wehub-resource-sync
67 lines
2.9 KiB
Python
67 lines
2.9 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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### This example demonstrates how to add options for a given underlying equity security.
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### It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
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### can inspect the option chain to pick a specific option contract to trade.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="options" />
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### <meta name="tag" content="filter selection" />
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class BasicTemplateOptionsHourlyAlgorithm(QCAlgorithm):
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underlying_ticker = "AAPL"
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def initialize(self):
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self.set_start_date(2014, 6, 6)
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self.set_end_date(2014, 6, 9)
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self.set_cash(100000)
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equity = self.add_equity(self.underlying_ticker, Resolution.HOUR)
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option = self.add_option(self.underlying_ticker, Resolution.HOUR)
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self.option_symbol = option.symbol
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# set our strike/expiry filter for this option chain
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option.set_filter(lambda u: (u.standards_only().strikes(-2, +2)
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# Expiration method accepts TimeSpan objects or integer for days.
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# The following statements yield the same filtering criteria
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.expiration(0, 180)))
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#.expiration(TimeSpan.zero, TimeSpan.from_days(180))))
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# use the underlying equity as the benchmark
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self.set_benchmark(equity.symbol)
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def on_data(self,slice):
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if self.portfolio.invested or not self.is_market_open(self.option_symbol): return
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chain = slice.option_chains.get(self.option_symbol)
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if not chain:
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return
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# we sort the contracts to find at the money (ATM) contract with farthest expiration
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contracts = sorted(sorted(sorted(chain, \
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key = lambda x: abs(chain.underlying.price - x.strike)), \
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key = lambda x: x.expiry, reverse=True), \
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key = lambda x: x.right, reverse=True)
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# if found, trade it
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if len(contracts) == 0 or not self.is_market_open(contracts[0].symbol): return
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symbol = contracts[0].symbol
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self.market_order(symbol, 1)
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self.market_on_close_order(symbol, -1)
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def on_order_event(self, order_event):
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self.log(str(order_event))
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