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
101 lines
4.1 KiB
C#
101 lines
4.1 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.Data;
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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 No <see cref="IAlgorithmSettings.MinimumOrderMarginPortfolioPercentage"/>
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/// causing multiple trades to be filled, see <see cref="MinimumOrderMarginRegressionAlgorithm"/> instead
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/// </summary>
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public class NoMinimumOrderMarginRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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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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SetStartDate(2013, 10, 07); //Set Start Date
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SetEndDate(2013, 10, 11); //Set End Date
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SetCash(100000); //Set Strategy Cash
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AddEquity("SPY", Resolution.Minute);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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SetHoldings("SPY", 0.25);
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public Language[] Languages { get; } = { Language.CSharp };
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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 long DataPoints => 3943;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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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 virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "5"},
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{"Average Win", "0.00%"},
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{"Average Loss", "0.00%"},
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{"Compounding Annual Return", "38.897%"},
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{"Drawdown", "0.600%"},
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{"Expectancy", "-0.118"},
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{"Net Profit", "0.421%"},
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{"Sharpe Ratio", "5.585"},
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{"Probabilistic Sharpe Ratio", "67.350%"},
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{"Loss Rate", "50%"},
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{"Win Rate", "50%"},
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{"Profit-Loss Ratio", "0.76"},
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{"Alpha", "-0.184"},
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{"Beta", "0.249"},
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{"Annual Standard Deviation", "0.055"},
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{"Annual Variance", "0.003"},
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{"Information Ratio", "-10.01"},
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{"Tracking Error", "0.167"},
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{"Treynor Ratio", "1.243"},
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{"Total Fees", "$5.00"},
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{"Estimated Strategy Capacity", "$63000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "5.15%"},
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{"OrderListHash", "3def5351c42f7fd286cc0aafc5aff6b5"}
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};
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}
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}
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