Overall Statistics |
Total Trades 7 Average Win 0.01% Average Loss -0.38% Compounding Annual Return 1192.565% Drawdown 1.700% Expectancy -0.322 Net Profit 3.326% Sharpe Ratio 6.634 Loss Rate 33% Win Rate 67% Profit-Loss Ratio 0.02 Alpha 0 Beta 152.168 Annual Standard Deviation 0.253 Annual Variance 0.064 Information Ratio 6.592 Tracking Error 0.253 Treynor Ratio 0.011 Total Fees $67.34 |
# 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.Alphas import * from QuantConnect.Algorithm.Framework.Execution import * from QuantConnect.Algorithm.Framework.Risk import * from QuantConnect.Algorithm.Framework.Selection import * from Alphas.RsiAlphaModel import RsiAlphaModel from Alphas.EmaCrossAlphaModel import EmaCrossAlphaModel from Portfolio.EqualWeightingPortfolioConstructionModel import EqualWeightingPortfolioConstructionModel from datetime import timedelta import numpy as np ### <summary> ### Show cases how to use the CompositeAlphaModel to define. ### </summary> class CompositeAlphaModelFrameworkAlgorithm(QCAlgorithmFramework): '''Show cases how to use the CompositeAlphaModel to define.''' def Initialize(self): self.SetStartDate(2013,10,7) #Set Start Date self.SetEndDate(2013,10,11) #Set End Date self.SetCash(100000) #Set Strategy Cash # even though we're using a framework algorithm, we can still add our securities # using the AddEquity/Forex/Crypto/ect methods and then pass them into a manual # universe selection model using Securities.Keys self.AddEquity("SPY") self.AddEquity("IBM") self.AddEquity("BAC") self.AddEquity("AIG") # define a manual universe of all the securities we manually registered self.SetUniverseSelection(ManualUniverseSelectionModel()) # define alpha model as a composite of the rsi and ema cross models self.SetAlpha(CompositeAlphaModel(RsiAlphaModel(), EmaCrossAlphaModel())) # default models for the rest self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel()) self.SetExecution(ImmediateExecutionModel()) self.SetRiskManagement(NullRiskManagementModel())