Colton Sellers
5b10b3b509
* Add futures regression reproducing the issue * Cleanup futures regression * Add Options regression * Add IRegressionAlgorithmDefinition * Add IRegressionAlgorithmDefinition * Adjust regressions to compare to expiration date; delisting time is not always correct * Refactor subscription enumerator filtering of AuxData to top of the stack * Update broken tests to reflect the split/dividends/delisting subscriptions * Update regression statistics because of Delisting EOD instead of at time * Let custom data configurations bypass filter * Adjust expected count, now that we are letting aux data through to history requests * another small adjustment * Use ExpectedBarCount in error message * Add filter test for both cases * Add some clarifying comments * Verify we did recieve data in the regressions * Make _shouldEmitAuxiliaryData private readonly * Filter out aux data for history requests * Remove option to not include aux data in subscriptions * Refactor filtering to be more explicit for each piece of data; fixes universe selection aux data * Cleanup comments after removed var * Refactor order of filtering for performance reasons.
111 lines
4.0 KiB
C#
111 lines
4.0 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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using QuantConnect.Securities;
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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 if expired futures contract chains are making their
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/// way into the timeslices being delivered to OnData()
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/// </summary>
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public class FuturesExpiredContractRegression : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private bool _receivedData;
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/// <summary>
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/// Initializes the algorithm state.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 1);
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SetEndDate(2013, 12, 23);
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SetCash(1000000);
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// Subscribe to futures ES
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var future = AddFuture(Futures.Indices.SP500EMini, Resolution.Minute, Market.CME, false);
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future.SetFilter(TimeSpan.FromDays(0), TimeSpan.FromDays(90));
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}
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public override void OnData(Slice data)
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{
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foreach (var chain in data.FutureChains)
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{
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_receivedData = true;
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foreach (var contract in chain.Value.OrderBy(x => x.Expiry))
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{
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if (contract.Expiry.Date < Time.Date)
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{
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throw new Exception($"Received expired contract {contract} expired: {contract.Expiry} current time: {Time}");
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}
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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 (!_receivedData)
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{
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throw new Exception("No Futures chains were received in this regression");
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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", "-3.464"},
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{"Tracking Error", "0.097"},
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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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{"Fitness Score", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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} |