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* Implement RangeConsolidator It turned out that the behavior of RangeConsolidator was similar to ClassicRenkoConsolidator. Then, some of the ClassicRenkoConsolidator methods, were abstracted to new class called BaseTimelessConsolidator.cs, from which both RangeConsolidator and ClassicRenkoConsolidator could inherit, therefore resusing code. The following tasks were done: - Create RangeConsolidator.cs - Create RangeBar.cs - Create BaseTimelessConsolidator.cs - Create RangeConsolidatorTests.cs - Modify ClassicRenkoConsolidator.cs * Allow intermediate/Phantom RangeBar's - Enhance unit tests - Nit changes - Allow intermediate/Phantom RangeBar's on RangeConsolidator * Nit changes * Create ClassicRangeConsolidator and more changes - Add regression tests - Enhance unit tests * Address required changes * Address requested changes * Address requested changes * Add regression tests with Tick Resolution * Address required changes * Increase Range for RangeConsolidatorWithTickAlgo * Add more unit tests and solve bugs * Nit change
129 lines
4.9 KiB
C#
129 lines
4.9 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.Consolidators;
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using QuantConnect.Data.Market;
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using QuantConnect.Interfaces;
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using System;
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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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/// Example algorithm of how to use RangeConsolidator
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/// </summary>
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public class RangeConsolidatorAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private RangeBar _firstDataConsolidated;
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protected virtual int Range => 100;
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protected virtual Resolution Resolution => Resolution.Daily;
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public override void Initialize()
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{
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SetStartAndEndDates();
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AddEquity("SPY", Resolution);
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var rangeConsolidator = CreateRangeConsolidator();
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rangeConsolidator.DataConsolidated += OnDataConsolidated;
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_firstDataConsolidated = null;
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SubscriptionManager.AddConsolidator("SPY", rangeConsolidator);
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}
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public override void OnEndOfAlgorithm()
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{
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if (_firstDataConsolidated == null)
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{
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throw new Exception("The consolidator should have consolidated at least one RangeBar, but it did not consolidated any one");
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}
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}
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protected virtual void OnDataConsolidated(Object sender, RangeBar rangeBar)
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{
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if (_firstDataConsolidated == null)
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{
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_firstDataConsolidated = rangeBar;
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}
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// Log($"{rangeBar.Open} {rangeBar.High} {rangeBar.Low} {rangeBar.Close}");
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if (Math.Round(rangeBar.High - rangeBar.Low, 2) != (Range * 0.01m)) // The minimum price change for SPY is 0.01, therefore the range size of each bar equals Range * 0.01
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{
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throw new Exception($"The difference between the High and Low for all RangeBar's should be {Range * 0.01m}, but for this RangeBar was {Math.Round(rangeBar.High - rangeBar.Low), 2}");
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}
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}
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protected virtual void SetStartAndEndDates()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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}
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protected virtual RangeConsolidator CreateRangeConsolidator()
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{
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return new RangeConsolidator(Range);
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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, Language.Python };
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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 virtual long DataPoints => 48;
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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", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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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"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-8.91"},
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{"Tracking Error", "0.223"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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