wehub-resource-sync
101 lines
4.2 KiB
C#
101 lines
4.2 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 System.Linq;
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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.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Abstract regression framework algorithm for multiple framework regression tests
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/// </summary>
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public abstract class BaseFrameworkRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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public override void Initialize()
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{
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SetStartDate(2014, 6, 1);
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SetEndDate(2014, 6, 30);
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UniverseSettings.Resolution = Resolution.Hour;
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UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
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var symbols = new[] { "AAPL", "AIG", "BAC", "SPY" }
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.Select(ticker => QuantConnect.Symbol.Create(ticker, SecurityType.Equity, Market.USA))
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.ToList();
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// Manually add AAPL and AIG when the algorithm starts
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SetUniverseSelection(new ManualUniverseSelectionModel(symbols.Take(2)));
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// At midnight, add all securities every day except on the last data
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// With this procedure, the Alpha Model will experience multiple universe changes
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AddUniverseSelection(new ScheduledUniverseSelectionModel(
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DateRules.EveryDay(), TimeRules.Midnight,
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dt => dt < EndDate.AddDays(-1) ? symbols : Enumerable.Empty<Symbol>()));
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SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(31), 0.025, null));
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SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
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SetExecution(new ImmediateExecutionModel());
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SetRiskManagement(new NullRiskManagementModel());
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}
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public override void OnEndOfAlgorithm()
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{
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// The base implementation checks for active insights
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var insightsCount = Insights.GetInsights(insight => insight.IsActive(UtcTime)).Count;
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if (insightsCount != 0)
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{
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throw new RegressionTestException($"The number of active insights should be 0. Actual: {insightsCount}");
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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 virtual List<Language> Languages { get; } = new() { 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 => 764;
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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 virtual int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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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 abstract Dictionary<string, string> ExpectedStatistics { get; }
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}
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}
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