AlexCatarino
595700e340
`EqualEeightingPortfolioConstructionModel` (C# and Python) allocates all cash to the stocks who have insights in universe. - Fixes regression tests to reflect the model logic change - Fixes imports in python algorithms to use python models when available
65 lines
3.0 KiB
Python
65 lines
3.0 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.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.StandardDeviationExecutionModel import StandardDeviationExecutionModel
|
|
from datetime import timedelta
|
|
|
|
### <summary>
|
|
### Regression algorithm for the StandardDeviationExecutionModel.
|
|
### This algorithm shows how the execution model works to split up orders and submit them
|
|
### only when the price is 2 standard deviations from the 60min mean (default model settings).
|
|
### </summary>
|
|
### <meta name="tag" content="using data" />
|
|
### <meta name="tag" content="using quantconnect" />
|
|
### <meta name="tag" content="trading and orders" />
|
|
class StandardDeviationExecutionModelRegressionAlgorithm(QCAlgorithmFramework):
|
|
'''Regression algorithm for the StandardDeviationExecutionModel.
|
|
This algorithm shows how the execution model works to split up orders and submit them
|
|
only when the price is 2 standard deviations from the 60min mean (default model settings).'''
|
|
|
|
def Initialize(self):
|
|
''' Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
|
|
|
|
# Set requested data resolution
|
|
self.UniverseSettings.Resolution = Resolution.Minute
|
|
|
|
self.SetStartDate(2013,10,7)
|
|
self.SetEndDate(2013,10,11)
|
|
self.SetCash(1000000)
|
|
|
|
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)
|
|
]))
|
|
|
|
self.SetAlpha(RsiAlphaModel(14, Resolution.Hour))
|
|
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
|
|
self.SetExecution(StandardDeviationExecutionModel())
|
|
|
|
def OnOrderEvent(self, orderEvent):
|
|
self.Log(f"{self.Time}: {orderEvent}") |