wehub-resource-sync
37 lines
1.7 KiB
Python
37 lines
1.7 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 AlgorithmImports import *
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### <summary>
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### Demonstration of how to estimate constituents of QC500 index based on the company fundamentals
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### The algorithm creates a default tradable and liquid universe containing 500 US equities
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### which are chosen at the first trading day of each month.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="universes" />
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### <meta name="tag" content="coarse universes" />
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### <meta name="tag" content="fine universes" />
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class ConstituentsQC500GeneratorAlgorithm(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.universe_settings.resolution = Resolution.DAILY
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self.set_start_date(2018, 1, 1) # Set Start Date
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self.set_end_date(2019, 1, 1) # Set End Date
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self.set_cash(100000) # Set Strategy Cash
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# Add QC500 Universe
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self.add_universe(self.universe.qc_500)
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