Martin-Molinero
03f56481d4
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Python research import improvements - Improve start.py for research env - Remove unrequired imports * Centralize algorithm imports * Add regression test GH action * Unit test python import clean up * Join research and main imports * More python import clean up * Fix failing skipped regression algorithm
66 lines
2.8 KiB
Python
66 lines
2.8 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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### <summary>
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### Simple indicator demonstration algorithm of MACD
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### </summary>
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### <meta name="tag" content="indicators" />
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### <meta name="tag" content="indicator classes" />
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### <meta name="tag" content="plotting indicators" />
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class MACDTrendAlgorithm(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(2004, 1, 1) #Set Start Date
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self.SetEndDate(2015, 1, 1) #Set End Date
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self.SetCash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.AddEquity("SPY", Resolution.Daily)
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# define our daily macd(12,26) with a 9 day signal
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self.__macd = self.MACD("SPY", 12, 26, 9, MovingAverageType.Exponential, Resolution.Daily)
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self.__previous = datetime.min
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self.PlotIndicator("MACD", True, self.__macd, self.__macd.Signal)
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self.PlotIndicator("SPY", self.__macd.Fast, self.__macd.Slow)
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def OnData(self, data):
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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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# wait for our macd to fully initialize
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if not self.__macd.IsReady: return
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# only once per day
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if self.__previous.date() == self.Time.date(): return
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# define a small tolerance on our checks to avoid bouncing
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tolerance = 0.0025
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holdings = self.Portfolio["SPY"].Quantity
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signalDeltaPercent = (self.__macd.Current.Value - self.__macd.Signal.Current.Value)/self.__macd.Fast.Current.Value
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# if our macd is greater than our signal, then let's go long
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if holdings <= 0 and signalDeltaPercent > tolerance: # 0.01%
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# longterm says buy as well
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self.SetHoldings("SPY", 1.0)
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# of our macd is less than our signal, then let's go short
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elif holdings >= 0 and signalDeltaPercent < -tolerance:
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self.Liquidate("SPY")
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self.__previous = self.Time
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