bfd319c91e
* OptionChain and OptionContract improvements - QCAlgorithm.AddUniverse will return the added Universe instance. - Adding new OptionChainedUniverseSelectionModel will monitor a Universe changes and will spwan new OptionChainUniverse from it's selections. Adding regression test Py/C#. - Adding new OptionContractUniverse that will own option contracts and their underlying symbol. Adding regression test - Fix double notification for security changes, bug seen in updated UniverseSelectionRegressionAlgorithm - Remove UniverseSelection special handling for Option and Future chains - Fix DataManager not removing SubscriptionDataConfigs for Subscriptions which finished before being removed from the universe - Refactor detection of user added Universe so that they do not get removed after calling the UniverseSelectionModel * Add check for option underlying price is set * Address reviews - Adding python regression algorithm for `AddOptionContractFromUniverseRegressionAlgorithm` and `AddOptionContractExpiresRegressionAlgorithm` - Rename QCAlgorithm new api method to `AddChainedOptionUniverse` * Fix universe refresh bug - Fix bug where a universe selection refresh would cause option or future chain universes from being removed. Adding regression algorithm reproducing the issue. * Rename new option universe Algorithm API method - Rename new option universe Algorith API method from AddChainedOptionUniverse to AddUniverseOptions - Rebase and update regression test order hash because of option expiration message changed
165 lines
6.9 KiB
C#
165 lines
6.9 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.Linq;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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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 and wait till it expires
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/// later will liquidate the resulting equity position and assert both option and underlying get removed
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/// </summary>
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public class AddOptionContractExpiresRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private DateTime _expiration = new DateTime(2014, 06, 21);
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private Symbol _option;
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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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SetStartDate(2014, 06, 05);
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SetEndDate(2014, 06, 30);
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_twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA);
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AddUniverse("my-daily-universe-name", time => new List<string> { "AAPL" });
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}
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public override void OnData(Slice data)
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{
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if (_option == null)
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{
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var option = OptionChainProvider.GetOptionContractList(_twx, Time)
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.OrderBy(symbol => symbol.ID.Symbol)
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.FirstOrDefault(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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if (option != null)
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{
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_option = AddOptionContract(option).Symbol;
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}
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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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foreach (var symbol in new [] { _option, _option.Underlying })
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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 Exception($"Was expecting configurations for {symbol}");
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}
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if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
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{
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throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
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}
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}
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}
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if (Time.Date > _expiration)
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{
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if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_option).Any())
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{
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throw new Exception($"Unexpected configurations for {_option} after it has been delisted");
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}
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if (Securities[_twx].Invested)
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{
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if (!SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
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{
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throw new Exception($"Was expecting configurations for {_twx}");
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}
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// first we liquidate the option exercised position
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Liquidate(_twx);
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}
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}
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else if (Time.Date > _expiration && !Securities[_twx].Invested)
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{
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if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
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{
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throw new Exception($"Unexpected configurations for {_twx} after it has been liquidated");
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}
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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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
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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 Trades", "3"},
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{"Average Win", "2.94%"},
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{"Average Loss", "-2.98%"},
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{"Compounding Annual Return", "-1.749%"},
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{"Drawdown", "0.200%"},
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{"Expectancy", "-0.006"},
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{"Net Profit", "-0.124%"},
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{"Sharpe Ratio", "3.589"},
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{"Probabilistic Sharpe Ratio", "90.473%"},
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{"Loss Rate", "50%"},
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{"Win Rate", "50%"},
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{"Profit-Loss Ratio", "0.99"},
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{"Alpha", "0.007"},
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{"Beta", "-0.001"},
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{"Annual Standard Deviation", "0.002"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-2.913"},
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{"Tracking Error", "0.057"},
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{"Treynor Ratio", "-4.947"},
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{"Total Fees", "$2.00"},
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{"Fitness Score", "0.001"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-0.946"},
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{"Return Over Maximum Drawdown", "-10.498"},
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{"Portfolio Turnover", "0.007"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "1123164511"}
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};
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}
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}
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