quantconnect--lean/Algorithm.CSharp/UniverseSharingSubscriptionRequestRegressionAlgorithm.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 System.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;

namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// This regression algorithm has two different Universe using the same SubscriptionDataConfig.
    /// One of them will add and remove it in a toggle fashion but since it will still be consumed
    /// by the other Universe it should not be removed.
    /// </summary>
    /// <meta name="tag" content="regression test" />
    public class UniverseSharingSubscriptionRequestRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
    {
        private readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);

        private int _onDataCalls;
        private bool _restOneDay;
        /// <summary>
        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
        /// </summary>
        public override void Initialize()
        {
            SetStartDate(2013, 10, 01); //Set Start Date
            SetEndDate(2013, 10, 30); //Set End Date
            SetCash(100000); //Set Strategy Cash

            AddEquity("SPY", Resolution.Daily);

            UniverseSettings.Resolution = Resolution.Daily;
            AddUniverse(SecurityType.Equity,
                "SecondUniverse",
                Resolution.Daily,
                Market.USA,
                UniverseSettings,
                time => time.Day % 3 == 0 ? new[] { "SPY" } : Enumerable.Empty<string>()
            );
        }

        /// <summary>
        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
        /// </summary>
        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
        public override void OnData(Slice slice)
        {
            if (slice.Count != 1)
            {
                throw new RegressionTestException($"Unexpected data count {slice.Count}");
            }
            Debug($"{slice.Time}. Data count {slice.Count}. Data {slice.Bars.First().Value}");
            _onDataCalls++;

            if (_restOneDay)
            {
                // let a day pass before trading again, this will cause
                // "SecondUniverse" remove request to be applied
                _restOneDay = false;
            }
            else if(!Portfolio.Invested)
            {
                SetHoldings(_spy, 1);
                Debug("Purchased Stock");
            }
            else
            {
                SetHoldings(_spy, 0);
                Debug("Sell Stock");
                _restOneDay = true;
            }
        }

        public override void OnEndOfAlgorithm()
        {
            if (_onDataCalls != 22)
            {
                throw new RegressionTestException($"Unexpected OnData() calls count {_onDataCalls}");
            }
        }

        /// <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 List<Language> Languages { get; } = new() { Language.CSharp };

        /// <summary>
        /// Data Points count of all timeslices of algorithm
        /// </summary>
        public long DataPoints => 206;

        /// <summary>
        /// Data Points count of the algorithm history
        /// </summary>
        public int AlgorithmHistoryDataPoints => 0;

        /// <summary>
        /// Final status of the algorithm
        /// </summary>
        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;

        /// <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 Orders", "15"},
            {"Average Win", "0.30%"},
            {"Average Loss", "0%"},
            {"Compounding Annual Return", "29.578%"},
            {"Drawdown", "0.700%"},
            {"Expectancy", "0"},
            {"Start Equity", "100000"},
            {"End Equity", "102128.38"},
            {"Net Profit", "2.128%"},
            {"Sharpe Ratio", "4.345"},
            {"Sortino Ratio", "7.134"},
            {"Probabilistic Sharpe Ratio", "90.299%"},
            {"Loss Rate", "0%"},
            {"Win Rate", "100%"},
            {"Profit-Loss Ratio", "0"},
            {"Alpha", "0.073"},
            {"Beta", "0.292"},
            {"Annual Standard Deviation", "0.045"},
            {"Annual Variance", "0.002"},
            {"Information Ratio", "-2.681"},
            {"Tracking Error", "0.083"},
            {"Treynor Ratio", "0.666"},
            {"Total Fees", "$47.53"},
            {"Estimated Strategy Capacity", "$760000000.00"},
            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
            {"Portfolio Turnover", "46.41%"},
            {"Drawdown Recovery", "7"},
            {"OrderListHash", "224b0ff29c5b287ecffaaa257e594ef3"}
        };
    }
}