/*
* 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.Linq;
using QuantConnect.Data;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using QuantConnect.Data.Market;
using System.Collections.Generic;
using QuantConnect.Securities.Future;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Continuous Futures Back Month #1 Regression algorithm. Asserting and showcasing the behavior of adding a continuous future
///
public class ContinuousFutureBackMonthRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List _mappings = new();
private Future _continuousContract;
private DateTime _lastDateLog;
///
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
///
public override void Initialize()
{
SetStartDate(2013, 7, 1);
SetEndDate(2014, 1, 1);
try
{
AddFuture(Futures.Indices.SP500EMini,
dataNormalizationMode: DataNormalizationMode.BackwardsPanamaCanal,
dataMappingMode: DataMappingMode.OpenInterest,
contractDepthOffset: 5
);
throw new RegressionTestException("Expected out of rage exception. We don't support that many back months");
}
catch (ArgumentOutOfRangeException)
{
// expected
}
_continuousContract = AddFuture(Futures.Indices.SP500EMini,
dataNormalizationMode: DataNormalizationMode.BackwardsPanamaCanal,
dataMappingMode: DataMappingMode.OpenInterest,
contractDepthOffset: 1
);
}
///
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
///
/// Slice object keyed by symbol containing the stock data
public override void OnData(Slice slice)
{
if (slice.Keys.Count != 1)
{
throw new RegressionTestException($"We are getting data for more than one symbols! {string.Join(",", slice.Keys.Select(symbol => symbol))}");
}
foreach (var changedEvent in slice.SymbolChangedEvents.Values)
{
if (changedEvent.Symbol == _continuousContract.Symbol)
{
_mappings.Add(changedEvent);
Log($"SymbolChanged event: {changedEvent}");
var backMonthExpiration = changedEvent.Symbol.Underlying.ID.Date;
var frontMonthExpiration = FuturesExpiryFunctions.FuturesExpiryFunction(_continuousContract.Symbol)(Time.AddMonths(1));
if (backMonthExpiration <= frontMonthExpiration.Date)
{
throw new RegressionTestException($"Unexpected current mapped contract expiration {backMonthExpiration}" +
$" @ {Time} it should be AFTER front month expiration {frontMonthExpiration}");
}
if (_continuousContract.Mapped != changedEvent.Symbol.Underlying)
{
throw new RegressionTestException($"Unexpected mapped continuous contract {_continuousContract.Mapped} expected {changedEvent.Symbol.Underlying}");
}
}
}
if (_lastDateLog.Month != Time.Month && _continuousContract.HasData)
{
_lastDateLog = Time;
Log($"{Time}- {Securities[_continuousContract.Symbol].GetLastData()}");
if (_continuousContract.Exchange.ExchangeOpen)
{
if (Portfolio.Invested)
{
Liquidate();
}
else
{
Buy(_continuousContract.Mapped, 1);
}
}
if(Time.Month == 1 && Time.Year == 2013)
{
var response = History(new[] { _continuousContract.Symbol }, 60 * 24 * 90);
if (!response.Any())
{
throw new RegressionTestException("Unexpected empty history response");
}
}
}
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Status == OrderStatus.Filled)
{
Log($"{orderEvent}");
}
}
public override void OnEndOfAlgorithm()
{
var expectedMappingCounts = 2;
if (_mappings.Count != expectedMappingCounts)
{
throw new RegressionTestException($"Unexpected symbol changed events: {_mappings.Count}, was expecting {expectedMappingCounts}");
}
}
///
/// 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 => 172698;
///
/// 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", "3"},
{"Average Win", "1.48%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "4.603%"},
{"Drawdown", "1.600%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "102291.4"},
{"Net Profit", "2.291%"},
{"Sharpe Ratio", "0.892"},
{"Sortino Ratio", "0.312"},
{"Probabilistic Sharpe Ratio", "55.781%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.006"},
{"Beta", "0.14"},
{"Annual Standard Deviation", "0.028"},
{"Annual Variance", "0.001"},
{"Information Ratio", "-2.584"},
{"Tracking Error", "0.075"},
{"Treynor Ratio", "0.175"},
{"Total Fees", "$6.45"},
{"Estimated Strategy Capacity", "$230000000.00"},
{"Lowest Capacity Asset", "ES VP274HSU1AF5"},
{"Portfolio Turnover", "1.39%"},
{"Drawdown Recovery", "16"},
{"OrderListHash", "6a5b2e6b3f140e9bb7f32c07cbf5f36c"}
};
}
}