Martin-Molinero
cb326788b3
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* Filter out small orders based on Setting - BuyingPowerModel will filter out small orders based on algorithm setting, a % of PTV, instead of hard coded 1 share value. Addin unit and regression tests - Updating regression algorithms to use new setting, reduce order trades * Update regression algorithms
86 lines
3.7 KiB
C#
86 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 QuantConnect.Interfaces;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm testing the effect of <see cref="IAlgorithmSettings.MinimumOrderMarginPortfolioPercentage"/>.
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/// Setting a minimum order size of 1% of portfolio reduces order count significantly
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/// </summary>
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public class MinimumOrderMarginRegressionAlgorithm : NoMinimumOrderMarginRegressionAlgorithm
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{
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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base.Initialize();
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Settings.MinimumOrderMarginPortfolioPercentage = 0.01m;
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}
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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 Dictionary<string, string>
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{
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{"Total Trades", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "39.100%"},
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{"Drawdown", "0.500%"},
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{"Expectancy", "0"},
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{"Net Profit", "0.423%"},
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{"Sharpe Ratio", "5.634"},
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{"Probabilistic Sharpe Ratio", "67.498%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.181"},
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{"Beta", "0.248"},
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{"Annual Standard Deviation", "0.055"},
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{"Annual Variance", "0.003"},
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{"Information Ratio", "-9.989"},
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{"Tracking Error", "0.167"},
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{"Treynor Ratio", "1.254"},
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{"Total Fees", "$1.00"},
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{"Estimated Strategy Capacity", "$150000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Fitness Score", "0.062"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "71.484"},
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{"Portfolio Turnover", "0.062"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "86f2942f2fcfc7ee9e44521f86adc07d"}
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};
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}
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}
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