/*
* 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.Selection;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Securities;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Futures regression algorithm intended to test the behavior of the framework models. See GH issue 4027.
///
public class EqualWeightingPortfolioConstructionModelFutureRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private int _fillCount;
public override void Initialize()
{
SetStartDate(2013, 10, 07);
SetEndDate(2013, 10, 11);
SetUniverseSelection(new FrontMonthFutureUniverseSelectionModel(SelectFutureChainSymbols));
SetAlpha(new ConstantFutureContractAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1)));
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
SetExecution(new ImmediateExecutionModel());
// Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
// Commented so regression algorithm is more sensitive
//Settings.MinimumOrderMarginPortfolioPercentage = 0.005m;
}
// future symbol universe selection function
private static IEnumerable SelectFutureChainSymbols(DateTime utcTime)
{
return new []
{
QuantConnect.Symbol.Create(Futures.Indices.SP500EMini, SecurityType.Future, Market.CME),
QuantConnect.Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.COMEX)
};
}
///
/// Creates futures chain universes that select the front month contract and runs a user
/// defined futureChainSymbolSelector every day to enable choosing different futures chains
///
class FrontMonthFutureUniverseSelectionModel : FutureUniverseSelectionModel
{
public FrontMonthFutureUniverseSelectionModel(Func> futureChainSymbolSelector)
: base(TimeSpan.FromDays(1), futureChainSymbolSelector)
{
}
///
/// Defines the future chain universe filter
///
protected override FutureFilterUniverse Filter(FutureFilterUniverse filter)
{
return filter
.FrontMonth()
.OnlyApplyFilterAtMarketOpen();
}
}
///
/// Implementation of a constant alpha model that only emits insights for future symbols
///
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);
}
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
Log($"{orderEvent}");
if (orderEvent.Status == OrderStatus.Filled)
{
_fillCount++;
if (_fillCount == 2)
{
if (Portfolio.TotalHoldingsValue / Portfolio.TotalPortfolioValue < 10)
{
throw new RegressionTestException("Expected to be trading using the futures margin leverage");
}
}
}
}
///
/// 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 => 36213;
///
/// Data Points count of the algorithm history
///
public int AlgorithmHistoryDataPoints => 0;
///
/// 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", "8"},
{"Average Win", "0.69%"},
{"Average Loss", "-2.47%"},
{"Compounding Annual Return", "-99.946%"},
{"Drawdown", "28.600%"},
{"Expectancy", "-0.680"},
{"Start Equity", "100000"},
{"End Equity", "90213.76"},
{"Net Profit", "-9.786%"},
{"Sharpe Ratio", "-0.603"},
{"Sortino Ratio", "-0.892"},
{"Probabilistic Sharpe Ratio", "30.082%"},
{"Loss Rate", "75%"},
{"Win Rate", "25%"},
{"Profit-Loss Ratio", "0.28"},
{"Alpha", "-15.818"},
{"Beta", "7.498"},
{"Annual Standard Deviation", "1.669"},
{"Annual Variance", "2.787"},
{"Information Ratio", "-2.061"},
{"Tracking Error", "1.447"},
{"Treynor Ratio", "-0.134"},
{"Total Fees", "$52.01"},
{"Estimated Strategy Capacity", "$1800000.00"},
{"Lowest Capacity Asset", "GC VL5E74HP3EE5"},
{"Portfolio Turnover", "475.60%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "91aeb0d6f6a18df9fd755fc473183395"}
};
}
}