Files
quantconnect--lean/Algorithm.CSharp/OptionAssignmentRegressionAlgorithm.cs
T
Jhonathan Abreu bc05aa03f9 Fix win/loss count statistics for options assignments (#7354)
* Add ITM option assignment trade as win in trade statistics

* Add TradeStatistics unit tests

* Add unit tests

* Add OptionTrade class to abstract IsWin method

* Keep track of winning/losing trades

* Add more unit tests

* Change Trade.IsWin to a property calculated by the trade builder

* Improve regression algorithm

* Handle ITM option sell win/loss statistics

* Update regression algorithms statistics

* Revert accidental unwanted changes

* Address peer review

* Keep track of winning and losing transactions for portfolio statistics

* Add more SecurityPortfolioModel unit tests

* Fix failing unit tests

* Minor changes

* Address peer review

* Minor fix
2023-07-10 10:20:29 -03:00

134 lines
5.0 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 System.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This regression algorithm verifies automatic option contract assignment behavior.
/// </summary>
/// <meta name="tag" content="regression test" />
/// <meta name="tag" content="options" />
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="filter selection" />
public class OptionAssignmentRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Security Stock;
private Security CallOption;
private Symbol CallOptionSymbol;
private Security PutOption;
private Symbol PutOptionSymbol;
public override void Initialize()
{
SetStartDate(2015, 12, 23);
SetEndDate(2015, 12, 28);
SetCash(100000);
Stock = AddEquity("GOOG", Resolution.Minute);
var contracts = OptionChainProvider.GetOptionContractList(Stock.Symbol, UtcTime).ToList();
PutOptionSymbol = contracts
.Where(c => c.ID.OptionRight == OptionRight.Put)
.OrderBy(c => c.ID.Date)
.First(c => c.ID.StrikePrice == 800m);
CallOptionSymbol = contracts
.Where(c => c.ID.OptionRight == OptionRight.Call)
.OrderBy(c => c.ID.Date)
.First(c => c.ID.StrikePrice == 600m);
PutOption = AddOptionContract(PutOptionSymbol);
CallOption = AddOptionContract(CallOptionSymbol);
}
public override void OnData(Slice data)
{
if (!Portfolio.Invested && Stock.Price != 0 && PutOption.Price != 0 && CallOption.Price != 0)
{
// this gets executed on start and after each auto-assignment, finally ending with expiration assignment
if (Time < PutOptionSymbol.ID.Date)
{
MarketOrder(PutOptionSymbol, -1);
}
if (Time < CallOptionSymbol.ID.Date)
{
MarketOrder(CallOptionSymbol, -1);
}
}
}
/// <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 virtual Language[] Languages { get; } = { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 4025;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public 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 virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "32"},
{"Average Win", "9.60%"},
{"Average Loss", "-16.91%"},
{"Compounding Annual Return", "-84.836%"},
{"Drawdown", "2.900%"},
{"Expectancy", "-0.608"},
{"Net Profit", "-2.886%"},
{"Sharpe Ratio", "-6.759"},
{"Probabilistic Sharpe Ratio", "1.125%"},
{"Loss Rate", "75%"},
{"Win Rate", "25%"},
{"Profit-Loss Ratio", "0.57"},
{"Alpha", "-0.01"},
{"Beta", "0.458"},
{"Annual Standard Deviation", "0.014"},
{"Annual Variance", "0"},
{"Information Ratio", "5.991"},
{"Tracking Error", "0.015"},
{"Treynor Ratio", "-0.207"},
{"Total Fees", "$16.00"},
{"Estimated Strategy Capacity", "$710000.00"},
{"Lowest Capacity Asset", "GOOCV 305RBQ20WHPNQ|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "218.80%"},
{"OrderListHash", "171733fe6c2c8d178457baa8fd562952"}
};
}
}