15066ae5e1
* add data count properties * 'add history count property * assert data counts * update missing override * consider override/virtual cases * implement data count * add message handler for regression tests * use regression test message handler * set algorithm manager for regression test message handler * update data count * check if stats are present, check if algo manager is not null * update * add c# algo * make same as c# algo * use new line * logic shifted to RegressionTestMessageHandler * cleanup * auto cleanup * skip non deterministic data count * change data count * use inheritance * improve stats * update couht * add sma indicator to c# and customSMA to python * call base method before executing further * skip test * revert to original * add duplicate sma * skip regression test
65 lines
2.7 KiB
Python
65 lines
2.7 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 regression algorithm checks if all the option chain data coming to the algo is consistent with current securities manager state
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### </summary>
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### <meta name="tag" content="regression test" />
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### <meta name="tag" content="options" />
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="filter selection" />
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class OptionChainConsistencyRegressionAlgorithm(QCAlgorithm):
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UnderlyingTicker = "GOOG"
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def Initialize(self):
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self.SetCash(10000)
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self.SetStartDate(2015,12,24)
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self.SetEndDate(2015,12,24)
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self.equity = self.AddEquity(self.UnderlyingTicker);
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self.option = self.AddOption(self.UnderlyingTicker);
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# set our strike/expiry filter for this option chain
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self.option.SetFilter(self.UniverseFunc)
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self.SetBenchmark(self.equity.Symbol)
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def OnData(self, slice):
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if self.Portfolio.Invested: return
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for kvp in slice.OptionChains:
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chain = kvp.Value
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for o in chain:
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if not self.Securities.ContainsKey(o.Symbol):
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self.Log("Inconsistency found: option chains contains contract {0} that is not available in securities manager and not available for trading".format(o.Symbol.Value))
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contracts = filter(lambda x: x.Expiry.date() == self.Time.date() and
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x.Strike < chain.Underlying.Price and
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x.Right == OptionRight.Call, chain)
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sorted_contracts = sorted(contracts, key = lambda x: x.Strike, reverse = True)
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if len(sorted_contracts) > 2:
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self.MarketOrder(sorted_contracts[2].Symbol, 1)
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self.MarketOnCloseOrder(sorted_contracts[2].Symbol, -1)
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# set our strike/expiry filter for this option chain
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def UniverseFunc(self, universe):
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return universe.IncludeWeeklys().Strikes(-2, 2).Expiration(timedelta(0), timedelta(10))
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def OnOrderEvent(self, orderEvent):
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self.Log(str(orderEvent))
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