chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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 access to options history for a given underlying equity security.
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="options" />
+### <meta name="tag" content="filter selection" />
+### <meta name="tag" content="history" />
+class BasicTemplateOptionsHistoryAlgorithm(QCAlgorithm):
+    ''' This example demonstrates how to get access to options history for a given underlying equity security.'''
+
+    def initialize(self):
+        # this test opens position in the first day of trading, lives through stock split (7 for 1), and closes adjusted position on the second day
+        self.set_start_date(2015, 12, 24)
+        self.set_end_date(2015, 12, 24)
+        self.set_cash(1000000)
+
+        option = self.add_option("GOOG")
+        # add the initial contract filter 
+        # SetFilter method accepts timedelta objects or integer for days.
+        # The following statements yield the same filtering criteria
+        option.set_filter(-2, +2, 0, 180)
+        # option.set_filter(-2,2, timedelta(0), timedelta(180))
+
+        # set the pricing model for Greeks and volatility
+        # find more pricing models https://www.quantconnect.com/lean/documentation/topic27704.html
+        option.price_model = OptionPriceModels.black_scholes()
+        # set the warm-up period for the pricing model
+        self.set_warm_up(TimeSpan.from_days(4))
+        # set the benchmark to be the initial cash
+        self.set_benchmark(lambda x: 1000000)
+
+    def on_data(self,slice):
+        if self.is_warming_up: return
+        if not self.portfolio.invested:
+            for chain in slice.option_chains:
+                volatility = self.securities[chain.key.underlying].volatility_model.volatility
+                for contract in chain.value:
+                    self.log("{0},Bid={1} Ask={2} Last={3} OI={4} sigma={5:.3f} NPV={6:.3f} \
+                              delta={7:.3f} gamma={8:.3f} vega={9:.3f} beta={10:.2f} theta={11:.2f} IV={12:.2f}".format(
+                    contract.symbol.value,
+                    contract.bid_price,
+                    contract.ask_price,
+                    contract.last_price,
+                    contract.open_interest,
+                    volatility,
+                    contract.theoretical_price,
+                    contract.greeks.delta,
+                    contract.greeks.gamma,
+                    contract.greeks.vega,
+                    contract.greeks.rho,
+                    contract.greeks.theta / 365,
+                    contract.implied_volatility))
+
+    def on_securities_changed(self, changes):
+        for change in changes.added_securities:
+            # only print options price
+            if change.symbol.value == "GOOG": return
+            history = self.history(change.symbol, 10, Resolution.MINUTE).sort_index(level='time', ascending=False)[:3]
+            for index, row in history.iterrows():
+                self.log("History: " + str(index[3])
+                        + ": " + index[4].strftime("%m/%d/%Y %I:%M:%S %p")
+                        + " > " + str(row.close))