Louis Szeto
6d75aee0ce
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
92 lines
3.7 KiB
C#
92 lines
3.7 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.Collections.Generic;
|
|
using System.Linq;
|
|
using QuantConnect.Algorithm.Framework.Risk;
|
|
using QuantConnect.Algorithm.Framework.Selection;
|
|
|
|
namespace QuantConnect.Algorithm.CSharp
|
|
{
|
|
/// <summary>
|
|
/// Show example of how to use the <see cref="MaximumSectorExposureRiskManagementModel"/> Risk Management Model
|
|
/// </summary>
|
|
public class MaximumSectorExposureRiskManagementModelFrameworkRegressionAlgorithm : BaseFrameworkRegressionAlgorithm
|
|
{
|
|
public override void Initialize()
|
|
{
|
|
base.Initialize();
|
|
|
|
// Set requested data resolution
|
|
UniverseSettings.Resolution = Resolution.Daily;
|
|
|
|
SetStartDate(2014, 2, 1); //Set Start Date
|
|
SetEndDate(2014, 5, 1); //Set End Date
|
|
|
|
// set algorithm framework models
|
|
var tickers = new string[] { "AAPL", "MSFT", "GOOG", "AIG", "BAC" };
|
|
SetUniverseSelection(new FineFundamentalUniverseSelectionModel(
|
|
coarse => coarse.Where(x => tickers.Contains(x.Symbol.Value)).Select(x => x.Symbol),
|
|
fine => fine.Select(x => x.Symbol)
|
|
));
|
|
|
|
// define risk management model such that maximum weight of a single sector be 10%
|
|
// Number of of trades changed from 34 to 30 when using the MaximumSectorExposureRiskManagementModel
|
|
SetRiskManagement(new MaximumSectorExposureRiskManagementModel(0.1m));
|
|
}
|
|
|
|
public override void OnEndOfAlgorithm()
|
|
{
|
|
// The MaximumSectorExposureRiskManagementModel does not expire insights
|
|
}
|
|
|
|
/// <summary>
|
|
/// Data Points count of all timeslices of algorithm
|
|
/// </summary>
|
|
public override long DataPoints => 544;
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
|
/// </summary>
|
|
public override Dictionary<string, string> ExpectedStatistics => new()
|
|
{
|
|
{"Total Trades", "30"},
|
|
{"Average Win", "0.01%"},
|
|
{"Average Loss", "-0.07%"},
|
|
{"Compounding Annual Return", "-3.542%"},
|
|
{"Drawdown", "1.300%"},
|
|
{"Expectancy", "-0.909"},
|
|
{"Net Profit", "-0.885%"},
|
|
{"Sharpe Ratio", "-1.538"},
|
|
{"Probabilistic Sharpe Ratio", "3.669%"},
|
|
{"Loss Rate", "92%"},
|
|
{"Win Rate", "8%"},
|
|
{"Profit-Loss Ratio", "0.18"},
|
|
{"Alpha", "-0.036"},
|
|
{"Beta", "0.06"},
|
|
{"Annual Standard Deviation", "0.016"},
|
|
{"Annual Variance", "0"},
|
|
{"Information Ratio", "-2.295"},
|
|
{"Tracking Error", "0.093"},
|
|
{"Treynor Ratio", "-0.411"},
|
|
{"Total Fees", "$33.89"},
|
|
{"Estimated Strategy Capacity", "$44000000.00" },
|
|
{"Lowest Capacity Asset", "AIG R735QTJ8XC9X"},
|
|
{"Portfolio Turnover", "0.81%"},
|
|
{"OrderListHash", "a4abf04ae5be2437253d76a96c349335" }
|
|
};
|
|
}
|
|
}
|