wehub-resource-sync
50 lines
2.0 KiB
Python
50 lines
2.0 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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from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel
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### <summary>
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### Regression algorithm showing how to implement a custom universe selection model and asserting it's behavior
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### </summary>
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class CustomUniverseSelectionModelRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2014,3,24)
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self.set_end_date(2014,4,7)
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self.universe_settings.resolution = Resolution.DAILY
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self.set_universe_selection(MyCustomUniverseSelectionModel())
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def on_data(self, data):
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'''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if not self.portfolio.invested:
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for kvp in self.active_securities:
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self.set_holdings(kvp.key, 0.1)
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class MyCustomUniverseSelectionModel(FundamentalUniverseSelectionModel):
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def __init__(self, universe_settings = None):
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super().__init__(universe_settings)
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self._selected = False
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def select(self, algorithm, fundamental):
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if not self._selected:
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self._selected = True
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return [ Symbol.create('AAPL', SecurityType.EQUITY, Market.USA) ]
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return Universe.UNCHANGED
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