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>
+### Example demonstrating how to define an option price model.
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="options" />
+### <meta name="tag" content="filter selection" />
+### <meta name="tag" content="option price model" />
+class BasicTemplateOptionsPriceModel(QCAlgorithm):
+    '''Example demonstrating how to define an option price model.'''
+
+    def initialize(self):
+        self.set_start_date(2020, 1, 1)
+        self.set_end_date(2020, 1, 5)
+        self.set_cash(100000)
+
+        # Add the option
+        option = self.add_option("AAPL")
+        self.option_symbol = option.symbol
+
+        # Add the initial contract filter
+        option.set_filter(-3, +3, 0, 31)
+
+        # Define the Option Price Model
+        option.price_model = OptionPriceModels.QuantLib.crank_nicolson_fd()
+        #option.price_model = OptionPriceModels.QuantLib.black_scholes()
+        #option.price_model = OptionPriceModels.QuantLib.additive_equiprobabilities()
+        #option.price_model = OptionPriceModels.QuantLib.barone_adesi_whaley()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_cox_ross_rubinstein()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_jarrow_rudd()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_joshi()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_leisen_reimer()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_tian()
+        #option.price_model = OptionPriceModels.QuantLib.binomial_trigeorgis()
+        #option.price_model = OptionPriceModels.QuantLib.bjerksund_stensland()
+        #option.price_model = OptionPriceModels.QuantLib.integral()
+
+        # Set warm up with 30 trading days to warm up the underlying volatility model
+        self.set_warm_up(30, Resolution.DAILY)
+
+
+    def on_data(self,slice):
+        '''OnData will test whether the option contracts has a non-zero Greeks.delta'''
+
+        if self.is_warming_up or not slice.option_chains.contains_key(self.option_symbol):
+            return
+
+        chain = slice.option_chains[self.option_symbol]
+        if not any([x for x in chain if x.greeks.delta != 0]):
+            self.log(f'No contract with Delta != 0')