quantconnect--lean/Algorithm.CSharp/CustomBenchmarkRegressionAlgorithm.cs

/*
 * 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"},
            {"Estimated Strategy Capacity", "$8700000.00"},
            {"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
            {"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", "be3334e4aeb9dd7cca4ecc07419d0f95"}
        };
    }
}