Files
quantconnect--lean/Algorithm.CSharp/TrailingStopRiskFrameworkRegressionAlgorithm.cs
T
Derek Melchin 0fa2ea19bc
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Reset trailing stop model highwater mark upon security liquidation (#6724)
* Fix trailing stop reset

* Add regression algorithm
2022-11-07 17:46:46 -03:00

115 lines
4.5 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.Data;
using QuantConnect.Interfaces;
using QuantConnect.Algorithm.Framework.Risk;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm which tests that a trailing stop liquidates and restarts correctly
/// </summary>
public class TrailingStopRiskFrameworkRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
public override void Initialize()
{
SetStartDate(2014, 6, 5);
SetEndDate(2014, 6, 9);
SetCash(100000);
AddEquity("AAPL");
AddRiskManagement(new TrailingStopRiskManagementModel(0.01m));
}
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
SetHoldings("AAPL", 1);
}
}
/// <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 => 2371;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <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", "3"},
{"Average Win", "0%"},
{"Average Loss", "-0.31%"},
{"Compounding Annual Return", "202.556%"},
{"Drawdown", "1.400%"},
{"Expectancy", "-1"},
{"Net Profit", "1.426%"},
{"Sharpe Ratio", "9.374"},
{"Probabilistic Sharpe Ratio", "81.575%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "1.741"},
{"Beta", "-1.155"},
{"Annual Standard Deviation", "0.133"},
{"Annual Variance", "0.018"},
{"Information Ratio", "5.447"},
{"Tracking Error", "0.149"},
{"Treynor Ratio", "-1.075"},
{"Total Fees", "$71.90"},
{"Estimated Strategy Capacity", "$20000000.00"},
{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
{"Fitness Score", "0.249"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "-40.94"},
{"Portfolio Turnover", "0.497"},
{"Total Insights Generated", "0"},
{"Total Insights Closed", "0"},
{"Total Insights Analysis Completed", "0"},
{"Long Insight Count", "0"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$0"},
{"Total Accumulated Estimated Alpha Value", "$0"},
{"Mean Population Estimated Insight Value", "$0"},
{"Mean Population Direction", "0%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "0%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "87da67837d4a2c4c4a419f01b467d9c6"}
};
}
}