Martin Molinero
122 lines
4.8 KiB
C#
122 lines
4.8 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 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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/// Reproduces Lean GH issue 3572: benchmark _would_ use custom data versus equity
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/// when both were present
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/// </summary>
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public class CustomBenchmarkRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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/// <summary>
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/// Algorithm initialization
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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AddEquity("AAPL", Resolution.Hour);
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AddData<DummyCustomData>("AAPL");
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// set benchmark will use equity AAPL as benchmark
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SetBenchmark("AAPL");
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (!Portfolio.Invested)
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{
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SetHoldings("AAPL", 1);
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Debug("Purchased Stock");
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}
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}
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private class DummyCustomData : BaseData
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{
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public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
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{
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return new SubscriptionDataSource("NonExistingFile", SubscriptionTransportMedium.LocalFile);
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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 Language[] Languages { get; } = { Language.CSharp };
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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 Trades", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "37.355%"},
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{"Drawdown", "2.300%"},
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{"Expectancy", "0"},
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{"Net Profit", "0.407%"},
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{"Sharpe Ratio", "5.521"},
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{"Probabilistic Sharpe Ratio", "60.177%"},
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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", "-0.001"},
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{"Beta", "0.997"},
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{"Annual Standard Deviation", "0.179"},
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{"Annual Variance", "0.032"},
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{"Information Ratio", "-7.662"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0.988"},
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{"Total Fees", "$7.78"},
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{"Fitness Score", "0.031"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-2.145"},
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{"Return Over Maximum Drawdown", "-8.479"},
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{"Portfolio Turnover", "0.25"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "519536519"}
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};
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}
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}
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