# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. # QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from AlgorithmImports import * ### ### This algorithm sends a list of portfolio targets to vBsase API ### class VBaseSignalExportDemonstrationAlgorithm(QCAlgorithm): def initialize(self): ''' Initialize the date''' self.set_start_date(2013,10, 7) self.set_end_date(2013,10,11) self.set_cash(100000) # Set Strategy Cash self.vbase_apikey = "YOUR VBASE API KEY" self.vbase_collection_name = "YOUR VBASE COLLECTION NAME" self._symbols = [ Symbol.create("SPY", SecurityType.EQUITY, Market.USA), Symbol.create("IBM", SecurityType.EQUITY, Market.USA) ] for symbol in self._symbols: self.add_equity(symbol) self._sentSignal = False self.signal_export.add_signal_export_provider(VBaseSignalExport(self.vbase_apikey, self.vbase_collection_name)) def on_data(self, data): if self._sentSignal: return self._sentSignal = True self.targets = [] self.targets.append(PortfolioTarget(self._symbols[0], 0.25)) # SPY 25% of the portfolio self.targets.append(PortfolioTarget(self._symbols[1], 0.75)) # IBM 75% of the portfolio self.signal_export.set_target_portfolio(self.targets)