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 System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Indicators;
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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 asserting the behavior of the indicator history api
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/// </summary>
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public class IndicatorHistoryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _symbol;
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/// <summary>
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/// Initialize the data and resolution you require for your strategy
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 1, 1);
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SetEndDate(2014, 12, 31);
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_symbol = AddEquity("SPY", Resolution.Daily).Symbol;
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}
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public void OnData(Slice slice)
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{
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var bollingerBands = new BollingerBands("BB", 20, 2.0m, MovingAverageType.Simple);
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if (bollingerBands.Window.IsReady)
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{
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throw new RegressionTestException("Unexpected ready bollinger bands state");
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}
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var indicatorHistory = IndicatorHistory(bollingerBands, _symbol, 50);
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if (!bollingerBands.Window.IsReady)
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{
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throw new RegressionTestException("Unexpected not ready bollinger bands state");
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}
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// we ask for 50 data points
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if (indicatorHistory.Count != 50)
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{
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throw new RegressionTestException($"Unexpected indicators values {indicatorHistory.Count}");
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}
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foreach (var indicatorDataPoints in indicatorHistory)
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{
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var upperBand = ((dynamic)indicatorDataPoints).UpperBand;
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Debug($"BB @{indicatorDataPoints.Current}: middleband: {indicatorDataPoints["middleband"]} upperBand {upperBand}");
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if (indicatorDataPoints == 0)
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{
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throw new RegressionTestException($"Unexpected indicators point {indicatorDataPoints}");
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}
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}
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var currentValues = indicatorHistory.Current;
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if (currentValues.Count != 50 || currentValues.Any(x => x.Value == 0))
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{
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throw new RegressionTestException($"Unexpected indicators current values {currentValues.Count}");
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}
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var upperBandPoints = indicatorHistory["UpperBand"];
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if (upperBandPoints.Count != 50 || upperBandPoints.Any(x => x.Value == 0))
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{
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throw new RegressionTestException($"Unexpected indicators upperBandPoints values {upperBandPoints.Count}");
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}
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// We are done now!
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Quit();
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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 => 16;
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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 => 69;
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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", "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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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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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"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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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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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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