Colton Sellers
d2d99b1f10
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Implement scheduled event sampling solution * Use UTC time, only update daily portfolio value once a day * For daily resolutions sample chart always * Cleanup * Drop resample daily all together * Force final sample * Regression updates * FIx LiveResultHandler to update portfolio and benchmark values outside of sampling event * Name the daily sampling event * Address review pt 1 * Drop force and use reference wrapper * Adjust tests * Fix warning for Benchmark Timezone Misalignment and also add test * Fix for daily resolution orders and test adjustments * Also warn on universe settings with daily resolution * Update missed regression * Fix reference wrapper use * Update regression after rebase * Add values back in for Daylight Algo * Have statistics builder skip day 1 performance * Regression adjustments * Test adjustments * Update regression unit test * Adjust some regressions starts to show performance values * Add hourly algorithm for beta comparison * Address missing Python regression changes * Remove null comment
90 lines
3.6 KiB
Python
90 lines
3.6 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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### Demonstration of how to chain a coarse and fine universe selection with an option chain universe selection model
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### that will add and remove an'OptionChainUniverse' for each symbol selected on fine
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### </summary>
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class CoarseFineOptionUniverseChainRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.SetStartDate(2014,6,4) #Set Start Date
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self.SetEndDate(2014,6,6) #Set End Date
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self.UniverseSettings.Resolution = Resolution.Minute
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self._twx = Symbol.Create("TWX", SecurityType.Equity, Market.USA)
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self._aapl = Symbol.Create("AAPL", SecurityType.Equity, Market.USA)
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self._lastEquityAdded = None
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self._changes = None
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self._optionCount = 0
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universe = self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
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self.AddUniverseOptions(universe, self.OptionFilterFunction)
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def OptionFilterFunction(self, universe):
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universe.IncludeWeeklys().FrontMonth()
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contracts = list()
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for symbol in universe:
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if len(contracts) == 5:
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break
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contracts.append(symbol)
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return universe.Contracts(contracts)
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def CoarseSelectionFunction(self, coarse):
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if self.Time <= datetime(2014,6,5):
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return [ self._twx ]
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return [ self._aapl ]
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def FineSelectionFunction(self, fine):
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if self.Time <= datetime(2014,6,5):
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return [ self._twx ]
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return [ self._aapl ]
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def OnData(self, data):
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if self._changes == None or any(security.Price == 0 for security in self._changes.AddedSecurities):
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return
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# liquidate removed securities
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for security in self._changes.RemovedSecurities:
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if security.Invested:
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self.Liquidate(security.Symbol)
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for security in self._changes.AddedSecurities:
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if not security.Symbol.HasUnderlying:
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self._lastEquityAdded = security.Symbol
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else:
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# options added should all match prev added security
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if security.Symbol.Underlying != self._lastEquityAdded:
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raise ValueError(f"Unexpected symbol added {security.Symbol}")
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self._optionCount += 1
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self.SetHoldings(security.Symbol, 0.05)
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self._changes = None
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# this event fires whenever we have changes to our universe
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def OnSecuritiesChanged(self, changes):
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if self._changes == None:
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self._changes = changes
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return
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self._changes = self._changes.op_Addition(self._changes, changes)
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def OnEndOfAlgorithm(self):
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if self._optionCount == 0:
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raise ValueError("Option universe chain did not add any option!")
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