Martin-Molinero
bbbab6d9a8
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* Refactor alpha statistics - Refactor alpha statistics, cleaning up and simplifying no longer required calculations and scoring - Adding new InsightEvaluator abstraction, adding C# & PY regression algorithms * Optimization backtest result json converter update * Address reviews - Remove IAlphaHandler, move insight storage responsability to IResultHandler and centralizing insight collection on the QCAlgorithm.Insights to be reused by the framework models - Fix portfolio turnover single day backtests and duplicate time sampling handling. Updating regression algorithms * Add InsightCollection tests and minor fixes * Adding more & improved tests
62 lines
2.4 KiB
C#
62 lines
2.4 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 NUnit.Framework;
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using System.Collections.Generic;
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namespace QuantConnect.Tests.Common
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{
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[TestFixture]
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public class ExtendedDictionaryTests
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{
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[Test]
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public void RunPythonDictionaryFeatureRegressionAlgorithm()
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{
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var parameter = new RegressionTests.AlgorithmStatisticsTestParameters("PythonDictionaryFeatureRegressionAlgorithm",
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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", "-100%"},
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{"Drawdown", "99.600%"},
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{"Expectancy", "0"},
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{"Net Profit", "-99.625%"},
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{"Sharpe Ratio", "-0.126"},
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{"Probabilistic Sharpe Ratio", "1.667%"},
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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", "2.999"},
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{"Beta", "-2.017"},
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{"Annual Standard Deviation", "7.952"},
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{"Annual Variance", "63.235"},
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{"Information Ratio", "-0.374"},
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{"Tracking Error", "7.968"},
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{"Treynor Ratio", "0.496"},
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{"Total Fees", "$0.00"},
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{"OrderListHash", "d303a19fe5a40b59ee99535985833000"}
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},
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Language.Python,
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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.Language,
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parameter.ExpectedFinalStatus,
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initialCash: 100000);
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}
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}
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}
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