(f"Unexpected security {security.Symbol}")
+                
+                if security.symbol.security_type == SecurityType.OPTION:
+                    self.option_count += 1
+
+    def on_end_of_algorithm(self):
+        if len(self.active_securities) == 0:
+            raise RegressionTestException("No active securities found. Expected at least one active security")
+        if self.option_count == 0:
+            raise RegressionTestException("The option count should be greater than 0")