Files
quantconnect--lean/Algorithm.CSharp/MeanVarianceOptimizationFrameworkAlgorithm.cs
T
AlexCatarino b402c3673e Fixes MVOPC: it was not testing whether all magnitures are zero
- Changes `ExpectedStatistics` in MVOFA
  - All regression tests now
- Removes unnecessary constructor arguments in `ReturnsSymbolData`
- Tide up code and add method summaries.
2018-07-24 16:53:11 +01:00

111 lines
4.8 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 QuantConnect.Algorithm.Framework;
using QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Execution;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Risk;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Interfaces;
using System.Linq;
using QuantConnect.Data.UniverseSelection;
namespace QuantConnect.Algorithm.CSharp
{
public class MeanVarianceOptimizationFrameworkAlgorithm : QCAlgorithmFramework, IRegressionAlgorithmDefinition
{
private IEnumerable<Symbol> _symbols = (new string[] { "AIG", "BAC", "IBM", "SPY" }).Select(s => QuantConnect.Symbol.Create(s, SecurityType.Equity, Market.USA));
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
// Set requested data resolution
UniverseSettings.Resolution = Resolution.Minute;
SetStartDate(2013, 10, 07); //Set Start Date
SetEndDate(2013, 10, 11); //Set End Date
SetCash(100000); //Set Strategy Cash
// Find more symbols here: http://quantconnect.com/data
// Forex, CFD, Equities Resolutions: Tick, Second, Minute, Hour, Daily.
// Futures Resolution: Tick, Second, Minute
// Options Resolution: Minute Only.
// set algorithm framework models
SetUniverseSelection(new CoarseFundamentalUniverseSelectionModel(CoarseSelector));
SetAlpha(new HistoricalReturnsAlphaModel(resolution: Resolution.Daily));
SetPortfolioConstruction(new MeanVarianceOptimizationPortfolioConstructionModel());
SetExecution(new ImmediateExecutionModel());
SetRiskManagement(new NullRiskManagementModel());
}
public IEnumerable<Symbol> CoarseSelector(IEnumerable<CoarseFundamental> coarse)
{
int last = Time.Day > 8 ? 3 : _symbols.Count();
return _symbols.Take(last);
}
public bool CanRunLocally => 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", "11"},
{"Average Win", "0.50%"},
{"Average Loss", "-0.14%"},
{"Compounding Annual Return", "564.274%"},
{"Drawdown", "0.600%"},
{"Expectancy", "1.248"},
{"Net Profit", "2.628%"},
{"Sharpe Ratio", "8.542"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "3.50"},
{"Alpha", "0"},
{"Beta", "95.538"},
{"Annual Standard Deviation", "0.129"},
{"Annual Variance", "0.017"},
{"Information Ratio", "8.459"},
{"Tracking Error", "0.129"},
{"Treynor Ratio", "0.011"},
{"Total Fees", "$23.99"},
{"Total Insights Generated", "14"},
{"Total Insights Closed", "4"},
{"Total Insights Analysis Completed", "0"},
{"Long Insight Count", "6"},
{"Short Insight Count", "4"},
{"Long/Short Ratio", "150.0%"},
{"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%"}
};
}
}