Louis Szeto
8a087f2166
Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
98 lines
3.8 KiB
C#
98 lines
3.8 KiB
C#
/*
|
|
* 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.
|
|
*
|
|
*/
|
|
|
|
using System;
|
|
using System.Collections.Generic;
|
|
using QuantConnect.Algorithm;
|
|
using QuantConnect.Algorithm.Framework.Alphas;
|
|
using QuantConnect.Algorithm.Framework.Portfolio;
|
|
using QuantConnect.Interfaces;
|
|
|
|
namespace QuantConnect.DataLibrary.Tests
|
|
{
|
|
/// <summary>
|
|
/// Example algorithm of using RiskParityPortfolioConstructionModel
|
|
/// </summary>
|
|
public class RiskParityPortfolioAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
|
{
|
|
public override void Initialize()
|
|
{
|
|
SetStartDate(2021, 2, 21);
|
|
SetEndDate(2021, 3, 30);
|
|
SetCash(100000);
|
|
SetSecurityInitializer(security => security.SetMarketPrice(GetLastKnownPrice(security)));
|
|
|
|
AddEquity("SPY", Resolution.Daily);
|
|
AddEquity("AAPL", Resolution.Daily);
|
|
|
|
AddAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1)));
|
|
SetPortfolioConstruction(new RiskParityPortfolioConstructionModel());
|
|
}
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
|
|
/// </summary>
|
|
public bool CanRunLocally { get; } = true;
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
|
/// </summary>
|
|
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
|
|
|
/// <summary>
|
|
/// Data Points count of all timeslices of algorithm
|
|
/// </summary>
|
|
public long DataPoints => 252;
|
|
|
|
/// <summary>
|
|
/// Data Points count of the algorithm history
|
|
/// </summary>
|
|
public int AlgorithmHistoryDataPoints => 509;
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
|
/// </summary>
|
|
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
|
{
|
|
{"Total Trades", "42"},
|
|
{"Average Win", "0.01%"},
|
|
{"Average Loss", "0.00%"},
|
|
{"Compounding Annual Return", "3.593%"},
|
|
{"Drawdown", "4.900%"},
|
|
{"Expectancy", "0.304"},
|
|
{"Net Profit", "0.368%"},
|
|
{"Sharpe Ratio", "0.227"},
|
|
{"Probabilistic Sharpe Ratio", "38.412%"},
|
|
{"Loss Rate", "47%"},
|
|
{"Win Rate", "53%"},
|
|
{"Profit-Loss Ratio", "1.48"},
|
|
{"Alpha", "-0.103"},
|
|
{"Beta", "1.222"},
|
|
{"Annual Standard Deviation", "0.201"},
|
|
{"Annual Variance", "0.04"},
|
|
{"Information Ratio", "-0.845"},
|
|
{"Tracking Error", "0.09"},
|
|
{"Treynor Ratio", "0.037"},
|
|
{"Total Fees", "$42.65"},
|
|
{"Estimated Strategy Capacity", "$720000000.00"},
|
|
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
|
|
{"Portfolio Turnover", "2.99%"},
|
|
{"OrderListHash", "f0d4972dbf679730bf8c8de2674d4975"}
|
|
};
|
|
|
|
}
|
|
}
|