DataNormalizationMode Applies to AddSecurity (#5528)

* Use UniverseSettings.DataNormalizationMode for securities added in Algorithm * Stop SubscriptionUtils from forcing Adjusted mode * Return behavior to original and add comments * nit typo * Add regression * Add unit test that verifies DataNormalizationMode can be altered manually by security * Cleanup and add Py version of regression
2021-05-10 16:58:50 -07:00
parent 1958ac2935
commit ed077da501
5 changed files with 263 additions and 3 deletions
@@ -0,0 +1,67 @@
+# 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.Core")
+AddReference("QuantConnect.Common")
+AddReference("QuantConnect.Algorithm")
+
+from System import *
+from QuantConnect import *
+from QuantConnect.Algorithm import QCAlgorithm
+from QuantConnect.Data.Auxiliary import FactorFile
+from QuantConnect.Data.UniverseSelection import *
+from QuantConnect.Orders import OrderStatus
+from QuantConnect.Orders.Fees import ConstantFeeModel
+
+_ticker = "GOOGL";
+_factorFile = FactorFile.Read(_ticker, "USA");
+_expectedRawPrices = [ 1158.1100, 1158.7200,
+1131.7800, 1114.2800, 1119.6100, 1114.5500, 1135.3200, 567.59000, 571.4900, 545.3000, 540.6400 ]
+
+# <summary>
+# In this algorithm we demonstrate how to use the raw data for our securities
+# and verify that the behavior is correct.
+# </summary>
+# <meta name="tag" content="using data" />
+# <meta name="tag" content="regression test" />
+class RawDataRegressionAlgorithm(QCAlgorithm):
+
+        def Initialize(self):
+            self.SetStartDate(2014, 3, 25);    
+            self.SetEndDate(2014, 4, 7);         
+            self.SetCash(100000);                            
+
+            # Set our DataNormalizationMode to raw
+            self.UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
+            self._googl = self.AddEquity(_ticker, Resolution.Daily).Symbol;
+        
+
+        def OnData(self, data):
+            if not self.Portfolio.Invested:
+                self.SetHoldings(self._googl, 1);
+
+            if (data.Bars.ContainsKey(self._googl)):
+                googlData = data.Bars[self._googl];
+
+                # Assert our volume matches what we expected
+                if _expectedRawPrices.pop(0) != googlData.Close:
+                    # Our values don't match lets try and give a reason why
+                    dayFactor = _factorFile.GetPriceScaleFactor(googlData.Time);
+                    probableRawPrice = googlData.Close / dayFactor; # Undo adjustment
+
+                    if _expectedRawPrices.Current == probableRawPrice:
+                        raise Exception("Close price was incorrect; it appears to be the adjusted value")
+                    else:
+                        raise Exception("Close price was incorrect; Data may have changed.")
+