/* * 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.Data; using QuantConnect.Data.Consolidators; using QuantConnect.Indicators; using QuantConnect.Interfaces; namespace QuantConnect.Algorithm.CSharp { /// /// This algorithm reproduces GH issue 2404, exception: `This is a forward only indicator` /// public class WarmupIndicatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private Symbol _spy; /// /// 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, 11, 1); SetEndDate(2013, 12, 10); //Set End Date SetWarmup(TimeSpan.FromDays(30)); _spy = AddEquity("SPY", Resolution.Daily).Symbol; var renkoConsolidator = new ClassicRenkoConsolidator(2m); renkoConsolidator.DataConsolidated += (sender, consolidated) => { if (IsWarmingUp) return; if (!Portfolio.Invested) { SetHoldings(_spy, 1.0); } Log($"CLOSE - {consolidated.Time:o} - {consolidated.Open} {consolidated.Close}"); }; var sma = new SimpleMovingAverage("SMA", 3); RegisterIndicator(_spy, sma, renkoConsolidator); } /// /// 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) { } /// /// 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 => 397; /// /// 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", "1"}, {"Average Win", "0%"}, {"Average Loss", "0%"}, {"Compounding Annual Return", "11.962%"}, {"Drawdown", "1.200%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "101236.75"}, {"Net Profit", "1.237%"}, {"Sharpe Ratio", "1.636"}, {"Sortino Ratio", "3.633"}, {"Probabilistic Sharpe Ratio", "62.183%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0.001"}, {"Beta", "0.425"}, {"Annual Standard Deviation", "0.047"}, {"Annual Variance", "0.002"}, {"Information Ratio", "-1.856"}, {"Tracking Error", "0.054"}, {"Treynor Ratio", "0.18"}, {"Total Fees", "$3.23"}, {"Estimated Strategy Capacity", "$810000000.00"}, {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"}, {"Portfolio Turnover", "2.48%"}, {"Drawdown Recovery", "10"}, {"OrderListHash", "be8d7533a3c80d8c768d51a5d5098143"} }; } }