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.
91 lines
4.1 KiB
Python
91 lines
4.1 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.Securities 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.FutureUniverseSelectionModel import FutureUniverseSelectionModel
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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 futures framework algorithm uses framework components
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### to define an algorithm that trades futures.
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### </summary>
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class BasicTemplateFuturesFrameworkAlgorithm(QCAlgorithmFramework):
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def Initialize(self):
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self.UniverseSettings.Resolution = Resolution.Minute
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self.SetStartDate(2013, 10, 7)
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self.SetEndDate(2013, 10, 11)
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self.SetCash(100000)
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# set framework models
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self.SetUniverseSelection(FrontMonthFutureUniverseSelectionModel(self.SelectFutureChainSymbols))
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self.SetAlpha(ConstantFutureContractAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(1)))
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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 SelectFutureChainSymbols(self, utcTime):
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newYorkTime = Extensions.ConvertFromUtc(utcTime, TimeZones.NewYork)
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ticker = Futures.Indices.SP500EMini if newYorkTime.date() < date(2013, 10, 9) else Futures.Metals.Gold
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return [ Symbol.Create(ticker, SecurityType.Future, Market.USA) ]
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class FrontMonthFutureUniverseSelectionModel(FutureUniverseSelectionModel):
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'''Creates futures chain universes that select the front month contract and runs a user
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defined futureChainSymbolSelector every day to enable choosing different futures chains'''
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def __init__(self, select_future_chain_symbols):
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super().__init__(timedelta(1), select_future_chain_symbols)
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def Filter(self, filter):
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'''Defines the futures chain universe filter'''
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return (filter.FrontMonth()
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.OnlyApplyFilterAtMarketOpen())
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class ConstantFutureContractAlphaModel(ConstantAlphaModel):
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'''Implementation of a constant alpha model that only emits insights for future 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 future symbols and not underlying equity symbols
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if symbol.SecurityType != SecurityType.Future:
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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 |