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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.Collections.Generic;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Interfaces;
using System;
using QuantConnect.Securities;
using QuantConnect.Data.UniverseSelection;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This example demonstrates how to use the FutureUniverseSelectionModel to select futures contracts for a given underlying asset.
/// The model is set to update daily, and the algorithm ensures that the selected contracts meet specific criteria.
/// This also includes a check to ensure that only future contracts are added to the algorithm's universe.
/// </summary>
public class AddFutureUniverseSelectionModelRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2013, 10, 10);
SetUniverseSelection(new FutureUniverseSelectionModel(
TimeSpan.FromDays(1),
time => new List<Symbol> {
QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME)
}
));
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
if (changes.AddedSecurities.Count > 0)
{
foreach (var security in changes.AddedSecurities)
{
if (security.Symbol.SecurityType != SecurityType.Future)
{
throw new RegressionTestException($"Expected future security, but found '{security.Symbol.SecurityType}'");
}
if (security.Symbol.ID.Symbol != "ES")
{
throw new RegressionTestException($"Expected future symbol 'ES', but found '{security.Symbol.ID.Symbol}");
}
}
}
}
public override void OnEndOfAlgorithm()
{
if (ActiveSecurities.Count == 0)
{
throw new RegressionTestException("No active securities found. Expected at least one active security");
}
}
/// <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, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 26094;
/// <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", "-66.775"},
{"Tracking Error", "0.243"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}