Files
quantconnect--lean/Algorithm.CSharp/AddOptionContractExpiresRegressionAlgorithm.cs
T
Martin-Molinero 6ef2ead929 Do not update price scale for fillforward data & IsFillForward flag fix (#4836)
* Do not update price scale for fillforward data

- Do no update price scale for fill forward data. FillForward data
  should keep using the prev scale for which it was created. Adding unit tests
- When cloning do not lose IsFillForward flag state, affects
QuoteBars/Ticks, does not affect TradeBars since they perform a memberwise clone.
Adding unit tests

* Auxiliaries shouldn't really affect on applied price factor scale.

Despite we can receeive FillForward'ed data points, corresponding
Auxiliaries for them are not FillForward so we do meet the condition
and then refresh price factor. As a result all futher FF data points are scaled too.

* Regression algorithm to check that FillForward'ed data points arrived with last real price factor

* Add trade for regression algorithm

- Minot tweaks and adding trade for new regression algorithm.
- Updating AddOptionContractExpiresRegressionAlgorithm because it is
  using the symbol for which new data was added.

Co-authored-by: Adalyat Nazirov <aenazirov@gmail.com>
2020-10-09 18:09:30 -03:00

165 lines
6.9 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 QuantConnect.Data;
using QuantConnect.Interfaces;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// We add an option contract using <see cref="QCAlgorithm.AddOptionContract"/> and place a trade and wait till it expires
/// later will liquidate the resulting equity position and assert both option and underlying get removed
/// </summary>
public class AddOptionContractExpiresRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private DateTime _expiration = new DateTime(2014, 06, 21);
private Symbol _option;
private Symbol _twx;
private bool _traded;
public override void Initialize()
{
SetStartDate(2014, 06, 05);
SetEndDate(2014, 06, 30);
_twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA);
AddUniverse("my-daily-universe-name", time => new List<string> { "AAPL" });
}
public override void OnData(Slice data)
{
if (_option == null)
{
var option = OptionChainProvider.GetOptionContractList(_twx, Time)
.OrderBy(symbol => symbol.ID.Symbol)
.FirstOrDefault(optionContract => optionContract.ID.Date == _expiration
&& optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
if (option != null)
{
_option = AddOptionContract(option).Symbol;
}
}
if (_option != null && Securities[_option].Price != 0 && !_traded)
{
_traded = true;
Buy(_option, 1);
foreach (var symbol in new [] { _option, _option.Underlying })
{
var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
if (!config.Any())
{
throw new Exception($"Was expecting configurations for {symbol}");
}
if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
{
throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
}
}
}
if (Time.Date > _expiration)
{
if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_option).Any())
{
throw new Exception($"Unexpected configurations for {_option} after it has been delisted");
}
if (Securities[_twx].Invested)
{
if (!SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
{
throw new Exception($"Was expecting configurations for {_twx}");
}
// first we liquidate the option exercised position
Liquidate(_twx);
}
}
else if (Time.Date > _expiration && !Securities[_twx].Invested)
{
if (SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx).Any())
{
throw new Exception($"Unexpected configurations for {_twx} after it has been liquidated");
}
}
}
/// <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", "3"},
{"Average Win", "2.73%"},
{"Average Loss", "-2.98%"},
{"Compounding Annual Return", "-4.619%"},
{"Drawdown", "0.300%"},
{"Expectancy", "-0.042"},
{"Net Profit", "-0.332%"},
{"Sharpe Ratio", "-3.7"},
{"Probabilistic Sharpe Ratio", "0.563%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "0.92"},
{"Alpha", "-0.023"},
{"Beta", "0.005"},
{"Annual Standard Deviation", "0.006"},
{"Annual Variance", "0"},
{"Information Ratio", "-3.424"},
{"Tracking Error", "0.057"},
{"Treynor Ratio", "-4.775"},
{"Total Fees", "$2.00"},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "-43.418"},
{"Return Over Maximum Drawdown", "-14.274"},
{"Portfolio Turnover", "0.007"},
{"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", "-1185639451"}
};
}
}