/* * 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 QuantConnect.Data; using QuantConnect.Interfaces; using System.Collections.Generic; using QuantConnect.Securities.CryptoFuture; namespace QuantConnect.Algorithm.CSharp { /// /// Regression algorithm asserting DYDX Crypto Future support /// public class DYDXCryptoFuturesRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition { private CryptoFuture _cryptoFuture; /// /// 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(2026, 1, 1); SetEndDate(2026, 1, 1); SetBrokerageModel(Brokerages.BrokerageName.DYDX, AccountType.Margin); _cryptoFuture = AddCryptoFuture("BTCUSD"); } /// /// 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 (!Portfolio.Invested) { Buy("BTCUSD", 1); } else { if (Math.Abs(Portfolio.TotalFees - Portfolio.TotalHoldingsValue * 0.0005m) > 1 || Math.Abs(Portfolio.TotalFees - _cryptoFuture.Price * 0.0005m) > 1) { throw new RegressionTestException("Unexpected fees value!"); } if (Math.Abs(Portfolio.TotalHoldingsValue - _cryptoFuture.Price) > 1) { throw new RegressionTestException("Unexpected holdings value!"); } Quit(); } } /// /// 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 => 5; /// /// Data Points count of the algorithm history /// public int AlgorithmHistoryDataPoints => 15; /// /// 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", "0%"}, {"Drawdown", "0%"}, {"Expectancy", "0"}, {"Start Equity", "100000"}, {"End Equity", "99929.57"}, {"Net Profit", "0%"}, {"Sharpe Ratio", "0"}, {"Sortino Ratio", "0"}, {"Probabilistic Sharpe Ratio", "0%"}, {"Loss Rate", "0%"}, {"Win Rate", "0%"}, {"Profit-Loss Ratio", "0"}, {"Alpha", "0"}, {"Beta", "0"}, {"Annual Standard Deviation", "0"}, {"Annual Variance", "0"}, {"Information Ratio", "0"}, {"Tracking Error", "0"}, {"Treynor Ratio", "0"}, {"Total Fees", "$43.71"}, {"Estimated Strategy Capacity", "$33000.00"}, {"Lowest Capacity Asset", "BTCUSD 38Z"}, {"Portfolio Turnover", "87.48%"}, {"Drawdown Recovery", "0"}, {"OrderListHash", "637a937cda83ce88d29a3b279832401d"} }; } }