chore: import upstream snapshot with attribution
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wehub-resource-sync
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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.Data.UniverseSelection;
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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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/// Demonstration of how to chain a coarse and fine universe selection with an option chain universe selection model
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/// that will add and remove an <see cref="OptionChainUniverse"/> for each symbol selected on fine
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/// </summary>
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public class CoarseFineOptionUniverseChainRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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// initialize our changes to nothing
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private SecurityChanges _changes = SecurityChanges.None;
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private int _optionCount;
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private Symbol _lastEquityAdded;
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private Symbol _aapl;
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private Symbol _twx;
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private Dictionary<string, decimal> _rawPrices = new()
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{
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{ "AOL", 70 },
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{ "AAPL", 650 }
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};
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public override void Initialize()
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{
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_twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA);
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_aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
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UniverseSettings.Resolution = Resolution.Minute;
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// Let's disable initial price seeding, the algorithm will wait until both equity
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// and options are added an have prices to do the tests, we don't want the equity
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// having prices before the options are added.
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Settings.SeedInitialPrices = false;
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SetStartDate(2014, 06, 04);
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// TWX is selected the 4th and 5th and aapl after that.
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// If the algo ends on the 6th, TWX subscriptions will not be removed before OnEndOfAlgorithm is called:
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// - 6th: AAPL is selected, TWX is removed but subscriptions are not removed because the securities are invested.
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// - TWX and its options are liquidated.
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// - 7th: Since options universe selection is daily now, TWX subscriptions are removed the next day (7th)
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SetEndDate(2014, 06, 07);
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var selectionUniverse = AddUniverse(enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl },
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enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl });
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AddUniverseOptions(selectionUniverse, universe =>
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{
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if (universe.Underlying == null)
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{
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throw new RegressionTestException("Underlying data point is null! This shouldn't happen, each OptionChainUniverse handles and should provide this");
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}
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return universe.IncludeWeeklys()
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.FrontMonth()
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.Contracts(universe.Take(5));
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});
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}
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public override void OnData(Slice slice)
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{
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// if we have no changes, do nothing
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if (_changes == SecurityChanges.None ||
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_changes.AddedSecurities.Any(security => security.Price == 0))
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{
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return;
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}
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// liquidate removed securities
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foreach (var security in _changes.RemovedSecurities)
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{
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if (security.Invested)
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{
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Liquidate(security.Symbol);
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}
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}
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foreach (var security in _changes.AddedSecurities)
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{
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if (!security.Symbol.HasUnderlying)
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{
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_lastEquityAdded = security.Symbol;
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}
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else
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{
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// options added should all match prev added security
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if (security.Symbol.Underlying != _lastEquityAdded)
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{
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throw new RegressionTestException($"Unexpected symbol added {security.Symbol}");
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}
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_optionCount++;
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}
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SetHoldings(security.Symbol, 0.05m);
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var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(security.Symbol).ToList();
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if (!config.Any())
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{
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throw new RegressionTestException($"Was expecting configurations for {security.Symbol}");
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}
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if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
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{
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throw new RegressionTestException($"Was expecting DataNormalizationMode.Raw configurations for {security.Symbol}");
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}
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if (security.Symbol.SecurityType == SecurityType.Equity)
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{
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var expectedPrice = _rawPrices[security.Symbol.ID.Symbol];
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if (Math.Abs(security.Price - expectedPrice) > expectedPrice * 0.1m)
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{
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throw new RegressionTestException($"Unexpected raw prices for symbol {security.Symbol}");
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}
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}
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}
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_changes = SecurityChanges.None;
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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_changes += changes;
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}
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public override void OnEndOfAlgorithm()
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{
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var config = SubscriptionManager.Subscriptions.ToList();
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if (config.Any(dataConfig => dataConfig.Symbol == _twx || dataConfig.Symbol.Underlying == _twx))
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{
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throw new RegressionTestException($"Was NOT expecting any configurations for {_twx} or it's options, since coarse/fine should have deselected it");
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}
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if (_optionCount == 0)
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{
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throw new RegressionTestException("Option universe chain did not add any option!");
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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, 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 long DataPoints => 18993;
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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", "13"},
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{"Average Win", "0.04%"},
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{"Average Loss", "-0.05%"},
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{"Compounding Annual Return", "-24.719%"},
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{"Drawdown", "0.500%"},
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{"Expectancy", "-0.685"},
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{"Start Equity", "100000"},
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{"End Equity", "99766.89"},
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{"Net Profit", "-0.233%"},
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{"Sharpe Ratio", "-9.078"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "83%"},
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{"Win Rate", "17%"},
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{"Profit-Loss Ratio", "0.89"},
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{"Alpha", "4.632"},
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{"Beta", "-1.524"},
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{"Annual Standard Deviation", "0.029"},
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{"Annual Variance", "0.001"},
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{"Information Ratio", "-72.647"},
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{"Tracking Error", "0.048"},
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{"Treynor Ratio", "0.172"},
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{"Total Fees", "$16.10"},
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{"Estimated Strategy Capacity", "$5000000.00"},
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{"Lowest Capacity Asset", "AOL R735QTJ8XC9X"},
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{"Portfolio Turnover", "17.64%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "228e694280e05c8aa24246a5866b5a83"}
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};
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}
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}
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