Regression Algorithm being used

OptionHistoryRenameRegressionAlgorithm.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.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Interfaces;

namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// This is an option split regression algorithm
    /// </summary>
    /// <meta name="tag" content="options" />
    /// <meta name="tag" content="regression test" />
    public class OptionHistoryRenameRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
    {
        private Symbol _optionSymbol;

        public override void Initialize()
        {
            // this test opens position in the first day of trading, lives through stock rename (NWSA->FOXA), dividends, and closes adjusted position on the third day
            SetStartDate(2013, 06, 28);
            SetEndDate(2013, 07, 02);
            SetCash(1000000);

            var option = AddOption("FOXA");
            _optionSymbol = option.Symbol;

            // set our strike/expiry filter for this option chain
            option.SetFilter(-1, +1, TimeSpan.Zero, TimeSpan.MaxValue);

            // use the underlying equity as the benchmark
            SetBenchmark("FOXA");
        }

        public override void OnEndOfDay(Symbol symbol)
        {
            var data = History(symbol, 60, Resolution.Minute);

            foreach (var datum in data)
            {
                Log($"{Time} - {datum.Symbol.Value}");
            }
        }

        /// <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, Language.Python };

        /// <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", "4"},
            {"Average Win", "0%"},
            {"Average Loss", "-0.02%"},
            {"Compounding Annual Return", "-0.484%"},
            {"Drawdown", "0.000%"},
            {"Expectancy", "-1"},
            {"Net Profit", "-0.006%"},
            {"Sharpe Ratio", "-3.415"},
            {"Loss Rate", "100%"},
            {"Win Rate", "0%"},
            {"Profit-Loss Ratio", "0"},
            {"Alpha", "-0.016"},
            {"Beta", "-0.001"},
            {"Annual Standard Deviation", "0.002"},
            {"Annual Variance", "0"},
            {"Information Ratio", "10.014"},
            {"Tracking Error", "0.877"},
            {"Treynor Ratio", "4.289"},
            {"Total Fees", "$4.00"}
        };
    }
}