Jhonathan Abreu
2791765c94
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120 lines
5.8 KiB
Python
120 lines
5.8 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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from CustomDataRegressionAlgorithm import Bitcoin
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### <summary>
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### Regression algorithm reproducing data type bugs in the Consolidate API. Related to GH 4205.
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### </summary>
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class ConsolidateRegressionAlgorithm(QCAlgorithm):
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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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def Initialize(self):
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self.SetStartDate(2013, 10, 8)
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self.SetEndDate(2013, 10, 20)
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SP500 = Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME)
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self._symbol = _symbol = self.FutureChainProvider.GetFutureContractList(SP500, self.StartDate)[0]
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self.AddFutureContract(_symbol)
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self._consolidationCounts = [0] * 6
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self._smas = [SimpleMovingAverage(10) for x in self._consolidationCounts]
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self._lastSmaUpdates = [datetime.min for x in self._consolidationCounts]
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self._monthlyConsolidatorSma = SimpleMovingAverage(10)
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self._monthlyConsolidationCount = 0
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self._weeklyConsolidatorSma = SimpleMovingAverage(10)
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self._weeklyConsolidationCount = 0
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self._lastWeeklySmaUpdate = datetime.min
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self.Consolidate(_symbol, Calendar.Monthly, lambda bar: self.UpdateMonthlyConsolidator(bar, -1)) # shouldn't consolidate
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self.Consolidate(_symbol, Calendar.Weekly, TickType.Trade, lambda bar: self.UpdateWeeklyConsolidator(bar))
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self.Consolidate(_symbol, Resolution.Daily, lambda bar: self.UpdateTradeBar(bar, 0))
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self.Consolidate(_symbol, Resolution.Daily, TickType.Quote, lambda bar: self.UpdateQuoteBar(bar, 1))
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self.Consolidate(_symbol, timedelta(1), lambda bar: self.UpdateTradeBar(bar, 2))
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self.Consolidate(_symbol, timedelta(1), TickType.Quote, lambda bar: self.UpdateQuoteBar(bar, 3))
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# sending None tick type
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self.Consolidate(_symbol, timedelta(1), None, lambda bar: self.UpdateTradeBar(bar, 4))
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self.Consolidate(_symbol, Resolution.Daily, None, lambda bar: self.UpdateTradeBar(bar, 5))
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# custom data
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self._customDataConsolidator = 0
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customSymbol = self.AddData(Bitcoin, "BTC", Resolution.Minute).Symbol
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self.Consolidate(customSymbol, timedelta(1), lambda bar: self.IncrementCounter(1))
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self._customDataConsolidator2 = 0
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self.Consolidate(customSymbol, Resolution.Daily, lambda bar: self.IncrementCounter(2))
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def IncrementCounter(self, id):
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if id == 1:
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self._customDataConsolidator += 1
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if id == 2:
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self._customDataConsolidator2 += 1
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def UpdateTradeBar(self, bar, position):
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self._smas[position].Update(bar.EndTime, bar.Volume)
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self._lastSmaUpdates[position] = bar.EndTime
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self._consolidationCounts[position] += 1
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def UpdateQuoteBar(self, bar, position):
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self._smas[position].Update(bar.EndTime, bar.Ask.High)
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self._lastSmaUpdates[position] = bar.EndTime
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self._consolidationCounts[position] += 1
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def UpdateMonthlyConsolidator(self, bar):
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self._monthlyConsolidatorSma.Update(bar.EndTime, bar.Volume)
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self._monthlyConsolidationCount += 1
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def UpdateWeeklyConsolidator(self, bar):
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self._weeklyConsolidatorSma.Update(bar.EndTime, bar.Volume)
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self._lastWeeklySmaUpdate = bar.EndTime
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self._weeklyConsolidationCount += 1
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def OnEndOfAlgorithm(self):
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expectedConsolidations = 8
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expectedWeeklyConsolidations = 1
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if (any(i != expectedConsolidations for i in self._consolidationCounts) or
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self._weeklyConsolidationCount != expectedWeeklyConsolidations or
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self._customDataConsolidator == 0 or
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self._customDataConsolidator2 == 0):
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raise ValueError("Unexpected consolidation count")
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for i, sma in enumerate(self._smas):
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if sma.Samples != expectedConsolidations:
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raise Exception(f"Expected {expectedConsolidations} samples in each SMA but found {sma.Samples} in SMA in index {i}")
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lastUpdate = self._lastSmaUpdates[i]
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if sma.Current.Time != lastUpdate:
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raise Exception(f"Expected SMA in index {i} to have been last updated at {lastUpdate} but was {sma.Current.Time}")
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if self._monthlyConsolidationCount != 0 or self._monthlyConsolidatorSma.Samples != 0:
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raise Exception("Expected monthly consolidator to not have consolidated any data")
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if self._weeklyConsolidatorSma.Samples != expectedWeeklyConsolidations:
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raise Exception(f"Expected {expectedWeeklyConsolidations} samples in the weekly consolidator SMA but found {self._weeklyConsolidatorSma.Samples}")
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if self._weeklyConsolidatorSma.Current.Time != self._lastWeeklySmaUpdate:
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raise Exception(f"Expected weekly consolidator SMA to have been last updated at {self._lastWeeklySmaUpdate} but was {self._weeklyConsolidatorSma.Current.Time}")
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# OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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def OnData(self, data):
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if not self.Portfolio.Invested:
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self.SetHoldings(self._symbol, 0.5)
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