wehub-resource-sync
121 lines
4.4 KiB
C#
121 lines
4.4 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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*/
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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.Data.UniverseSelection;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm asserting that securities added via coarse selection get automatically seeded by default
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/// </summary>
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public class CoarseSelectionsAutomaticSeedRegressionAlgorithm : AutomaticSeedBaseRegressionAlgorithm
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{
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private readonly Queue<List<Symbol>> _coarseSelections = new(new[] { "AAPL", "GOOG", "AIG", "BAC", "FB", "IBM" }
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.Select(x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA))
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.BatchBy(2));
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private HashSet<Symbol> _addedSecurities = new();
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protected override bool ShouldHaveTradeData => true;
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// Daily resolution, only trade data is available
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protected override bool ShouldHaveQuoteData => false;
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protected override bool ShouldHaveOpenInterestData => false;
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public override void Initialize()
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{
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SetStartDate(2015, 01, 01);
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SetEndDate(2015, 03, 01);
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SetCash(100000);
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Settings.SeedInitialPrices = true;
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UniverseSettings.Resolution = Resolution.Daily;
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AddUniverse((coarse) =>
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{
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var selection = _coarseSelections.Dequeue();
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_coarseSelections.Enqueue(selection);
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return selection;
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});
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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base.OnSecuritiesChanged(changes);
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foreach (var addedSecurity in changes.AddedSecurities.Where(x => !x.Symbol.IsCanonical()))
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{
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_addedSecurities.Add(addedSecurity.Symbol);
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (!_coarseSelections.SelectMany(x => x).Order().SequenceEqual(_addedSecurities.Order()))
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{
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throw new RegressionTestException("Not all securities were added");
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}
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}
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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 override long DataPoints => 358;
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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 override int AlgorithmHistoryDataPoints => 390;
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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 override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "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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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino 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", "-1.066"},
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{"Tracking Error", "0.116"},
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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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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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