Martin-Molinero
9cb2452025
* Oanda default forex Market - Use Oanda as default forex Market since it has more pairs. - Remove FXCM data add Oanda equivalente data. - Update unit and regression tests * Address reviews - Revert FXCM data removal - Remove unrequired commented code * Fix rebase
271 lines
11 KiB
C#
271 lines
11 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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*/
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using System;
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using System.Collections.Generic;
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using Newtonsoft.Json;
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using NUnit.Framework;
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using QuantConnect.Algorithm.CSharp;
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using QuantConnect.Configuration;
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using QuantConnect.Interfaces;
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using QuantConnect.Logging;
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using QuantConnect.Packets;
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namespace QuantConnect.Tests.Common.Packets
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{
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[TestFixture]
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public class BacktestNodePacketTests
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{
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[SetUp]
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public void SetUp()
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{
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Log.DebuggingEnabled = false;
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}
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[TearDown]
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public void TearDown()
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{
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// clear the config
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Config.Reset();
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}
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[Test]
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public void JobDatesAreRespected()
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{
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var parameter = new RegressionTests.AlgorithmStatisticsTestParameters(nameof(BasicTemplateDailyAlgorithm),
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new Dictionary<string, string> {
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{ "Total Trades", "1" },
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{"Average Win", "0%"},
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{ "Average Loss", "0%"},
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{ "Compounding Annual Return", "17.560%"},
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{ "Drawdown", "30.300%"},
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{ "Expectancy", "0"},
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{ "Net Profit", "38.142%"},
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{ "Sharpe Ratio", "0.682"},
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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", "0.209"},
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{ "Beta", "-0.136"},
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{ "Annual Standard Deviation", "0.272"},
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{ "Annual Variance", "0.074"},
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{ "Information Ratio", "0.018"},
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{ "Tracking Error", "0.422"},
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{ "Treynor Ratio", "-1.363"},
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{ "Total Fees", "$6.62"} },
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Language.CSharp,
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AlgorithmStatus.Completed);
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AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
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parameter.Statistics,
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parameter.AlphaStatistics,
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parameter.Language,
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parameter.ExpectedFinalStatus,
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startDate: new DateTime(2008, 10, 10),
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endDate: new DateTime(2010, 10, 10));
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}
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[Test]
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public void JobDatesAreRespectedByAddUniverseAtInitialize()
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{
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var parameter = new RegressionTests.AlgorithmStatisticsTestParameters(nameof(CoarseFundamentalTop3Algorithm),
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new Dictionary<string, string> {
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{ "Total Trades", "3" },
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{"Average Win", "0%"},
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{ "Average Loss", "0%"},
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{ "Compounding Annual Return", "-40.620%"},
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{ "Drawdown", "0.300%"},
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{ "Expectancy", "0"},
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{ "Net Profit", "-0.285%"},
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{ "Sharpe Ratio", "-9.435"},
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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", "-0.802"},
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{ "Beta", "0.569"},
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{ "Annual Standard Deviation", "0.032"},
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{ "Annual Variance", "0.001"},
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{ "Information Ratio", "-48.662"},
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{ "Tracking Error", "0.024"},
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{ "Treynor Ratio", "-0.531"},
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{ "Total Fees", "$3.00"} },
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Language.CSharp,
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AlgorithmStatus.Completed);
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AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
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parameter.Statistics,
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parameter.AlphaStatistics,
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parameter.Language,
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parameter.ExpectedFinalStatus,
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startDate: new DateTime(2014, 03, 24),
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endDate: new DateTime(2014, 03, 25));
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}
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[Test, Parallelizable(ParallelScope.Self)]
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public void RoundTripNullJobDates()
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{
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var job = new BacktestNodePacket(1, 2, "3", null, 9m, $"{nameof(BacktestNodePacketTests)}.Pepe");
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var serialized = JsonConvert.SerializeObject(job);
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var job2 = JsonConvert.DeserializeObject<BacktestNodePacket>(serialized);
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Assert.AreEqual(job.BacktestId, job2.BacktestId);
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Assert.AreEqual(job.Name, job2.Name);
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Assert.IsNull(job.PeriodFinish);
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Assert.IsNull(job.PeriodStart);
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Assert.AreEqual(job.PeriodFinish, job2.PeriodFinish);
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Assert.AreEqual(job.PeriodStart, job2.PeriodStart);
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Assert.AreEqual(job.ProjectId, job2.ProjectId);
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Assert.AreEqual(job.SessionId, job2.SessionId);
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Assert.AreEqual(job.Language, job2.Language);
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}
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[Test, Parallelizable(ParallelScope.Self)]
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public void RoundTripWithJobDates()
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{
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var job = new BacktestNodePacket(1, 2, "3", null, 9m, $"{nameof(BacktestNodePacketTests)}.Pepe");
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job.PeriodStart = new DateTime(2019, 1, 1);
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job.PeriodFinish = new DateTime(2020, 1, 1);
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var serialized = JsonConvert.SerializeObject(job);
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var job2 = JsonConvert.DeserializeObject<BacktestNodePacket>(serialized);
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Assert.AreEqual(job.PeriodStart, job2.PeriodStart);
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Assert.AreEqual(job.PeriodFinish, job2.PeriodFinish);
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}
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[Test, Parallelizable(ParallelScope.Self)]
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public void RoundTripWithInitialCashAmount()
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{
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var job = new BacktestNodePacket(1, 2, "3", null, 9m, $"{nameof(BacktestNodePacketTests)}.Pepe");
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Assert.AreEqual(9m, job.CashAmount.Value.Amount);
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Assert.AreEqual(Currencies.USD, job.CashAmount.Value.Currency);
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var serialized = JsonConvert.SerializeObject(job);
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var job2 = JsonConvert.DeserializeObject<BacktestNodePacket>(serialized);
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Assert.AreEqual(job.CashAmount, job2.CashAmount);
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}
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[Test, Parallelizable(ParallelScope.Self)]
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public void RoundTripWithNullInitialCashAmount()
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{
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var job = new BacktestNodePacket(1, 2, "3", null, $"{nameof(BacktestNodePacketTests)}.Pepe");
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Assert.IsNull(job.CashAmount);
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var serialized = JsonConvert.SerializeObject(job);
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var job2 = JsonConvert.DeserializeObject<BacktestNodePacket>(serialized);
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Assert.AreEqual(job.CashAmount, job2.CashAmount);
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}
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[Test]
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public void InitialCashAmountIsRespected()
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{
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var parameter = new RegressionTests.AlgorithmStatisticsTestParameters(nameof(BasicTemplateDailyAlgorithm),
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new Dictionary<string, string> {
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{"Total Trades", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "246.584%"},
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{"Drawdown", "1.100%"},
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{"Expectancy", "0"},
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{"Net Profit", "3.464%"},
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{"Sharpe Ratio", "10.117"},
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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", "1.939"},
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{"Beta", "-0.12"},
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{"Annual Standard Deviation", "0.161"},
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{"Annual Variance", "0.026"},
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{"Information Ratio", "-4.537"},
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{"Tracking Error", "0.221"},
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{"Treynor Ratio", "-13.579"},
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{"Total Fees", "$32.60"} // 10x times more than original BasicTemplateDailyAlgorithm
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},
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Language.CSharp,
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AlgorithmStatus.Completed);
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AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
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parameter.Statistics,
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parameter.AlphaStatistics,
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parameter.Language,
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parameter.ExpectedFinalStatus,
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initialCash: 1000000); // 1M vs 100K that is set in BasicTemplateDailyAlgorithm (10x)
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}
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[Test]
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public void ClearsOtherCashAmounts()
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{
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var parameter = new RegressionTests.AlgorithmStatisticsTestParameters(nameof(TestInitialCashAmountAlgorithm),
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new Dictionary<string, string> {
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{"Total Trades", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "214.981%"},
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{"Drawdown", "1.100%"},
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{"Expectancy", "0"},
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{"Net Profit", "3.464%"},
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{"Sharpe Ratio", "9.066"},
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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", "1.572"},
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{"Beta", "-0.086"},
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{"Annual Standard Deviation", "0.153"},
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{"Annual Variance", "0.023"},
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{"Information Ratio", "-3.867"},
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{"Tracking Error", "0.208"},
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{"Treynor Ratio", "-16.079"},
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{"Total Fees", "$32.60"} // 10x times more than original BasicTemplateDailyAlgorithm
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},
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Language.CSharp,
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AlgorithmStatus.Completed);
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AlgorithmRunner.RunLocalBacktest(parameter.Algorithm,
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parameter.Statistics,
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parameter.AlphaStatistics,
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parameter.Language,
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parameter.ExpectedFinalStatus,
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initialCash: 1000000, // 1M vs 100K that is set in BasicTemplateDailyAlgorithm (10x)
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setupHandler: "TestInitialCashAmountSetupHandler");
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Assert.AreEqual(0, TestInitialCashAmountSetupHandler.TestAlgorithm.Portfolio.CashBook["EUR"].Amount);
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Assert.AreEqual(Currencies.USD, TestInitialCashAmountSetupHandler.TestAlgorithm.AccountCurrency);
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}
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internal class TestInitialCashAmountAlgorithm : BasicTemplateDailyAlgorithm
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{
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public override void Initialize()
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{
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SetAccountCurrency("EUR");
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base.Initialize();
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SetCash("EUR", 1000000);
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}
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}
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internal class TestInitialCashAmountSetupHandler : AlgorithmRunner.RegressionSetupHandlerWrapper
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{
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public static TestInitialCashAmountAlgorithm TestAlgorithm { get; set; }
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public override IAlgorithm CreateAlgorithmInstance(AlgorithmNodePacket algorithmNodePacket, string assemblyPath)
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{
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Algorithm = TestAlgorithm = new TestInitialCashAmountAlgorithm();
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return Algorithm;
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}
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}
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}
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}
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