# 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") from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Algorithm.Framework.Selection import * from QuantConnect.Data import * from QuantConnect.Data.Custom.SEC import * from QuantConnect.Data.UniverseSelection import * class CustomDataAddDataCoarseSelectionRegressionAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2013, 10, 7) self.SetEndDate(2013, 10, 11) self.SetCash(100000) self.UniverseSettings.Resolution = Resolution.Daily self.AddUniverseSelection(CoarseFundamentalUniverseSelectionModel(self.CoarseSelector)) def CoarseSelector(self, coarse): symbols = [i.Symbol for i in coarse if i.HasFundamentalData and i.DollarVolume > 500000000] self.customSymbols = [] for symbol in symbols: self.customSymbols.append(self.AddData(SECReport8K, symbol, Resolution.Daily).Symbol) return symbols def OnData(self, data): for customSymbol in self.customSymbols: if not self.ActiveSecurities.ContainsKey(customSymbol.Underlying): raise Exception(f"Custom data undelrying ({customSymbol.Underlying}) Symbol was not found in active securities")