Colton Sellers
dd4da7ba95
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
* Create generic writing for LeanDataWriter, + notes on todos * Make Options Daily/Hourly data store by year * Refactor Generic Write * Permit hour and daily resolutions for options * Refactor writer to merge when needed with other files * Cleanup redundancies, run write tasks in parallel * Make needed classes/vars available * Update tests to reflect new naming convention for daily hourly options data * Add Byte[] overloads for ZipData functions in compression * Implemented Store() for ZipDataCacheProvider * Have LeanDataWriter use a DataCacheProvider * ZipDataCacheProvider cleanup * ZipDataCacheProvider tweaks, doesn't support storing non-zips * Test adjustments * Update LeanDataWriter to use Write instead of SaveDailyHourly/SaveMinuteSecond * Implement tests to verify DownloadAndSave behavior * Nit cleanup on DownloadAndSave tests * Fix for options daily/hourly underlying equity subscription read * Add daily/hourly options data and regressions * Add missing open interest for hourly * Fix writing of OpenInterest Daily/Hourly data * Update data * Fix Date typo in regression * Use daily algorithm to test delisting * Revisions part 1 * Expand test for DataCacheProviders; refactor DiskDataCacheProvider * nit - test adjustments * ZipDataCacheProvider test setup refactor * Adjust multithreaded read/write test; fixes for ZipDataCacheProvider * Move DiskDataCacheProvider to its own file and add write test * Remove _appendToZips; always overwrite entry or create zip * Add mapping regression for daily options * nit - add license to regression * Fix Tick write case where more than one data point for a DateTime * Fix data issue * Address review * Tweaks for tests * Stop Store() early if no entry name is given
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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UnderlyingTicker = "AAPL"
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def Initialize(self):
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self.SetStartDate(2014, 6, 6)
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self.SetEndDate(2014, 6, 9)
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self.SetCash(100000)
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equity = self.AddEquity(self.UnderlyingTicker, Resolution.Hour)
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option = self.AddOption(self.UnderlyingTicker, 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.SetFilter(lambda u: (u.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.FromDays(180))))
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# use the underlying equity as the benchmark
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self.SetBenchmark(equity.Symbol)
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def OnData(self,slice):
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if self.Portfolio.Invested or not self.IsMarketOpen(self.option_symbol): return
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chain = slice.OptionChains.GetValue(self.option_symbol)
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if chain is None:
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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: return
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symbol = contracts[0].Symbol
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self.MarketOrder(symbol, 1)
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self.MarketOnCloseOrder(symbol, -1)
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def OnOrderEvent(self, orderEvent):
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self.Log(str(orderEvent))
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