Martin-Molinero
410956bf9f
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* 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
92 lines
3.7 KiB
C#
92 lines
3.7 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Algorithm.Framework.Risk;
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using QuantConnect.Algorithm.Framework.Selection;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Show example of how to use the <see cref="MaximumSectorExposureRiskManagementModel"/> Risk Management Model
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/// </summary>
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public class MaximumSectorExposureRiskManagementModelFrameworkRegressionAlgorithm : BaseFrameworkRegressionAlgorithm
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{
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public override void Initialize()
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{
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base.Initialize();
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// Set requested data resolution
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UniverseSettings.Resolution = Resolution.Daily;
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SetStartDate(2014, 2, 1); //Set Start Date
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SetEndDate(2014, 5, 1); //Set End Date
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// set algorithm framework models
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var tickers = new string[] { "AAPL", "MSFT", "GOOG", "AIG", "BAC" };
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SetUniverseSelection(new FineFundamentalUniverseSelectionModel(
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coarse => coarse.Where(x => tickers.Contains(x.Symbol.Value)).Select(x => x.Symbol),
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fine => fine.Select(x => x.Symbol)
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));
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// define risk management model such that maximum weight of a single sector be 10%
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// Number of of trades changed from 34 to 30 when using the MaximumSectorExposureRiskManagementModel
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SetRiskManagement(new MaximumSectorExposureRiskManagementModel(0.1m));
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}
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public override void OnEndOfAlgorithm()
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{
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// The MaximumSectorExposureRiskManagementModel does not expire insights
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}
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public override long DataPoints => 544;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public override Dictionary<string, string> ExpectedStatistics => new()
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{
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{"Total Trades", "17"},
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{"Average Win", "0.01%"},
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{"Average Loss", "-0.15%"},
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{"Compounding Annual Return", "-3.485%"},
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{"Drawdown", "1.300%"},
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{"Expectancy", "-0.739"},
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{"Net Profit", "-0.871%"},
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{"Sharpe Ratio", "-1.519"},
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{"Probabilistic Sharpe Ratio", "3.828%"},
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{"Loss Rate", "75%"},
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{"Win Rate", "25%"},
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{"Profit-Loss Ratio", "0.05"},
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{"Alpha", "-0.036"},
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{"Beta", "0.06"},
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{"Annual Standard Deviation", "0.016"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-2.291"},
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{"Tracking Error", "0.093"},
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{"Treynor Ratio", "-0.406"},
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{"Total Fees", "$20.85"},
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{"Estimated Strategy Capacity", "$63000000.00"},
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{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.80%"},
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{"OrderListHash", "81128ea61f4a90afe5b9eb8a66a5bb11"}
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};
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}
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}
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