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;
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using System.Collections.Generic;
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using QuantConnect.Interfaces;
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using QuantConnect.Util;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Algorithm illustrating how to get a security's industry-standard identifier from its <see cref="Symbol"/>
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/// </summary>
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public class IndustryStandardSecurityIdentifiersRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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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, 05);
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var equity = AddEquity("AAPL").Symbol;
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var cusip = equity.CUSIP;
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var compositeFigi = equity.CompositeFIGI;
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var sedol = equity.SEDOL;
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var isin = equity.ISIN;
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var cik = equity.CIK;
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CheckSymbolRepresentation(cusip, "CUSIP");
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CheckSymbolRepresentation(compositeFigi, "Composite FIGI");
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CheckSymbolRepresentation(sedol, "SEDOL");
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CheckSymbolRepresentation(isin, "ISIN");
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CheckSymbolRepresentation($"{cik}", "CIK");
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// Check Symbol API vs QCAlgorithm API
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CheckAPIsSymbolRepresentations(cusip, CUSIP(equity), "CUSIP");
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CheckAPIsSymbolRepresentations(compositeFigi, CompositeFIGI(equity), "Composite FIGI");
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CheckAPIsSymbolRepresentations(sedol, SEDOL(equity), "SEDOL");
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CheckAPIsSymbolRepresentations(isin, ISIN(equity), "ISIN");
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CheckAPIsSymbolRepresentations($"{cik}", $"{CIK(equity)}", "CIK");
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Log($"\nAAPL CUSIP: {cusip}" +
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$"\nAAPL Composite FIGI: {compositeFigi}" +
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$"\nAAPL SEDOL: {sedol}" +
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$"\nAAPL ISIN: {isin}" +
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$"\nAAPL CIK: {cik}");
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}
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private static void CheckSymbolRepresentation(string symbol, string standard)
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{
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if (symbol.IsNullOrEmpty())
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{
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throw new RegressionTestException($"{standard} symbol representation is null or empty");
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}
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}
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private static void CheckAPIsSymbolRepresentations(string symbolApiSymbol, string algorithmApiSymbol, string standard)
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{
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if (symbolApiSymbol != algorithmApiSymbol)
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{
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throw new RegressionTestException($@"Symbol API {standard} symbol representation ({symbolApiSymbol}) does not match QCAlgorithm API {
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standard} symbol representation ({algorithmApiSymbol})");
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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, 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 => 795;
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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", "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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