Michael Handschuh
fdc866fda0
We didn't experience the expected performance improvements. Locally under unit test there was aboout an order of magnitude throughput increase, but when run against the history benchmark, this new approach was 60% slower. We're reverting this for now to perform further analysis and better understand the performance profiling of the python history stack.
93 lines
4.2 KiB
Python
93 lines
4.2 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.Algorithm")
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AddReference("QuantConnect.Algorithm.Framework")
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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.Orders import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Algorithm.Framework import *
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from QuantConnect.Algorithm.Framework.Alphas import *
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from QuantConnect.Algorithm.Framework.Portfolio import *
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from QuantConnect.Algorithm.Framework.Selection import *
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from Alphas.ConstantAlphaModel import ConstantAlphaModel
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from Selection.OptionUniverseSelectionModel import OptionUniverseSelectionModel
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from Execution.ImmediateExecutionModel import ImmediateExecutionModel
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from Risk.NullRiskManagementModel import NullRiskManagementModel
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from datetime import date, timedelta
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### <summary>
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### Basic template options framework algorithm uses framework components
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### to define an algorithm that trades options.
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### </summary>
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class BasicTemplateOptionsFrameworkAlgorithm(QCAlgorithmFramework):
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def Initialize(self):
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self.UniverseSettings.Resolution = Resolution.Minute
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self.SetStartDate(2014, 6, 5)
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self.SetEndDate(2014, 6, 6)
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self.SetCash(100000)
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# set framework models
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self.SetUniverseSelection(EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(self.SelectOptionChainSymbols))
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self.SetAlpha(ConstantOptionContractAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(hours = 0.5)))
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self.SetPortfolioConstruction(SingleSharePortfolioConstructionModel())
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self.SetExecution(ImmediateExecutionModel())
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self.SetRiskManagement(NullRiskManagementModel())
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def SelectOptionChainSymbols(self, utcTime):
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newYorkTime = Extensions.ConvertFromUtc(utcTime, TimeZones.NewYork)
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ticker = "TWX" if newYorkTime.date() < date(2014, 6, 6) else "AAPL"
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return [ Symbol.Create(ticker, SecurityType.Option, Market.USA, f"?{ticker}") ]
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class EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(OptionUniverseSelectionModel):
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'''Creates option chain universes that select only the earliest expiry ATM weekly put contract
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and runs a user defined optionChainSymbolSelector every day to enable choosing different option chains'''
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def __init__(self, select_option_chain_symbols):
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super().__init__(timedelta(1), select_option_chain_symbols)
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def Filter(self, filter):
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'''Defines the option chain universe filter'''
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return (filter.Strikes(+1, +1)
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.Expiration(timedelta(0), timedelta(7))
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.WeeklysOnly()
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.PutsOnly()
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.OnlyApplyFilterAtMarketOpen())
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class ConstantOptionContractAlphaModel(ConstantAlphaModel):
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'''Implementation of a constant alpha model that only emits insights for option symbols'''
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def __init__(self, type, direction, period):
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super().__init__(type, direction, period)
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def ShouldEmitInsight(self, utcTime, symbol):
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# only emit alpha for option symbols and not underlying equity symbols
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if symbol.SecurityType != SecurityType.Option:
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return False
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return super().ShouldEmitInsight(utcTime, symbol)
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class SingleSharePortfolioConstructionModel(PortfolioConstructionModel):
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'''Portoflio construction model that sets target quantities to 1 for up insights and -1 for down insights'''
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def CreateTargets(self, algorithm, insights):
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targets = []
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for insight in insights:
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targets.append(PortfolioTarget(insight.Symbol, insight.Direction))
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return targets |