Martin-Molinero
cb326788b3
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Filter out small orders based on Setting - BuyingPowerModel will filter out small orders based on algorithm setting, a % of PTV, instead of hard coded 1 share value. Addin unit and regression tests - Updating regression algorithms to use new setting, reduce order trades * Update regression algorithms
66 lines
2.7 KiB
Python
66 lines
2.7 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 AlgorithmImports import *
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### <summary>
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### Basic template framework algorithm uses framework components to define the algorithm.
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### Shows EqualWeightingPortfolioConstructionModel.LongOnly() application
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### </summary>
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### <meta name="tag" content="alpha streams" />
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### <meta name="tag" content="using quantconnect" />
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### <meta name="tag" content="algorithm framework" />
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class LongOnlyAlphaStreamAlgorithm(QCAlgorithm):
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'''Basic template framework algorithm uses framework components to define the algorithm.
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Shows EqualWeightingPortfolioConstructionModel.LongOnly() application'''
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def Initialize(self):
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# 1. Required:
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self.SetStartDate(2013, 10, 7)
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self.SetEndDate(2013, 10, 11)
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# 2. Required: Alpha Streams Models:
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self.SetBrokerageModel(BrokerageName.AlphaStreams)
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# 3. Required: Significant AUM Capacity
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self.SetCash(1000000)
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# Only SPY will be traded
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self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(Resolution.Daily, PortfolioBias.Long))
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self.SetExecution(ImmediateExecutionModel())
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# Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
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# Commented so regression algorithm is more sensitive
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#self.Settings.MinimumOrderMarginPortfolioPercentage = 0.005
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# Set algorithm framework models
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self.SetUniverseSelection(ManualUniverseSelectionModel(
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[Symbol.Create(x, SecurityType.Equity, Market.USA) for x in ["SPY", "IBM"]]))
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def OnData(self, slice):
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if self.Portfolio.Invested: return
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self.EmitInsights(
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[
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Insight.Price("SPY", timedelta(1), InsightDirection.Up),
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Insight.Price("IBM", timedelta(1), InsightDirection.Down)
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])
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def OnOrderEvent(self, orderEvent):
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if orderEvent.Status == OrderStatus.Filled:
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if self.Securities[orderEvent.Symbol].Holdings.IsShort:
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raise ValueError("Invalid position, should not be short");
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self.Debug(orderEvent)
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