Martin-Molinero
03f56481d4
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Python research import improvements - Improve start.py for research env - Remove unrequired imports * Centralize algorithm imports * Add regression test GH action * Unit test python import clean up * Join research and main imports * More python import clean up * Fix failing skipped regression algorithm
55 lines
2.5 KiB
Python
55 lines
2.5 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 AlgorithmImports 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}")
|