43a540cbb1
* Filter values that are before subscription start time; also adjust starttime for OpenInterest * Use data EndTime for comparison * Allow Auxiliary data through * Fix OpenInterest DataReader Logic * Add regression * Address review * Ignore open interest for time slice - TimeSliceFactory will directly ignore open interest for determining if the slice has data or not. Open interest will still be available through the Tick collection. Reverting some of the previous commits changes since they are no longer required. - HistoryRequests and SubscriptionRequest will use AlwaysOpen exchange for open interest requests. Adding unit test reproducing issue - Adding `BaseDataRequest` to avoid duplication logic. * Make OpenInterest an internal feed and ignored by default in history - Adding unit tests * Revert SubscriptionFilterEnumerator Start time addition Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
135 lines
5.2 KiB
C#
135 lines
5.2 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.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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/// Regression algorithm to test time slice irregularities when adding options
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/// after algorithm initialization
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/// </summary>
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public class OptionTimeSliceRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _symbol;
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private Symbol _optionSymbol;
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private DateTime _lastSliceTime = DateTime.MinValue;
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public override void Initialize()
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{
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SetStartDate(2014, 6, 6);
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SetEndDate(2014, 6, 9);
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var aapl = AddEquity("aapl", Resolution.Minute);
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aapl.SetDataNormalizationMode(DataNormalizationMode.Raw);
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_symbol = aapl.Symbol;
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}
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public override void OnData(Slice data)
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{
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// Compare our previous slice time to this slice
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// Because of issues with Delisting data we have to let Auxiliary data pass through GH #5207
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if (Time.Ticks - _lastSliceTime.Ticks < 1000 && data.Values.Any(x => x.DataType != MarketDataType.Auxiliary))
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{
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throw new Exception($"Emitted two slices within 1000 ticks of each other.");
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}
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// Store our slice time
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_lastSliceTime = Time;
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var underlyingPrice = Securities[_symbol].Price;
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var contractSymbol = OptionChainProvider.GetOptionContractList(_symbol, Time)
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.Where(x => x.ID.StrikePrice - underlyingPrice > 0)
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.OrderBy(x => x.ID.Date)
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.FirstOrDefault();
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if (contractSymbol != null)
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{
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_optionSymbol = AddOptionContract(contractSymbol).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 (_optionSymbol == null)
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{
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throw new Exception("No option symbol was added!");
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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 };
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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", "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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{"Net Profit", "0%"},
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{"Sharpe 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", "-11.978"},
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{"Tracking Error", "0.011"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Fitness Score", "0"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
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{"Portfolio Turnover", "0"},
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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", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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