Martin-Molinero
410956bf9f
Regression Tests / 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
Python Virtual Environments / build (push) Has been cancelled
* Implement Trailing FreePortfolioValue - Implement Trailing FreePortfolioValue by default, users will be able to set it to a fixed number if desired. Adding regression algorithm - Setting the default 'MinimumOrderMarginPortfolioPercentage' from 0 to 0.1% of the TPV to avoud tiny trades by default * Update existing regression algorithms * Address reviews - Send warning message to the user if a trade does not happen due to the default setting of the minimum order margin percentage value * Address reivews * Rename TotalPortfolioValueLessFreeBuffer * Update new regression algorithm
76 lines
3.1 KiB
C#
76 lines
3.1 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 QuantConnect.Algorithm.Framework.Portfolio;
|
|
using QuantConnect.Interfaces;
|
|
using System;
|
|
using System.Collections.Generic;
|
|
|
|
namespace QuantConnect.Algorithm.CSharp
|
|
{
|
|
/// <summary>
|
|
/// Regression algorithm asserting we can specify a custom portfolio optimizer with a MeanVarianceOptimizationPortfolioConstructionModel
|
|
/// </summary>
|
|
public class CustomPortfolioOptimizerRegressionAlgorithm : MeanVarianceOptimizationFrameworkAlgorithm, IRegressionAlgorithmDefinition
|
|
{
|
|
public override void Initialize()
|
|
{
|
|
base.Initialize();
|
|
SetPortfolioConstruction(new MeanVarianceOptimizationPortfolioConstructionModel(optimizer: new CustomPortfolioOptimizer()));
|
|
}
|
|
|
|
private class CustomPortfolioOptimizer : IPortfolioOptimizer
|
|
{
|
|
public double[] Optimize(double[,] historicalReturns, double[] expectedReturns = null, double[,] covariance = null)
|
|
{
|
|
var result = new double[historicalReturns.GetLength(0)];
|
|
Array.Fill(result, 0.5);
|
|
return result;
|
|
}
|
|
}
|
|
|
|
/// <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", "13"},
|
|
{"Average Win", "0%"},
|
|
{"Average Loss", "-0.14%"},
|
|
{"Compounding Annual Return", "773.203%"},
|
|
{"Drawdown", "3.300%"},
|
|
{"Expectancy", "-1"},
|
|
{"Net Profit", "3.013%"},
|
|
{"Sharpe Ratio", "12.437"},
|
|
{"Probabilistic Sharpe Ratio", "62.198%"},
|
|
{"Loss Rate", "100%"},
|
|
{"Win Rate", "0%"},
|
|
{"Profit-Loss Ratio", "0"},
|
|
{"Alpha", "1.941"},
|
|
{"Beta", "2.094"},
|
|
{"Annual Standard Deviation", "0.49"},
|
|
{"Annual Variance", "0.24"},
|
|
{"Information Ratio", "14.343"},
|
|
{"Tracking Error", "0.287"},
|
|
{"Treynor Ratio", "2.91"},
|
|
{"Total Fees", "$39.73"},
|
|
{"Estimated Strategy Capacity", "$3100000.00"},
|
|
{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
|
|
{"Portfolio Turnover", "52.21%"},
|
|
{"OrderListHash", "12425242f98844dc855c5c5e1dff9a6a"}
|
|
};
|
|
}
|
|
}
|