Files
quantconnect--lean/Algorithm.CSharp/OptionExpiryDateTodayRegressionAlgorithm.cs
T
Martin-Molinero 6563d6e394
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Use any resolution for chain provider (#6860)
* Use any resolution for chain provider

- Use any data resolution available to source symbols for the file based
  chain provider. Adding unit test

* Fix selection timezone bug

- Fix universe selection timezone bug. Updating regression algorithms
2023-01-16 16:10:07 -03:00

167 lines
6.2 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;
using System.Linq;
using System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Securities.Option;
using QuantConnect.Securities;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm exercising an equity covered option asserting that greeks can be accessed
/// and have are not all zero, the same day as the contract expiration date.
/// </summary>
public class OptionExpiryDateTodayRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _optionSymbol;
private bool _triedGreeksCalculation;
public override void Initialize()
{
SetStartDate(2014, 06, 9);
SetEndDate(2014, 06, 15);
var option = AddOption("AAPL", Resolution.Minute);
option.SetFilter((universeFilter) =>
{
return universeFilter.IncludeWeeklys().Strikes(-1, 1).Expiration(0, 10);
});
option.PriceModel = OptionPriceModels.BaroneAdesiWhaley();
_optionSymbol = option.Symbol;
SetWarmUp(TimeSpan.FromDays(3));
}
public override void OnData(Slice slice)
{
if (IsWarmingUp || Time.Hour > 10)
{
return;
}
foreach (var kvp in slice.OptionChains)
{
if (kvp.Key != _optionSymbol)
{
continue;
}
var chain = kvp.Value;
// Find the call options expiring today
var contracts = chain
.Where(contract => contract.Expiry.Date == Time.Date && contract.Strike < chain.Underlying.Price)
.ToList();
if (contracts.Count == 0)
{
return;
}
_triedGreeksCalculation = true;
foreach (var contract in contracts)
{
var greeks = contract.Greeks;
if (greeks.Delta == 0m && greeks.Gamma == 0m && greeks.Theta == 0m && greeks.Vega == 0m && greeks.Rho == 0m)
{
throw new Exception($"Expected greeks to not be zero simultaneously for {contract.Symbol} at contract expiration date {contract.Expiry}");
}
}
}
}
public override void OnEndOfAlgorithm()
{
if (!_triedGreeksCalculation)
{
throw new Exception("Expected to have tried greeks calculation");
}
}
/// <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>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 8896599;
/// <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 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", "5.176"},
{"Tracking Error", "0.071"},
{"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"}
};
}
}