chore: import upstream snapshot with attribution

This commit is contained in:
wehub-resource-sync
2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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/*
* 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 QuantConnect.Data;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm reproduces GH issue #8023, where fill forward resolution will no get updated in some cases on security removals
/// </summary>
public class FillForwardResolutionAdjustedOnRemovalRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private readonly Queue<DateTime> _expectedDataTimes = new(new DateTime[]
{
new DateTime(2013, 10, 7, 9, 31, 0),
new DateTime(2013, 10, 7, 16, 0, 0),
new DateTime(2013, 10, 8, 16, 0, 0),
new DateTime(2013, 10, 8, 16, 0, 0), // minute data & we remove it
new DateTime(2013, 10, 9, 16, 0, 0),
new DateTime(2013, 10, 10, 16, 0, 0)
});
public override void Initialize()
{
SetStartDate(2013, 10, 07);
SetEndDate(2013, 10, 10);
AddFuture("ES", Resolution.Minute);
AddEquity("SPY", Resolution.Daily);
}
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
var expected = _expectedDataTimes.Dequeue();
if (expected != Time)
{
throw new RegressionTestException($"Unexpected data time {expected} != {Time}");
}
if (ActiveSecurities.ContainsKey("/ES"))
{
if (slice.ContainsKey("/ES"))
{
RemoveSecurity("/ES");
}
}
else if (Time == new DateTime(2013, 10, 8, 16, 0, 0))
{
// let's re add it
AddFuture("ES", Resolution.Minute);
}
}
public override void OnEndOfAlgorithm()
{
if (_expectedDataTimes.Count != 0)
{
throw new RegressionTestException($"OnEndOfAlgorithm(): Unexpected data times!");
}
}
/// <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 List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 852;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <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 Orders", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100000"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino 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", "-5.677"},
{"Tracking Error", "0.271"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}