AlexCatarino
77d1b537ee
Adds overloads to Plot and PlotIndicator to handle calls from python. Adds CustomChartingAlgorithm and changes MACDTrendAlgorithm to showcase the feature
71 lines
3.0 KiB
Python
71 lines
3.0 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.Indicators")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Indicators import *
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from datetime import datetime
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class MACDTrendAlgorithm(QCAlgorithm):
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'''MACD Example Algorithm'''
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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, 01, 01) #Set Start Date
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self.SetEndDate(2015, 01, 01) #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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equity = self.AddEquity("SPY", Resolution.Daily)
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self.spy = equity.Symbol
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# define our daily macd(12,26) with a 9 day signal
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self.__macd = self.MACD(self.spy, 9, 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(str(self.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[self.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(self.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(self.spy)
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self.__previous = self.Time |