Martin Molinero
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.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.Alphas import *
|
|
from QuantConnect.Algorithm.Framework.Selection import *
|
|
from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel
|
|
from Alphas.ConstantAlphaModel import ConstantAlphaModel
|
|
from Execution.ImmediateExecutionModel import ImmediateExecutionModel
|
|
from Risk.MaximumSectorExposureRiskManagementModel import MaximumSectorExposureRiskManagementModel
|
|
from datetime import date, timedelta
|
|
|
|
### <summary>
|
|
### This example algorithm defines its own custom coarse/fine fundamental selection model
|
|
### with equally weighted portfolio and a maximum sector exposure.
|
|
### </summary>
|
|
class SectorExposureRiskFrameworkAlgorithm(QCAlgorithm):
|
|
'''This example algorithm defines its own custom coarse/fine fundamental selection model
|
|
### with equally weighted portfolio and a maximum sector exposure.'''
|
|
|
|
def Initialize(self):
|
|
|
|
# Set requested data resolution
|
|
self.UniverseSettings.Resolution = Resolution.Daily
|
|
|
|
self.SetStartDate(2014, 3, 24)
|
|
self.SetEndDate(2014, 4, 7)
|
|
self.SetCash(100000)
|
|
|
|
# set algorithm framework models
|
|
self.SetUniverseSelection(FineFundamentalUniverseSelectionModel(self.SelectCoarse, self.SelectFine))
|
|
self.SetAlpha(ConstantAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(1)))
|
|
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel())
|
|
self.SetRiskManagement(MaximumSectorExposureRiskManagementModel())
|
|
|
|
def OnOrderEvent(self, orderEvent):
|
|
if orderEvent.Status == OrderStatus.Filled:
|
|
self.Debug(f"Order event: {orderEvent}. Holding value: {self.Securities[orderEvent.Symbol].Holdings.AbsoluteHoldingsValue}")
|
|
|
|
def SelectCoarse(self, coarse):
|
|
tickers = ["AAPL", "AIG", "IBM"] if self.Time.date() < date(2014, 4, 1) else [ "GOOG", "BAC", "SPY" ]
|
|
return [Symbol.Create(x, SecurityType.Equity, Market.USA) for x in tickers]
|
|
|
|
def SelectFine(self, fine):
|
|
return [f.Symbol for f in fine] |