Jared Broad
76 lines
3.4 KiB
Python
76 lines
3.4 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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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 QuantConnect.Data.Market import TradeBar
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### <summary>
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### Using rolling windows for efficient storage of historical data; which automatically clears after a period of time.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="history and warm up" />
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### <meta name="tag" content="history" />
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### <meta name="tag" content="warm up" />
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### <meta name="tag" content="indicators" />
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### <meta name="tag" content="rolling windows" />
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class RollingWindowAlgorithm(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(2013,10,1) #Set Start Date
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self.SetEndDate(2013,11,1) #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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# Creates a Rolling Window indicator to keep the 2 TradeBar
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self.window = RollingWindow[TradeBar](2) # For other security types, use QuoteBar
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# Creates an indicator and adds to a rolling window when it is updated
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self.SMA("SPY", 5).Updated += self.SmaUpdated
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self.smaWin = RollingWindow[IndicatorDataPoint](5)
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def SmaUpdated(self, sender, updated):
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'''Adds updated values to rolling window'''
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self.smaWin.Add(updated)
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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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# Add SPY TradeBar in rollling window
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self.window.Add(data["SPY"])
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# Wait for windows to be ready.
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if not (self.window.IsReady and self.smaWin.IsReady): return
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currBar = self.window[0] # Current bar had index zero.
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pastBar = self.window[1] # Past bar has index one.
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self.Log("Price: {0} -> {1} ... {2} -> {3}".format(pastBar.Time, pastBar.Close, currBar.Time, currBar.Close))
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currSma = self.smaWin[0] # Current SMA had index zero.
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pastSma = self.smaWin[self.smaWin.Count-1] # Oldest SMA has index of window count minus 1.
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self.Log("SMA: {0} -> {1} ... {2} -> {3}".format(pastSma.Time, pastSma.Value, currSma.Time, currSma.Value))
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if not self.Portfolio.Invested and currSma.Value > pastSma.Value:
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self.SetHoldings("SPY", 1) |