Files
quantconnect--lean/Algorithm.CSharp/BasicTemplateFuturesFrameworkAlgorithm.cs
T
2019-09-29 21:50:44 -03:00

173 lines
7.1 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;
using System.Collections.Generic;
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 QuantConnect.Securities;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Basic template futures framework algorithm uses framework components to define an algorithm
/// that trades futures.
/// </summary>
public class BasicTemplateFuturesFrameworkAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
public override void Initialize()
{
UniverseSettings.Resolution = Resolution.Minute;
SetStartDate(2013, 10, 07);
SetEndDate(2013, 10, 11);
SetCash(100000);
// set framework models
SetUniverseSelection(new FrontMonthFutureUniverseSelectionModel(SelectFutureChainSymbols));
SetAlpha(new ConstantFutureContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1)));
SetPortfolioConstruction(new SingleSharePortfolioConstructionModel());
SetExecution(new ImmediateExecutionModel());
SetRiskManagement(new NullRiskManagementModel());
}
// future symbol universe selection function
private static IEnumerable<Symbol> SelectFutureChainSymbols(DateTime utcTime)
{
var newYorkTime = utcTime.ConvertFromUtc(TimeZones.NewYork);
if (newYorkTime.Date < new DateTime(2013, 10, 09))
{
yield return QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.USA);
}
if (newYorkTime.Date >= new DateTime(2013, 10, 09))
{
yield return QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.USA);
}
}
/// <summary>
/// Creates futures chain universes that select the front month contract and runs a user
/// defined futureChainSymbolSelector every day to enable choosing different futures chains
/// </summary>
class FrontMonthFutureUniverseSelectionModel : FutureUniverseSelectionModel
{
public FrontMonthFutureUniverseSelectionModel(Func<DateTime, IEnumerable<Symbol>> futureChainSymbolSelector)
: base(TimeSpan.FromDays(1), futureChainSymbolSelector)
{
}
/// <summary>
/// Defines the future chain universe filter
/// </summary>
protected override FutureFilterUniverse Filter(FutureFilterUniverse filter)
{
return filter
.FrontMonth()
.OnlyApplyFilterAtMarketOpen();
}
}
/// <summary>
/// Implementation of a constant alpha model that only emits insights for future symbols
/// </summary>
class ConstantFutureContractAlphaModel : ConstantAlphaModel
{
public ConstantFutureContractAlphaModel(InsightType type, InsightDirection direction, TimeSpan period)
: base(type, direction, period)
{
}
protected override bool ShouldEmitInsight(DateTime utcTime, Symbol symbol)
{
// only emit alpha for future symbols and not underlying equity symbols
if (symbol.SecurityType != SecurityType.Future)
{
return false;
}
return base.ShouldEmitInsight(utcTime, symbol);
}
}
/// <summary>
/// Portfolio construction model that sets target quantities to 1 for up insights and -1 for down insights
/// </summary>
class SingleSharePortfolioConstructionModel : PortfolioConstructionModel
{
public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
{
foreach (var insight in insights)
{
yield return new PortfolioTarget(insight.Symbol, (int) insight.Direction);
}
}
}
/// <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 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", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "-91.448%"},
{"Drawdown", "5.000%"},
{"Expectancy", "0"},
{"Net Profit", "-3.312%"},
{"Sharpe Ratio", "-14.22"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-1.479"},
{"Beta", "0.204"},
{"Annual Standard Deviation", "0.099"},
{"Annual Variance", "0.01"},
{"Information Ratio", "-10.043"},
{"Tracking Error", "0.176"},
{"Treynor Ratio", "-6.907"},
{"Total Fees", "$3.70"},
{"Total Insights Generated", "6"},
{"Total Insights Closed", "5"},
{"Total Insights Analysis Completed", "5"},
{"Long Insight Count", "6"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$-90.70258"},
{"Total Accumulated Estimated Alpha Value", "$-15.621"},
{"Mean Population Estimated Insight Value", "$-3.1242"},
{"Mean Population Direction", "0%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "0%"},
{"Rolling Averaged Population Magnitude", "0%"}
};
}
}