/* * 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 System.Collections.Generic; using QuantConnect.Securities.Future; using QuantConnect.Data.UniverseSelection; namespace QuantConnect.Algorithm.CSharp { /// /// Continuous Futures Regression algorithm. Asserting and showcasing the behavior of adding a continuous future /// and a future contract at the same time /// public class AddFutureContractWithContinuousRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private Symbol _currentMappedSymbol; private Future _continuousContract; private Future _futureContract; private bool _ended; /// /// 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, 10, 6); SetEndDate(2013, 10, 10); _continuousContract = AddFuture(Futures.Indices.SP500EMini, dataNormalizationMode: DataNormalizationMode.BackwardsRatio, dataMappingMode: DataMappingMode.LastTradingDay, contractDepthOffset: 0 ); _futureContract = AddFutureContract(FutureChainProvider.GetFutureContractList(_continuousContract.Symbol, Time).First()); } /// /// 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 data) { if (_ended) { throw new Exception($"Algorithm should of ended!"); } if (data.Keys.Count > 2) { throw new Exception($"Getting data for more than 2 symbols! {string.Join(",", data.Keys.Select(symbol => symbol))}"); } if (UniverseManager.Count != 3) { throw new Exception($"Expecting 3 universes (chain, continuous and user defined) but have {UniverseManager.Count}"); } if (!Portfolio.Invested) { Buy(_futureContract.Symbol, 1); Buy(_continuousContract.Mapped, 1); RemoveSecurity(_futureContract.Symbol); RemoveSecurity(_continuousContract.Symbol); _ended = true; } } public override void OnOrderEvent(OrderEvent orderEvent) { if (orderEvent.Status == OrderStatus.Filled) { Log($"{orderEvent}"); } } public override void OnSecuritiesChanged(SecurityChanges changes) { Debug($"{Time}-{changes}"); if (changes.AddedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol) || changes.RemovedSecurities.Any(security => security.Symbol != _continuousContract.Symbol && security.Symbol != _futureContract.Symbol)) { throw new Exception($"We got an unexpected security changes {changes}"); } } /// /// 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 Language[] Languages { get; } = { Language.CSharp }; /// /// Data Points count of all timeslices of algorithm /// public long DataPoints => 59; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 0; /// /// 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 Trades", "3"}, {"Average Win", "0%"}, {"Average Loss", "-0.03%"}, {"Compounding Annual Return", "-2.503%"}, {"Drawdown", "0.000%"}, {"Expectancy", "-1"}, {"Net Profit", "-0.032%"}, {"Sharpe Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "100%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0"}, {"Beta", "0"}, {"Annual Standard Deviation", "0"}, {"Annual Variance", "0"}, {"Information Ratio", "-0.678"}, {"Tracking Error", "0.243"}, {"Treynor Ratio", "0"}, {"Total Fees", "$7.40"}, {"Estimated Strategy Capacity", "$2100000.00"}, {"Lowest Capacity Asset", "ES VMKLFZIH2MTD"}, {"Fitness Score", "0.419"}, {"Kelly Criterion Estimate", "0"}, {"Kelly Criterion Probability Value", "0"}, {"Sortino Ratio", "79228162514264337593543950335"}, {"Return Over Maximum Drawdown", "-81.557"}, {"Portfolio Turnover", "0.837"}, {"Total Insights Generated", "0"}, {"Total Insights Closed", "0"}, {"Total Insights Analysis Completed", "0"}, {"Long Insight Count", "0"}, {"Short Insight Count", "0"}, {"Long/Short Ratio", "100%"}, {"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%"}, {"OrderListHash", "68775c18eb40c1bde212653faec4016e"} }; } }