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quantconnect--lean/Algorithm.CSharp/MaximumDrawdownPercentPortfolioFrameworkRegressionAlgorithm.cs
T
Alexandre Catarino 3b2e165254
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Adds BaseFrameworkRegressionAlgorithm and New Regression Algorithms (#7116)
* Renames and Updates BaseAlphaModelFrameworkRegressionAlgorithm

The `BaseFrameworkRegressionAlgorithm ` will be used for multiple framework regression tests

* Updates and Renames EmaCrossAlphaModelFrameworkAlgorithm

Adds "Regression" to inform that it's a regression algorithm.

* Updates and Renames MaximumPortfolioDrawdownFrameworkAlgorithm

Adds "Regression" to inform that it's a regression algorithm, and use the model name: `MaximumDrawdownPercentPortfolio`

* Adds New Regression Algorithms
2023-03-22 11:21:30 -03:00

80 lines
3.2 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.Collections.Generic;
using QuantConnect.Algorithm.Framework.Risk;
using QuantConnect.Algorithm.Framework.Selection;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm to assert the behavior of <see cref="MaximumDrawdownPercentPortfolio"/> Risk Management Model
/// </summary>
public class MaximumDrawdownPercentPortfolioFrameworkRegressionAlgorithm : BaseFrameworkRegressionAlgorithm
{
public override void Initialize()
{
base.Initialize();
SetUniverseSelection(new ManualUniverseSelectionModel(QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA)));
// define risk management model as a composite of several risk management models
SetRiskManagement(new CompositeRiskManagementModel(
new MaximumDrawdownPercentPortfolio(0.01m), // Avoid loss of initial capital
new MaximumDrawdownPercentPortfolio(0.015m, true) // Avoid profit losses
));
}
public override void OnEndOfAlgorithm()
{
}
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 304;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public override Dictionary<string, string> ExpectedStatistics => new()
{
{"Total Trades", "8"},
{"Average Win", "2.43%"},
{"Average Loss", "-1.45%"},
{"Compounding Annual Return", "12.322%"},
{"Drawdown", "6.000%"},
{"Expectancy", "-0.109"},
{"Net Profit", "0.949%"},
{"Sharpe Ratio", "0.834"},
{"Probabilistic Sharpe Ratio", "47.313%"},
{"Loss Rate", "67%"},
{"Win Rate", "33%"},
{"Profit-Loss Ratio", "1.67"},
{"Alpha", "-0.065"},
{"Beta", "0.79"},
{"Annual Standard Deviation", "0.11"},
{"Annual Variance", "0.012"},
{"Information Ratio", "-1.027"},
{"Tracking Error", "0.104"},
{"Treynor Ratio", "0.116"},
{"Total Fees", "$35.09"},
{"Estimated Strategy Capacity", "$35000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "23.27%"},
{"OrderListHash", "b4ded74daedcb4bb12b65d6743f1300f"}
};
}
}