Jing Wu
39 lines
1.5 KiB
Python
39 lines
1.5 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 clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Indicators")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Data import *
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### <summary>
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### Benchmark Algorithm: Pure processing of 1 equity second resolution with the same benchmark.
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### </summary>
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### <remarks>
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### This should eliminate the synchronization part of LEAN and focus on measuring the performance of a single datafeed and event handling system.
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### </remarks>
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class EmptySingleSecuritySecondEquityBenchmark(QCAlgorithm):
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def Initialize(self):
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self.SetStartDate(2008, 1, 1)
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self.SetEndDate(2009, 1, 1)
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self.SetBenchmark(lambda x: 1)
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self.AddEquity("SPY", Resolution.Second)
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def OnData(self, data):
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pass |