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 QuantConnect.Data;
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using QuantConnect.Data.UniverseSelection;
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using QuantConnect.Interfaces;
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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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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// We add an option contract using <see cref="QCAlgorithm.AddOptionContract"/> and place a trade, the underlying
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/// gets deselected from the universe selection but should still be present since we manually added the option contract.
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/// Later we call <see cref="QCAlgorithm.RemoveOptionContract"/> and expect both option and underlying to be removed.
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/// </summary>
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public class AddOptionContractFromUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private DateTime _expiration = new DateTime(2014, 06, 21);
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private SecurityChanges _securityChanges = SecurityChanges.None;
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private Symbol _option;
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private Symbol _aapl;
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private Symbol _twx;
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private bool _traded;
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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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UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
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SetStartDate(2014, 06, 05);
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SetEndDate(2014, 06, 09);
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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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}
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public override void OnData(Slice slice)
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{
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if (_option != null && Securities[_option].Price != 0 && !_traded)
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{
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_traded = true;
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Buy(_option, 1);
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}
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if (Time.Date > new DateTime(2014, 6, 5))
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{
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if (Time < new DateTime(2014, 6, 6, 14, 0, 0))
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{
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var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx);
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// assert underlying still there after the universe selection removed it, still used by the manually added option contract
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if (!configs.Any())
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{
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throw new RegressionTestException($"Was expecting configurations for {_twx}" +
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$" even after it has been deselected from coarse universe because we still have the option contract.");
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}
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}
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else if (Time == new DateTime(2014, 6, 6, 14, 0, 0))
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{
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// liquidate & remove the option
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RemoveOptionContract(_option);
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}
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// assert underlying was finally removed
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else if(Time > new DateTime(2014, 6, 6, 14, 0, 0))
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{
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foreach (var symbol in new[] { _option, _option.Underlying })
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{
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var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol);
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if (configs.Any())
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{
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throw new RegressionTestException($"Unexpected configuration for {symbol} after it has been deselected from coarse universe and option contract is removed.");
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}
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}
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}
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}
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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if (_securityChanges.RemovedSecurities.Intersect(changes.RemovedSecurities).Any())
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{
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throw new RegressionTestException($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
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}
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if (_securityChanges.AddedSecurities.Intersect(changes.AddedSecurities).Any())
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{
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throw new RegressionTestException($"SecurityChanges.AddedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
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}
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// keep track of all removed and added securities
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_securityChanges += changes;
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if (changes.AddedSecurities.Any(security => security.Symbol.SecurityType == SecurityType.Option))
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{
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return;
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}
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foreach (var addedSecurity in changes.AddedSecurities)
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{
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var option = OptionChain(addedSecurity.Symbol)
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.OrderBy(contractData => contractData.ID.Symbol)
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.First(optionContract => optionContract.ID.Date == _expiration
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&& optionContract.ID.OptionRight == OptionRight.Call
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&& optionContract.ID.OptionStyle == OptionStyle.American);
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AddOptionContract(option);
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foreach (var symbol in new[] { option.Symbol, option.UnderlyingSymbol })
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{
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var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
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if (!config.Any())
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{
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throw new RegressionTestException($"Was expecting configurations for {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($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
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}
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}
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// just keep the first we got
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if (_option == null)
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{
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_option = option;
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}
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (SubscriptionManager.Subscriptions.Any(dataConfig => dataConfig.Symbol == _twx || dataConfig.Symbol.Underlying == _twx))
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{
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throw new RegressionTestException($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract");
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}
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if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol != _aapl))
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{
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throw new RegressionTestException($"Was expecting configurations for {_aapl}");
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}
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if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol.Underlying != _aapl))
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{
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throw new RegressionTestException($"Was expecting options configurations for {_aapl}");
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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 => 5800;
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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 => 2;
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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", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.23%"},
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{"Compounding Annual Return", "-15.596%"},
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{"Drawdown", "0.200%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "99768"},
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{"Net Profit", "-0.232%"},
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{"Sharpe Ratio", "-8.903"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0.024%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0.015"},
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{"Beta", "-0.171"},
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{"Annual Standard Deviation", "0.006"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-11.082"},
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{"Tracking Error", "0.043"},
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{"Treynor Ratio", "0.335"},
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{"Total Fees", "$2.00"},
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{"Estimated Strategy Capacity", "$2800000.00"},
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{"Lowest Capacity Asset", "AOL VRKS95ENPM9Y|AOL R735QTJ8XC9X"},
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{"Portfolio Turnover", "1.14%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "e33b98d8e94ed92d0441fc6fe0d461fb"}
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};
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}
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}
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