# 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.UniverseSelection import * ### ### Demonstration of how to estimate constituents of QC500 index based on the company fundamentals ### The algorithm creates a default tradable and liquid universe containing 500 US equities ### which are chosen at the first trading day of each month. ### ### ### ### ### class ConstituentsQC500GeneratorAlgorithm(QCAlgorithm): def Initialize(self): '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.''' self.UniverseSettings.Resolution = Resolution.Daily self.SetStartDate(2018, 1, 1) # Set Start Date self.SetEndDate(2019, 1, 1) # Set End Date self.SetCash(100000) # Set Strategy Cash # Add QC500 Universe self.AddUniverse(self.Universe.Index.QC500)