/*
* 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 System.Linq;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Regression algorithm testing the behavior of the algorithm when a security is removed and re-added.
/// It asserts that the securities are marked as non-tradable when removed and that they are tradable when re-added.
/// It also asserts that the algorithm receives the correct security changed events for the added and removed securities.
///
/// Additionally, it tests that the security is initialized after every addition, and no more.
///
/// This specific algorithm tests this behavior for securities selected, deselected and re-selected from universes.
///
public class SecurityInitializationOnReAdditionForUniverseSelectionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List _symbolsToSelect;
private List _selectedSymbols;
private int _selectionsCount;
private Dictionary _securityInializationCounts = new();
public override void Initialize()
{
SetStartDate(2014, 03, 24);
SetEndDate(2014, 04, 07);
SetCash(100000);
UniverseSettings.Resolution = Resolution.Daily;
var seeder = new FuncSecuritySeeder((security) =>
{
if (!_securityInializationCounts.TryGetValue(security, out var count))
{
count = 0;
}
_securityInializationCounts[security] = count + 1;
Debug($"[{Time}] Seeding {security.Symbol}");
return GetLastKnownPrices(security);
});
SetSecurityInitializer(security => seeder.SeedSecurity(security));
_symbolsToSelect = new List()
{
QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA),
QuantConnect.Symbol.Create("IWM", SecurityType.Equity, Market.USA),
QuantConnect.Symbol.Create("QQQ", SecurityType.Equity, Market.USA),
QuantConnect.Symbol.Create("AIG", SecurityType.Equity, Market.USA),
QuantConnect.Symbol.Create("BAC", SecurityType.Equity, Market.USA),
QuantConnect.Symbol.Create("IBM", SecurityType.Equity, Market.USA),
};
AddUniverse("MyUniverse", Resolution.Daily, SelectionFunction);
}
private IEnumerable SelectionFunction(DateTime dateTime)
{
_securityInializationCounts.Clear();
_selectionsCount++;
_selectedSymbols = _symbolsToSelect.Skip(dateTime.Day % 2 == 0 ? 0 : 3).Take(3).ToList();
return _selectedSymbols.Select(x => x.Value);
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
foreach (var security in changes.AddedSecurities)
{
if (!security.IsTradable)
{
throw new RegressionTestException($"Expected the security to be tradable. Symbol: {security.Symbol}");
}
}
foreach (var security in changes.RemovedSecurities)
{
if (security.IsTradable)
{
throw new RegressionTestException($"Expected the security to be not tradable. Symbol: {security.Symbol}");
}
}
if (changes.AddedSecurities.Count != _selectedSymbols.Count ||
changes.AddedSecurities.Any(x => !_selectedSymbols.Contains(x.Symbol)))
{
throw new RegressionTestException($"Expected the added securities to be the selected ones. " +
$"Added: {string.Join(", ", changes.AddedSecurities.Select(x => x.Symbol.Value))}, " +
$"Selected: {string.Join(", ", _selectedSymbols)}");
}
if (changes.AddedSecurities.Count != _securityInializationCounts.Count ||
changes.AddedSecurities.Any(x => !_securityInializationCounts.TryGetValue(x, out var count) || count != 1))
{
throw new RegressionTestException($"Expected all contracts to be initialized. " +
$"Added: {string.Join(", ", changes.AddedSecurities.Select(x => x.Symbol.Value))}, " +
$"Initialized: {string.Join(", ", _securityInializationCounts.Select(x => $"{x.Key.Symbol.Value} - {x.Value}"))}");
}
if (changes.RemovedSecurities.Count > 0)
{
var expectedDeselectedSymbols = _symbolsToSelect.Where(x => !_selectedSymbols.Contains(x)).ToList();
if (changes.RemovedSecurities.Count != expectedDeselectedSymbols.Count ||
changes.RemovedSecurities.Any(x => !expectedDeselectedSymbols.Contains(x.Symbol)))
{
throw new RegressionTestException($"Expected the removed securities to be the deselected ones. " +
$"Removed: {string.Join(", ", changes.RemovedSecurities.Select(x => x.Symbol.Value))}, " +
$"Deselected: {string.Join(", ", expectedDeselectedSymbols)}");
}
}
}
public override void OnEndOfAlgorithm()
{
if (_selectionsCount < 2)
{
throw new RegressionTestException("Expected at least two selections");
}
}
///
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
///
public bool CanRunLocally { get; } = true;
///
/// This is used by the regression test system to indicate which languages this algorithm is written in.
///
public List Languages { get; } = new() { Language.CSharp };
///
/// Data Points count of all timeslices of algorithm
///
public long DataPoints => 128;
///
/// Data Points count of the algorithm history
///
public int AlgorithmHistoryDataPoints => 150;
///
/// Final status of the algorithm
///
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
///
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
///
public Dictionary ExpectedStatistics => new Dictionary
{
{"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", "0.97"},
{"Tracking Error", "0.097"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}