AlexCatarino
122 lines
4.7 KiB
Python
122 lines
4.7 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")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Data import SubscriptionDataSource
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from QuantConnect.Python import PythonData
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from QCAlgorithm import QCAlgorithm
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from datetime import date, timedelta, datetime
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import decimal as d
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### <summary>
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### This algorithm shows how to grab symbols from an external api each day
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### and load data using the universe selection feature. In this example we
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### define a custom data type for the NYSE top gainers and then short the
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### top 2 gainers each day
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="universes" />
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### <meta name="tag" content="custom universes" />
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class CustomDataUniverseAlgorithm(QCAlgorithm):
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def Initialize(self):
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# Data ADDED via universe selection is added with Daily resolution.
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self.UniverseSettings.Resolution = Resolution.Daily
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self.SetStartDate(2015,1,5)
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self.SetEndDate(2015,7,1)
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self.SetCash(100000)
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self.AddEquity("SPY", Resolution.Daily)
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self.SetBenchmark("SPY")
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# add a custom universe data source (defaults to usa-equity)
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self.AddUniverse(NyseTopGainers, "universe-nyse-top-gainers", Resolution.Daily, self.nyseTopGainers)
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def nyseTopGainers(self, data):
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return [ x.Symbol for x in data if x["TopGainersRank"] <= 2 ]
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def OnData(self, slice):
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pass
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def OnSecuritiesChanged(self, changes):
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self._changes = changes
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for security in changes.RemovedSecurities:
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# liquidate securities that have been removed
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if security.Invested:
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self.Liquidate(security.Symbol)
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self.Log("Exit {0} at {1}".format(security.Symbol, security.Close))
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for security in changes.AddedSecurities:
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# enter short positions on new securities
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if not security.Invested and security.Close != 0:
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qty = self.CalculateOrderQuantity(security.Symbol, -0.25)
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self.MarketOnOpenOrder(security.Symbol, qty)
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self.Log("Enter {0} at {1}".format(security.Symbol, security.Close))
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class NyseTopGainers(PythonData):
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def __init__(self):
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self.count = 0
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self.last_date = datetime.min
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def GetSource(self, config, date, isLiveMode):
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url = "http://www.wsj.com/mdc/public/page/2_3021-gainnyse-gainer.html" if isLiveMode else \
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"https://www.dropbox.com/s/vrn3p38qberw3df/nyse-gainers.csv?dl=1"
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return SubscriptionDataSource(url, SubscriptionTransportMedium.RemoteFile)
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def Reader(self, config, line, date, isLiveMode):
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if not isLiveMode:
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# backtest gets data from csv file in dropbox
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if not (line.strip() and line[0].isdigit()): return None
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csv = line.split(',')
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nyse = NyseTopGainers()
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nyse.Time = datetime.strptime(csv[0], "%Y%m%d")
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nyse.EndTime = nyse.Time + timedelta(1)
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nyse.Symbol = Symbol.Create(csv[1], SecurityType.Equity, Market.USA)
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nyse["TopGainersRank"] = int(csv[2])
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return nyse
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if self.last_date != date:
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# reset our counter for the new day
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self.last_date = date
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self.count = 0
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# parse the html into a symbol
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if not line.startswith('<a href=\"/public/quotes/main.html?symbol='):
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# we're only looking for lines that contain the symbols
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return None
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last_close_paren = line.rfind(')')
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last_open_paren = line.rfind('(')
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if last_open_paren == -1 or last_close_paren == -1:
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return None
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symbol_string = line[last_open_paren + 1:last_close_paren]
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nyse = NyseTopGainers()
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nyse.Time = date
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nyse.EndTime = nyse.Time + timedelta(1)
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nyse.Symbol = Symbol.Create(symbol_string, SecurityType.Equity, Market.USA)
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nyse["TopGainersRank"] = self.count
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self.count = self.count + 1
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return nyse |