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quantconnect--lean/Algorithm.Python/SpreadExecutionModelRegressionAlgorithm.py
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Louis Szeto 9f15ca4c9c
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feature-<#5631>-<Create SpreadExecutionModel> (#5633)
* Create SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.py

* Create SpreadExecutionModel.cs

* Create SpreadExecutionModelTests.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModel.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModel.cs

* Update SpreadExecutionModel.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModel.cs

* Update QuantConnect.Algorithm.Framework.csproj

* Create SpreadExecutionModelRegressionAlgorithm.py

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModelTests.cs

* Update SpreadExecutionModel.py

* Update SpreadExecutionModel.cs

* Address review

- Adding CSharp regression algorithm implementation
- Updating unit tests, minor format changes

* Address review. Add comment and Abs spread percent

Co-authored-by: Martin-Molinero <martin@quantconnect.com>
2021-06-09 14:55:00 -03:00

66 lines
2.8 KiB
Python

# 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 clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Algorithm.Framework")
AddReference("QuantConnect.Common")
from System import *
from QuantConnect import *
from QuantConnect.Orders import *
from QuantConnect.Algorithm import *
from QuantConnect.Algorithm.Framework import *
from QuantConnect.Algorithm.Framework.Selection import *
from Alphas.RsiAlphaModel import RsiAlphaModel
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
from Execution.SpreadExecutionModel import SpreadExecutionModel
### <summary>
### Regression algorithm for the SpreadExecutionModel.
### This algorithm shows how the execution model works to
### submit orders only when the price is on desirably tight spread.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="using quantconnect" />
### <meta name="tag" content="trading and orders" />
class SpreadExecutionModelRegressionAlgorithm(QCAlgorithm):
'''Regression algorithm for the SpreadExecutionModel.
This algorithm shows how the execution model works to
submit orders only when the price is on desirably tight spread.'''
def Initialize(self):
self.SetStartDate(2013,10,7)
self.SetEndDate(2013,10,11)
self.SetUniverseSelection(ManualUniverseSelectionModel([
Symbol.Create('AIG', SecurityType.Equity, Market.USA),
Symbol.Create('BAC', SecurityType.Equity, Market.USA),
Symbol.Create('IBM', SecurityType.Equity, Market.USA),
Symbol.Create('SPY', SecurityType.Equity, Market.USA)
]))
# using hourly rsi to generate more insights
self.SetAlpha(RsiAlphaModel(14, Resolution.Hour))
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
self.SetExecution(SpreadExecutionModel())
self.InsightsGenerated += self.OnInsightsGenerated
def OnInsightsGenerated(self, algorithm, data):
self.Log(f"{self.Time}: {', '.join(str(x) for x in data.Insights)}")
def OnOrderEvent(self, orderEvent):
self.Log(f"{self.Time}: {orderEvent}")