wehub-resource-sync
47 lines
2.1 KiB
Python
47 lines
2.1 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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### Shows how to set a custom benchmark for you algorithms
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="benchmarks" />
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class CustomBenchmarkAlgorithm(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.set_start_date(2013,10,7) #Set Start Date
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self.set_end_date(2013,10,11) #Set End Date
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self.set_cash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.add_equity("SPY", Resolution.SECOND)
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# Disabling the benchmark / setting to a fixed value
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# self.set_benchmark(lambda x: 0)
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# Set the benchmark to AAPL US Equity
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self.set_benchmark(Symbol.create("AAPL", SecurityType.EQUITY, Market.USA))
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def on_data(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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if not self.portfolio.invested:
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self.set_holdings("SPY", 1)
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self.debug("Purchased Stock")
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tuple_result = SymbolCache.try_get_symbol("AAPL", None)
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if tuple_result[0]:
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raise AssertionError("Benchmark Symbol is not expected to be added to the Symbol cache")
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