AlexCatarino
3da8449fea
In python algorithm using Universe Selection, the selector method should return a List<Symbol>. To make it more pythonic, we allow returning python list. The conversion is, then, performed in C# side.
94 lines
4.0 KiB
Python
94 lines
4.0 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.Core")
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AddReference("QuantConnect.Common")
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AddReference("QuantConnect.Algorithm")
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from System import *
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from System.Collections.Generic import List
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Orders import *
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from QuantConnect.Data.UniverseSelection import *
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from datetime import datetime
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### <summary>
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### Universe Selection regression algorithm simulates an edge case. In one week, Google listed two new symbols, delisted one of them and changed
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### tickers.
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### </summary>
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### <meta name="tag" content="regression test" />
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class UniverseSelectionRegressionAlgorithm(QCAlgorithm):
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'''Basic template algorithm simply initializes the date range and cash'''
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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.SetStartDate(2014,03,22) #Set Start Date
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self.SetEndDate(2014,04,07) #Set End Date
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self.SetCash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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# security that exists with no mappings
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self.AddEquity("SPY", Resolution.Daily)
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# security that doesn't exist until half way in backtest (comes in as GOOCV)
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self.AddEquity("GOOG", Resolution.Daily)
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self.UniverseSettings.Resolution = Resolution.Daily
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self.AddUniverse(self.CoarseSelectionFunction)
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self.__delistedSymbols = []
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self.__changes = None
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def CoarseSelectionFunction(self, coarse):
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return [ c.Symbol for c in coarse if c.Symbol.Value == "GOOG" or c.Symbol.Value == "GOOCV" or c.Symbol.Value == "GOOAV" or c.Symbol.Value == "GOOGL" ]
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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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if self.Transactions.OrdersCount == 0:
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self.MarketOrder("SPY", 100)
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for kvp in data.Delistings:
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self.__delistedSymbols.append(kvp.Key)
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if self.Time.date == datetime(2014, 4, 7):
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self.Liquidade()
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return
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if self.__changes is None:
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return
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for security in self.__changes.AddedSecurities:
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if security.Symbol in data:
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self.Log("{0}: Added Security: {1}".format(self.Time, security.Symbol))
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self.MarketOnOpenOrder(security.Symbol, 100)
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for security in self.__changes.RemovedSecurities:
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if security.Symbol in data:
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self.Log("{0}: Removed Security: {1}".format(self.Time, security.Symbol))
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if security.Symbol not in self.__delistedSymbols:
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self.Log("Not in delisted: {0}:".format(security.Symbol))
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self.MarketOnOpenOrder(security.Symbol, -100)
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def OnSecuritiesChanged(self, changes):
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self.__changes = changes
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def OnOrderEvent(self, orderEvent):
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if orderEvent.Status == OrderStatus.Submitted:
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self.Log("{0}: Submitted: {1}".format(self.Time, self.Transactions.GetOrderById(orderEvent.OrderId)))
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if orderEvent.Status == OrderStatus.Filled:
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self.Log("{0}: Filled: {1}".format(self.Time, self.Transactions.GetOrderById(orderEvent.OrderId))) |