4fd16f6daf
Fixes a bug where we were using the security's data resolution to compute the insight's close time. This led a case such as insight.Period == 20days to step 20days worth of tradable minutes (assuming minute data resolution), yielding a close time that was very far in the future. We also add different means of specifying an insight's period/close time: 1. Specify insight period as a TimeSpan and we compute close time 2. Specify insight period and a resolution and bar count and we compute close time 3. Specify insight close time local directly and we compute the insight period The key here is maintaining consistency between the three different approaches which is heavily validated with the corresponding unit tests. Edits also made to trust the insight's close time as the analysis end time in the case where the analysis period == insight period (extra analysis period = 0). Given the current setup (extra analysis period == 0), this guarantees that close and analysis end times are equivalent. Regression statistics were updated and expectedly we get many more insights that have completed analysis, and as such, average scores have also changed.
179 lines
7.4 KiB
C#
179 lines
7.4 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.Algorithm.Framework;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Execution;
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using QuantConnect.Algorithm.Framework.Portfolio;
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using QuantConnect.Algorithm.Framework.Risk;
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using QuantConnect.Algorithm.Framework.Selection;
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using QuantConnect.Data.UniverseSelection;
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using QuantConnect.Interfaces;
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using QuantConnect.Orders;
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using QuantConnect.Securities;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Basic template options framework algorithm uses framework components to define an algorithm
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/// that trades options.
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/// </summary>
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public class BasicTemplateOptionsFrameworkAlgorithm : QCAlgorithmFramework, IRegressionAlgorithmDefinition
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{
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public override void Initialize()
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{
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UniverseSettings.Resolution = Resolution.Minute;
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SetStartDate(2014, 06, 05);
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SetEndDate(2014, 06, 06);
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SetCash(100000);
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// set framework models
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SetUniverseSelection(new EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(SelectOptionChainSymbols));
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SetAlpha(new ConstantOptionContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromHours(0.5)));
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SetPortfolioConstruction(new SingleSharePortfolioConstructionModel());
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SetExecution(new ImmediateExecutionModel());
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SetRiskManagement(new NullRiskManagementModel());
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}
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// option symbol universe selection function
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private static IEnumerable<Symbol> SelectOptionChainSymbols(DateTime utcTime)
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{
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var newYorkTime = utcTime.ConvertFromUtc(TimeZones.NewYork);
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if (newYorkTime.Date < new DateTime(2014, 06, 06))
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{
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yield return QuantConnect.Symbol.Create("TWX", SecurityType.Option, Market.USA, "?TWX");
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}
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if (newYorkTime.Date >= new DateTime(2014, 06, 06))
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{
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yield return QuantConnect.Symbol.Create("AAPL", SecurityType.Option, Market.USA, "?AAPL");
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}
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}
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/// <summary>
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/// Creates option chain universes that select only the earliest expiry ATM weekly put contract
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/// and runs a user defined optionChainSymbolSelector every day to enable choosing different option chains
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/// </summary>
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class EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel : OptionUniverseSelectionModel
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{
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public EarliestExpiringWeeklyAtTheMoneyPutOptionUniverseSelectionModel(Func<DateTime, IEnumerable<Symbol>> optionChainSymbolSelector)
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: base(TimeSpan.FromDays(1), optionChainSymbolSelector)
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{
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}
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/// <summary>
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/// Defines the option chain universe filter
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/// </summary>
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protected override OptionFilterUniverse Filter(OptionFilterUniverse filter)
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{
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return filter
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.Strikes(+1, +1)
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.Expiration(TimeSpan.Zero, TimeSpan.FromDays(7))
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.WeeklysOnly()
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.PutsOnly()
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.OnlyApplyFilterAtMarketOpen();
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}
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}
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/// <summary>
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/// Implementation of a constant alpha model that only emits insights for option symbols
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/// </summary>
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class ConstantOptionContractAlphaModel : ConstantAlphaModel
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{
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public ConstantOptionContractAlphaModel(InsightType type, InsightDirection direction, TimeSpan period)
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: base(type, direction, period)
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{
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}
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protected override bool ShouldEmitInsight(DateTime utcTime, Symbol symbol)
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{
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// only emit alpha for option symbols and not underlying equity symbols
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if (symbol.SecurityType != SecurityType.Option)
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{
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return false;
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}
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return base.ShouldEmitInsight(utcTime, symbol);
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}
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}
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/// <summary>
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/// Portfolio construction model that sets target quantities to 1 for up insights and -1 for down insights
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/// </summary>
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class SingleSharePortfolioConstructionModel : PortfolioConstructionModel
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{
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public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithmFramework algorithm, Insight[] insights)
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{
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foreach (var insight in insights)
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{
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yield return new PortfolioTarget(insight.Symbol, (int) insight.Direction);
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}
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}
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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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/// 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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "4"},
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{"Average Win", "0.14%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "72.420%"},
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{"Drawdown", "0.700%"},
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{"Expectancy", "0"},
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{"Net Profit", "0.274%"},
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{"Sharpe Ratio", "9.165"},
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{"Loss Rate", "0%"},
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{"Win Rate", "100%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "25.02"},
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{"Annual Standard Deviation", "0.025"},
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{"Annual Variance", "0.001"},
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{"Information Ratio", "8.886"},
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{"Tracking Error", "0.025"},
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{"Treynor Ratio", "0.009"},
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{"Total Fees", "$1.00"},
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{"Total Insights Generated", "26"},
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{"Total Insights Closed", "24"},
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{"Total Insights Analysis Completed", "24"},
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{"Long Insight Count", "26"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$28.43325"},
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{"Total Accumulated Estimated Alpha Value", "$1.89555"},
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{"Mean Population Estimated Insight Value", "$0.07898125"},
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{"Mean Population Direction", "50%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "50.0482%"},
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{"Rolling Averaged Population Magnitude", "0%"}
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};
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}
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}
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