Martin-Molinero
102 lines
4.1 KiB
Python
102 lines
4.1 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 clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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AddReference("QuantConnect.Indicators")
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from System import *
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from QuantConnect import *
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from QuantConnect.Data.Market import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Indicators import *
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from QuantConnect.Securities import *
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### <summary>
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### This example demonstrates how to implement a cross moving average for the futures front contract
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="indicator" />
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### <meta name="tag" content="futures" />
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class EmaCrossFuturesFrontMonthAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2013, 10, 8)
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self.SetEndDate(2013, 10, 10)
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self.SetCash(1000000)
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future = self.AddFuture(Futures.Metals.Gold);
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# Only consider the front month contract
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# Update the universe once per day to improve performance
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future.SetFilter(lambda x: x.FrontMonth().OnlyApplyFilterAtMarketOpen())
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# Symbol of the current contract
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self.symbol = None
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# Create two exponential moving averages
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self.fast = ExponentialMovingAverage(100)
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self.slow = ExponentialMovingAverage(300)
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self.tolerance = 0.001
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self.consolidator = None
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# Add a custom chart to track the EMA cross
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chart = Chart('EMA Cross')
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chart.AddSeries(Series('Fast', SeriesType.Line, 0))
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chart.AddSeries(Series('Slow', SeriesType.Line, 0))
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self.AddChart(chart)
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def OnData(self,slice):
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holding = None if self.symbol is None else self.Portfolio.get(self.symbol)
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if holding is not None:
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# Buy the futures' front contract when the fast EMA is above the slow one
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if self.fast.Current.Value > self.slow.Current.Value * (1 + self.tolerance):
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if not holding.Invested:
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self.SetHoldings(self.symbol, .1)
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self.PlotEma()
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elif holding.Invested:
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self.Liquidate(self.symbol)
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self.PlotEma()
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def OnSecuritiesChanged(self, changes):
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if len(changes.RemovedSecurities) > 0:
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# Remove the consolidator for the previous contract
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# and reset the indicators
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if self.symbol is not None and self.consolidator is not None:
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self.SubscriptionManager.RemoveConsolidator(self.symbol, self.consolidator)
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self.fast.Reset()
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self.slow.Reset()
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# We don't need to call Liquidate(_symbol),
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# since its positions are liquidated because the contract has expired.
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# Only one security will be added: the new front contract
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self.symbol = changes.AddedSecurities[0].Symbol
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# Create a new consolidator and register the indicators to it
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self.consolidator = self.ResolveConsolidator(self.symbol, Resolution.Minute)
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self.RegisterIndicator(self.symbol, self.fast, self.consolidator)
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self.RegisterIndicator(self.symbol, self.slow, self.consolidator)
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# Warm up the indicators
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self.WarmUpIndicator(self.symbol, self.fast, Resolution.Minute)
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self.WarmUpIndicator(self.symbol, self.slow, Resolution.Minute)
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self.PlotEma()
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def PlotEma(self):
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self.Plot('EMA Cross', 'Fast', self.fast.Current.Value)
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self.Plot('EMA Cross', 'Slow', self.slow.Current.Value)
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