# 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 datetime import datetime import clr clr.AddReference("System.Core") clr.AddReference("QuantConnect.Common") clr.AddReference("QuantConnect.Algorithm") from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Orders import * from QuantConnect.Data.UniverseSelection import * class UniverseSelectionRegressionAlgorithm(QCAlgorithm): '''Basic template algorithm simply initializes the date range and cash''' def __init__(self): self.__delistedSymbols = [] self.__changes = None def CoarseSelectionFunction(self, coarse): 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"] def Initialize(self): '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.''' self.SetStartDate(2014,03,22) #Set Start Date self.SetEndDate(2014,04,07) #Set End Date self.SetCash(100000) #Set Strategy Cash # Find more symbols here: http://quantconnect.com/data # security that exists with no mappings self.AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily) # security that doesn't exist until half way in backtest (comes in as GOOCV) self.AddSecurity(SecurityType.Equity, "GOOG", Resolution.Daily) self.UniverseSettings.Resolution = Resolution.Daily self.AddUniverse(self.CoarseSelectionFunction) def OnData(self, data): '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. Arguments: data: Slice object keyed by symbol containing the stock data ''' if self.Transactions.OrdersCount == 0: self.MarketOrder("SPY", 100) for kvp in data.Delistings: self.__delistedSymbols.append(kvp.Key) pyTime = datetime(self.Time) if pyTime.date == datetime(2014, 4, 7): self.Liquidade() return if self.__changes is not None: if all(security.Symbol in data.Bars for security in self.__changes.AddedSecurities): for security in self.__changes.AddedSecurities: self.Log("{0}: Added Security: {1}".format(pyTime, security.Symbol)) self.MarketOnOpenOrder(security.Symbol, 100) for security in self.__changes.RemovedSecurities: self.Log("{0}: Removed Security: {1}".format(pyTime, security.Symbol)) if security.Symbol not in self.__delistedSymbols: self.Log("Not in delisted: {0}:".format(security.Symbol)) self.MarketOnOpenOrder(security.Symbol, -100) self.__changes = None; def OnSecuritiesChanged(self, changes): self.__changes = changes def OnOrderEvent(self, orderEvent): if orderEvent.Status == OrderStatus.Submitted: self.Log("{0}: Submitted: {1}".format(self.Time, self.Transactions.GetOrderById(orderEvent.OrderId))) if orderEvent.Status == OrderStatus.Filled: self.Log("{0}: Filled: {1}".format(self.Time, self.Transactions.GetOrderById(orderEvent.OrderId)))