add CustomDataIndicatorExtensions Algorithm

2018-03-15 17:11:55 -04:00
parent 42d38f7b51
commit 75c5902f89
5 changed files with 187 additions and 1 deletions
@@ -0,0 +1,84 @@
+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from clr import AddReference
+AddReference("System")
+AddReference("QuantConnect.Algorithm")
+AddReference("QuantConnect.Common")
+AddReference("QuantConnect.Indicators")
+
+
+from System import *
+from QuantConnect import *
+from QuantConnect.Indicators import *
+from QuantConnect.Data import *
+from QuantConnect.Data.Market import *
+from QuantConnect.Data.Custom import *
+from QuantConnect.Algorithm import *
+from QuantConnect.Python import PythonQuandl
+
+### <summary>
+### The algorithm creates new indicator value with the existing indicator method by Indicator Extensions
+### Demonstration of using the external custom datasource Quandl to request the VIX and VXV daily data
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="using quantconnect" />
+### <meta name="tag" content="custom data" />
+### <meta name="tag" content="indicators" />
+### <meta name="tag" content="indicator classes" />
+### <meta name="tag" content="plotting indicators" />
+### <meta name="tag" content="charting" />
+class CustomDataIndicatorExtensionsAlgorithm(QCAlgorithm):
+
+    # Initialize the data and resolution you require for your strategy
+    def Initialize(self):
+
+        self.SetStartDate(2014,1,1) 
+        self.SetEndDate(2018,1,1)  
+        self.SetCash(25000)
+        
+        vix = 'CBOE/VIX'
+        vxv = 'CBOE/VXV'
+        
+        # Define the symbol and "type" of our generic data
+        self.AddData(QuandlVix, vix, Resolution.Daily)
+        self.AddData[Quandl](vxv, Resolution.Daily)
+        
+        # Set up default Indicators, these are just 'identities' of the closing price
+        self.vix_sma = self.SMA(vix, 1, Resolution.Daily)
+        self.vxv_sma = self.SMA(vxv, 1, Resolution.Daily)
+        
+        # This will create a new indicator whose value is smaVXV / smaVIX
+        self.ratio = IndicatorExtensions.Over(self.vxv_sma, self.vix_sma)
+        
+        # Plot our indicators each time they update using th PlotIndicator function
+        self.PlotIndicator("Ratio", self.ratio)
+        self.PlotIndicator("Data", self.vix_sma, self.vxv_sma)
+    
+    # OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+    def OnData(self, data):
+        
+        # Wait for all indicators to fully initialize
+        if not (self.vix_sma.IsReady and self.vxv_sma.IsReady and self.ratio.IsReady): return
+        if not self.Portfolio.Invested and self.ratio.Current.Value > 1:
+            self.MarketOrder('CBOE/VIX', 100)
+        elif self.ratio.Current.Value < 1:
+                self.Liquidate()
+
+# In CBOE/VIX data, there is a "vix close" column instead of "close" which is the 
+# default column namein LEAN Quandl custom data implementation.
+# This class assigns new column name to match the the external datasource setting.
+class QuandlVix(PythonQuandl):
+    
+    def __init__(self):
+        self.ValueColumnName = "VIX Close"