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* Update CME futures market hours * Update regression algorithms stats * Update regression algorithms stats * Update expected values in unit tests * Additional mhdb updates * Update mhdb
178 lines
7.3 KiB
C#
178 lines
7.3 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;
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using System.Collections.Generic;
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using QuantConnect.Interfaces;
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using QuantConnect.Data;
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using QuantConnect.Data.Consolidators;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm using a consolidator to check GetNextMarketClose() and GetNextMarketOpen()
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/// are returning the correct market close and open times
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/// </summary>
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public class FutureMarketOpenConsolidatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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protected virtual bool ExtendedMarketHours => false;
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protected virtual List<DateTime> ExpectedOpens => new List<DateTime>()
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{
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new DateTime(2013, 10, 07, 9, 30, 0),
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new DateTime(2013, 10, 08, 9, 30, 0),
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new DateTime(2013, 10, 09, 9, 30, 0),
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new DateTime(2013, 10, 10, 9, 30, 0),
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new DateTime(2013, 10, 11, 9, 30, 0),
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new DateTime(2013, 10, 14, 9, 30, 0),
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new DateTime(2013, 10, 14, 9, 30, 0),
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};
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protected virtual List<DateTime> ExpectedCloses => new List<DateTime>()
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{
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new DateTime(2013, 10, 07, 17, 0, 0),
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new DateTime(2013, 10, 08, 17, 0, 0),
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new DateTime(2013, 10, 09, 17, 0, 0),
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new DateTime(2013, 10, 10, 17, 0, 0),
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new DateTime(2013, 10, 11, 17, 0, 0),
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new DateTime(2013, 10, 14, 17, 0, 0),
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new DateTime(2013, 10, 14, 17, 0, 0),
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};
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private Queue<DateTime> _expectedOpensQueue;
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private Queue<DateTime> _expectedClosesQueue;
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public override void Initialize()
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{
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SetStartDate(2013, 10, 06);
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SetEndDate(2013, 10, 14);
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var es = AddSecurity(SecurityType.Future, "ES", extendedMarketHours: ExtendedMarketHours);
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_expectedOpensQueue = new Queue<DateTime>(ExpectedOpens);
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_expectedClosesQueue = new Queue<DateTime>(ExpectedCloses);
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Consolidate<BaseData>(es.Symbol, dataTime =>
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{
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var start = es.Exchange.Hours.GetPreviousMarketOpen(dataTime, ExtendedMarketHours);
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var end = es.Exchange.Hours.GetNextMarketClose(start, ExtendedMarketHours);
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if (ExtendedMarketHours)
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{
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// market might open at 16:30 and close again at 17:00 but we are not interested in using the close so we skip it here
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while (end.Date == start.Date)
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{
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end = es.Exchange.Hours.GetNextMarketClose(end, ExtendedMarketHours);
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}
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} else
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{
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// Let's not consider regular market gaps like when market closes at 16:15 and opens again at 16:30
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while (true)
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{
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var potentialEnd = es.Exchange.Hours.GetNextMarketClose(end, ExtendedMarketHours);
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if (potentialEnd.Date != end.Date)
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{
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break;
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}
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end = potentialEnd;
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}
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}
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var period = end - start;
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// based on the given data time we return the start time of it's bar and the expected period size
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return new CalendarInfo(start, period);
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}, bar => Assert(bar));
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}
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public void Assert(BaseData bar)
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{
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var open = _expectedOpensQueue.Dequeue();
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var close = _expectedClosesQueue.Dequeue();
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if (open != bar.Time || close != bar.EndTime)
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{
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throw new Exception($"Bar span was expected to be from {open} to {close}. " +
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$"\n But was from {bar.Time} to {bar.EndTime}.");
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}
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Logging.Log.Debug($"Consolidator Event span. Start {bar.Time} End : {bar.EndTime}");
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}
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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 virtual 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 virtual long DataPoints => 29802;
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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", "-3.108"},
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{"Tracking Error", "0.163"},
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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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{"Fitness Score", "0"},
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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", "79228162514264337593543950335"},
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{"Portfolio Turnover", "0"},
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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", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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