Marco Grassi
e823dfdfb7
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
49 lines
1.7 KiB
Python
49 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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### Regression algorithm to test zeroed benchmark through BrokerageModel override
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### </summary>
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### <meta name="tag" content="regression test" />
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class ZeroedBenchmarkRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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self.SetCash(100000)
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self.SetStartDate(2013,10,7)
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self.SetEndDate(2013,10,8)
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# Add Equity
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self.AddEquity("SPY", Resolution.Hour)
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# Use our Test Brokerage Model with zerod default benchmark
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self.SetBrokerageModel(TestBrokerageModel())
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def OnData(self, data):
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'''OnData 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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self.SetHoldings("SPY", 1)
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class TestBrokerageModel(DefaultBrokerageModel):
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def GetBenchmark(self, securities):
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return FuncBenchmark(self.func)
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def func(self, datetime):
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return 0
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