wehub-resource-sync
53 lines
2.0 KiB
Python
53 lines
2.0 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# 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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### This algorithm sends a list of portfolio targets to vBsase API
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### </summary>
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class VBaseSignalExportDemonstrationAlgorithm(QCAlgorithm):
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def initialize(self):
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''' Initialize the date'''
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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_cash(100000) # Set Strategy Cash
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self.vbase_apikey = "YOUR VBASE API KEY"
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self.vbase_collection_name = "YOUR VBASE COLLECTION NAME"
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self._symbols = [
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Symbol.create("SPY", SecurityType.EQUITY, Market.USA),
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Symbol.create("IBM", SecurityType.EQUITY, Market.USA)
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]
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for symbol in self._symbols:
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self.add_equity(symbol)
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self._sentSignal = False
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self.signal_export.add_signal_export_provider(VBaseSignalExport(self.vbase_apikey, self.vbase_collection_name))
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def on_data(self, data):
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if self._sentSignal:
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return
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self._sentSignal = True
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self.targets = []
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self.targets.append(PortfolioTarget(self._symbols[0], 0.25)) # SPY 25% of the portfolio
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self.targets.append(PortfolioTarget(self._symbols[1], 0.75)) # IBM 75% of the portfolio
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self.signal_export.set_target_portfolio(self.targets)
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