wehub-resource-sync
127 lines
5.0 KiB
C#
127 lines
5.0 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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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period
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/// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925
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/// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630
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/// </summary>
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public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private decimal _exptectedClose = 84.09m;
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private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0);
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private Symbol _shy;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2008, 3, 7);
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SetEndDate(2008, 3, 10);
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_shy = AddEquity("SHY", Resolution.Minute).Symbol;
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// just to make debugging easier, less subscriptions
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SetBenchmark(time => 1);
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}
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public override void OnData(Slice slice)
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{
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var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime));
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if (trackingBar != null)
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{
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if (!Portfolio.Invested)
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{
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SetHoldings(_shy, 1);
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}
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if (trackingBar.Close != _exptectedClose)
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{
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throw new RegressionTestException(
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$"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}");
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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 List<Language> Languages { get; } = new() { Language.CSharp };
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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 => 1561;
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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", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "16.086%"},
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{"Drawdown", "0.100%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100148.25"},
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{"Net Profit", "0.148%"},
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{"Sharpe Ratio", "7.182"},
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{"Sortino 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", "0.014"},
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{"Annual Variance", "0"},
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{"Information Ratio", "9.758"},
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{"Tracking Error", "0.014"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$5.93"},
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{"Estimated Strategy Capacity", "$150000.00"},
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{"Lowest Capacity Asset", "SHY 2T"},
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{"Portfolio Turnover", "24.91%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "9d00701591b363edda102536ec5e75e0"}
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};
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}
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}
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