wehub-resource-sync
46 lines
1.9 KiB
Python
46 lines
1.9 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 CustomBrokerageModelRegressionAlgorithm import CustomBrokerageModel
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### <summary>
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### Regression algorithm to test we can specify a custom benchmark model, and override some of its methods
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### </summary>
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class CustomBenchmarkRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2013,10,7)
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self.set_end_date(2013,10,11)
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self.set_brokerage_model(CustomBrokerageModelWithCustomBenchmark())
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self.add_equity("SPY", Resolution.DAILY)
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self.update_request_submitted = False
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def on_data(self, slice):
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benchmark = self.benchmark.evaluate(self.time)
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if (self.time.day % 2 == 0) and (benchmark != 1):
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raise AssertionError(f"Benchmark should be 1, but was {benchmark}")
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if (self.time.day % 2 == 1) and (benchmark != 2):
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raise AssertionError(f"Benchmark should be 2, but was {benchmark}")
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class CustomBenchmark:
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def evaluate(self, time):
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if time.day % 2 == 0:
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return 1
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else:
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return 2
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class CustomBrokerageModelWithCustomBenchmark(CustomBrokerageModel):
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def get_benchmark(self, securities):
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return CustomBenchmark()
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