/*

* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.

* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.

*

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0

*

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

*/

using System;

using System.Collections.Generic;

using QuantConnect.Data;

using QuantConnect.Interfaces;

namespace QuantConnect.Algorithm.CSharp

{

/// <summary>

/// Reproduces Lean GH issue 3572: benchmark _would_ use custom data versus equity

/// when both were present

/// </summary>

public class CustomBenchmarkRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition

{

/// <summary>

/// Algorithm initialization

/// </summary>

public override void Initialize()

{

SetStartDate(2013, 10, 07);

SetEndDate(2013, 10, 11);

AddEquity("AAPL", Resolution.Hour);

AddData<DummyCustomData>("AAPL");

// set benchmark will use equity AAPL as benchmark

SetBenchmark("AAPL");

}

/// <summary>

/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.

/// </summary>

/// <param name="data">Slice object keyed by symbol containing the stock data</param>

public override void OnData(Slice data)

{

if (!Portfolio.Invested)

{

SetHoldings("AAPL", 1);

Debug("Purchased Stock");

}

}

private class DummyCustomData : BaseData

{

public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)

{

return new SubscriptionDataSource("NonExistingFile", SubscriptionTransportMedium.LocalFile);

}

}

/// <summary>

/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.

/// </summary>

public bool CanRunLocally { get; } = true;

/// <summary>

/// This is used by the regression test system to indicate which languages this algorithm is written in.

/// </summary>

public Language[] Languages { get; } = { Language.CSharp };

/// <summary>

/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm

/// </summary>

public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>

{

{"Total Trades", "1"},

{"Average Win", "0%"},

{"Average Loss", "0%"},

{"Compounding Annual Return", "37.355%"},

{"Drawdown", "2.300%"},

{"Expectancy", "0"},

{"Net Profit", "0.407%"},

{"Sharpe Ratio", "5.521"},

{"Probabilistic Sharpe Ratio", "60.177%"},

{"Loss Rate", "0%"},

{"Win Rate", "0%"},

{"Profit-Loss Ratio", "0"},

{"Alpha", "-0.001"},

{"Beta", "0.997"},

{"Annual Standard Deviation", "0.179"},

{"Annual Variance", "0.032"},

{"Information Ratio", "-7.662"},

{"Tracking Error", "0"},

{"Treynor Ratio", "0.988"},

{"Total Fees", "$7.78"},

{"Fitness Score", "0.031"},

{"Kelly Criterion Estimate", "0"},

{"Kelly Criterion Probability Value", "0"},

{"Sortino Ratio", "-2.145"},

{"Return Over Maximum Drawdown", "-8.479"},

{"Portfolio Turnover", "0.25"},

{"Total Insights Generated", "0"},

{"Total Insights Closed", "0"},

{"Total Insights Analysis Completed", "0"},

{"Long Insight Count", "0"},

{"Short Insight Count", "0"},

{"Long/Short Ratio", "100%"},

{"Estimated Monthly Alpha Value", "$0"},

{"Total Accumulated Estimated Alpha Value", "$0"},

{"Mean Population Estimated Insight Value", "$0"},

{"Mean Population Direction", "0%"},

{"Mean Population Magnitude", "0%"},

{"Rolling Averaged Population Direction", "0%"},

{"Rolling Averaged Population Magnitude", "0%"},

{"OrderListHash", "519536519"}

};

}

}