# 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 illustrating the usage of the <see cref="QCAlgorithm.OptionChains(IEnumerable{Symbol})"/> method### to get multiple future option chains.### </summary>class FutureOptionChainsMultipleFullDataRegressionAlgorithm(QCAlgorithm):def initialize(self):self.set_start_date(2020, 1, 6)self.set_end_date(2020, 1, 6)es_future_contract = self.add_future_contract(Symbol.create_future(Futures.Indices.SP_500_E_MINI, Market.CME, datetime(2020, 3, 20)),Resolution.MINUTE).symbolgc_future_contract = self.add_future_contract(Symbol.create_future(Futures.Metals.GOLD, Market.COMEX, datetime(2020, 4, 28)),Resolution.MINUTE).symbolchains = self.option_chains([es_future_contract, gc_future_contract], flatten=True)self._es_option_contract = self.get_contract(chains, es_future_contract)self._gc_option_contract = self.get_contract(chains, gc_future_contract)self.add_future_option_contract(self._es_option_contract)self.add_future_option_contract(self._gc_option_contract)def get_contract(self, chains: OptionChains, underlying: Symbol) -> Symbol:df = chains.data_frame# Index by the requested underlying, by getting all data with canonicals which underlying is the requested underlying symbol:canonicals = df.index.get_level_values('canonical')condition = [canonical for canonical in canonicals if canonical.underlying == underlying]contracts = df.loc[condition]# Get contracts expiring within 4 months, with the latest expiration date, highest strike and lowest pricecontracts = contracts.loc[(df.expiry <= self.time + timedelta(days=120))]contracts = contracts.sort_values(['expiry', 'strike', 'lastprice'], ascending=[False, False, True])return contracts.index[0][1]def on_data(self, data):# Do some trading with the selected contract for sample purposesif not self.portfolio.invested:self.set_holdings(self._es_option_contract, 0.25)self.set_holdings(self._gc_option_contract, 0.25)else:self.liquidate()
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