chore: import upstream snapshot with attribution
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/*
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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.Data;
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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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/// This regression algorithm has two different Universe using the same Security but with
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/// different SubscriptionDataConfig. One of them will add and remove it in a toggle fashion and it should also remove the
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/// corresponding SubscriptionDataConfig.
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/// Also will test manually adding and removing a security.
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/// </summary>
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/// <meta name="tag" content="regression test" />
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public class UniverseSharingSecurityDifferentSubscriptionRequestRegressionAlgorithm
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: QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
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private readonly Symbol _aig = QuantConnect.Symbol.Create("AIG", SecurityType.Equity, Market.USA);
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private int _onDataCalls;
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private bool _alreadyRemoved;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 08); //Set Start Date
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SetEndDate(2013, 10, 11); //Set End Date
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SetCash(100000); //Set Strategy Cash
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AddEquity("SPY");
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AddEquity("AIG");
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UniverseSettings.Resolution = Resolution.Minute;
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UniverseSettings.ExtendedMarketHours = true;
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AddUniverse(SecurityType.Equity,
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"SecondUniverse",
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Resolution.Daily,
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Market.USA,
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UniverseSettings,
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time => time.Day % 2 == 0 ? new[] { "SPY" } : Enumerable.Empty<string>()
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);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice slice)
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{
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_onDataCalls++;
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if (_alreadyRemoved)
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{
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var config = SubscriptionManager
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.SubscriptionDataConfigService
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.GetSubscriptionDataConfigs(_aig);
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if (config.Any())
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{
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throw new RegressionTestException($"Unexpected SubscriptionDataConfig: {config}");
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}
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}
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if (!_alreadyRemoved)
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{
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_alreadyRemoved = true;
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var config = SubscriptionManager
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.SubscriptionDataConfigService
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.GetSubscriptionDataConfigs(_aig);
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if (!config.Any())
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{
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throw new RegressionTestException("Expecting to find a SubscriptionDataConfig for AIG");
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}
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RemoveSecurity(_aig);
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}
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var isExtendedMarketHours = SubscriptionManager
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.SubscriptionDataConfigService
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.GetSubscriptionDataConfigs(_spy)
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.IsExtendedMarketHours();
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if (Time.Day % 2 == 0)
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{
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if (!isExtendedMarketHours)
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{
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throw new RegressionTestException($"Unexpected isExtendedMarketHours value: {false}");
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}
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}
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else
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{
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if (isExtendedMarketHours)
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{
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throw new RegressionTestException($"Unexpected isExtendedMarketHours value: {true}");
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}
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (_onDataCalls == 0)
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{
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throw new RegressionTestException($"Unexpected OnData() calls count {_onDataCalls}");
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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 List<Language> Languages { get; } = new() { 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 long DataPoints => 7001;
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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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/// 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 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", "-57.739"},
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{"Tracking Error", "0.178"},
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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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