wehub-resource-sync
50 lines
2.1 KiB
Python
50 lines
2.1 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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### <summary>
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### Regression algorithm illustrating the usage of the <see cref="QCAlgorithm.FuturesChain(Symbol, bool)"/>
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### method to get a future chain.
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### </summary>
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class FuturesChainFullDataRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2013, 10, 7)
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self.set_end_date(2013, 10, 7)
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future = self.add_future(Futures.Indices.SP_500_E_MINI, Resolution.MINUTE).symbol
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chain = self.futures_chain(future, flatten=True)
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# Demonstration using data frame:
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df = chain.data_frame
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for index, row in df.iterrows():
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if row['bidprice'] == 0 and row['askprice'] == 0 and row['volume'] == 0:
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raise AssertionError("FuturesChain() returned contract with no data.");
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# Get contracts expiring within 6 months, with the latest expiration date, and lowest price
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contracts = df.loc[(df.expiry <= self.time + timedelta(days=180))]
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contracts = contracts.sort_values(['expiry', 'lastprice'], ascending=[False, True])
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self._future_contract = contracts.index[0]
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self.add_future_contract(self._future_contract)
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def on_data(self, data):
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# Do some trading with the selected contract for sample purposes
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if not self.portfolio.invested:
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self.set_holdings(self._future_contract, 0.5)
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else:
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self.liquidate()
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