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quantconnect--lean/Algorithm.CSharp/OptionPriceModelForSupportedEuropeanOptionRegressionAlgorithm.cs
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Ryan Russell 98fa4464ce
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docs: excersizing -> exercising (#6559)
* docs: `excersizing` -> `exercising`

Signed-off-by: Ryan Russell <git@ryanrussell.org>

* docs: fix `exercising for exercising`

Signed-off-by: Ryan Russell <git@ryanrussell.org>

* docs: `migth` -> `might`

Signed-off-by: Ryan Russell <git@ryanrussell.org>

Signed-off-by: Ryan Russell <git@ryanrussell.org>
2022-08-18 11:00:26 -03:00

101 lines
4.1 KiB
C#

/*
* 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.Collections.Generic;
using QuantConnect.Securities.Option;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm exercising an index covered European style option, using an option price model
/// that supports European style options and asserting that the option price model is used.
/// </summary>
public class OptionPriceModelForSupportedEuropeanOptionRegressionAlgorithm : OptionPriceModelForOptionStylesBaseRegressionAlgorithm
{
public override void Initialize()
{
SetStartDate(2021, 1, 14);
SetEndDate(2021, 1, 14);
var option = AddIndexOption("SPX", Resolution.Hour);
// BlackScholes model supports European style options
option.PriceModel = OptionPriceModels.BlackScholes();
SetWarmup(7, Resolution.Daily);
Init(option, optionStyleIsSupported: true);
}
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public override long DataPoints => 211;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public override int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
{"Portfolio Turnover", "0"},
{"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", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}