chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System;
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using QuantConnect.Data;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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using QuantConnect.Brokerages;
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using QuantConnect.Data.Market;
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using System.Collections.Generic;
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using QuantConnect.Securities.CryptoFuture;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Daily regression algorithm trading ADAUSDT binance futures long and short asserting the behavior
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/// </summary>
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public class CryptoFutureHourlyMarginInterestRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Dictionary<Symbol, int> _interestPerSymbol = new();
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private decimal _amountAfterTrade;
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private CryptoFuture _adaUsdt;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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Initialize(Resolution.Hour);
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}
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protected virtual void Initialize(Resolution resolution)
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{
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SetStartDate(2022, 12, 12);
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SetEndDate(2022, 12, 13);
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SetTimeZone(NodaTime.DateTimeZone.Utc);
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SetBrokerageModel(BrokerageName.BinanceCoinFutures, AccountType.Margin);
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_adaUsdt = AddCryptoFuture("ADAUSDT", resolution);
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// Default USD cash, set 1M but it wont be used
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SetCash(1000000);
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// the amount of USDT we need to hold to trade 'ADAUSDT'
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_adaUsdt.QuoteCurrency.SetAmount(200);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice slice)
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{
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var interestRates = slice.Get<MarginInterestRate>();
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foreach (var interestRate in interestRates)
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{
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_interestPerSymbol.TryGetValue(interestRate.Key, out var count);
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_interestPerSymbol[interestRate.Key] = ++count;
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var cachedInterestRate = Securities[interestRate.Key].Cache.GetData<MarginInterestRate>();
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if (cachedInterestRate != interestRate.Value)
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{
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throw new RegressionTestException($"Unexpected cached margin interest rate for {interestRate.Key}!");
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}
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}
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if(interestRates.Count != slice.MarginInterestRates.Count)
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{
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throw new RegressionTestException($"Unexpected cached margin interest rate data!");
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}
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if (Portfolio.Invested)
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{
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return;
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}
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Buy(_adaUsdt.Symbol, 1000);
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_amountAfterTrade = Portfolio.CashBook["USDT"].Amount;
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}
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public override void OnEndOfAlgorithm()
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{
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if (!_interestPerSymbol.TryGetValue(_adaUsdt.Symbol, out var count) || count != 1)
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{
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throw new RegressionTestException($"Unexpected interest rate count {count}");
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}
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// negative because we are long. Rate * Value * Application Count
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var expectedFundingRateDifference = - (0.0001m * _adaUsdt.Holdings.HoldingsValue * 3);
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var finalCash = Portfolio.CashBook["USDT"].Amount;
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if (Math.Abs(finalCash - (_amountAfterTrade + expectedFundingRateDifference)) > Math.Abs(expectedFundingRateDifference * 0.05m))
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{
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throw new RegressionTestException($"Unexpected interest rate count {Portfolio.CashBook["USDT"].Amount}");
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug(Time + " " + orderEvent);
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public virtual long DataPoints => 50;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "1000200"},
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{"End Equity", "1000207.90"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.15"},
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{"Estimated Strategy Capacity", "$410000000.00"},
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{"Lowest Capacity Asset", "ADAUSDT 18R"},
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{"Portfolio Turnover", "0.02%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "f3d491f943932e64bc38b85d74eb5129"}
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};
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}
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}
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