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>
+### The demonstration algorithm shows some of the most common order methods when working with FutureOption assets.
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="using quantconnect" />
+### <meta name="tag" content="trading and orders" />
+
+class BasicTemplateFutureOptionAlgorithm(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(2022, 1, 1)
+        self.set_end_date(2022, 2, 1)
+        self.set_cash(100000)
+
+        gold_futures = self.add_future(Futures.Metals.GOLD, Resolution.MINUTE)
+        gold_futures.set_filter(0, 180)
+        self._symbol = gold_futures.symbol
+        self.add_future_option(self._symbol, lambda universe: universe.strikes(-5, +5)
+                                                                    .calls_only()
+                                                                    .back_month()
+                                                                    .only_apply_filter_at_market_open())
+
+        # Historical Data
+        history = self.history(self._symbol, 60, Resolution.DAILY)
+        self.log(f"Received {len(history)} bars from {self._symbol} FutureOption historical data call.")
+
+    def on_data(self, data):
+        '''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        Arguments:
+            slice: Slice object keyed by symbol containing the stock data
+        '''
+        # Access Data
+        for kvp in data.option_chains:
+            underlying_future_contract = kvp.key.underlying
+            chain = kvp.value
+
+            if not chain: continue
+
+            for contract in chain:
+                self.log(f"""Canonical Symbol: {kvp.key}; 
+                    Contract: {contract}; 
+                    Right: {contract.right}; 
+                    Expiry: {contract.expiry}; 
+                    Bid price: {contract.bid_price}; 
+                    Ask price: {contract.ask_price}; 
+                    Implied Volatility: {contract.implied_volatility}""")
+
+            if not self.portfolio.invested:
+                atm_strike = sorted(chain, key = lambda x: abs(chain.underlying.price - x.strike))[0].strike
+                selected_contract = sorted([contract for contract in chain if contract.strike == atm_strike], \
+                           key = lambda x: x.expiry, reverse=True)[0]
+                self.market_order(selected_contract.symbol, 1)
+
+    def on_order_event(self, order_event):
+        self.debug("{} {}".format(self.time, order_event.to_string()))