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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*/
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using System;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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using System.Collections.Generic;
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using QuantConnect.Securities.Future;
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using QuantConnect.Data.UniverseSelection;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm using and testing HSI futures and index
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/// </summary>
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public class HSIFutureHourRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private int _symbolChangeEvent;
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private Symbol _contractSymbol;
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private Symbol _index;
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private Symbol _futureSymbol;
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/// <summary>
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/// The data resolution
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/// </summary>
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protected virtual Resolution Resolution => Resolution.Hour;
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/// <summary>
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/// Initialize your algorithm and add desired assets.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 20);
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SetEndDate(2013, 10, 30);
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SetAccountCurrency("HKD");
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SetTimeZone(TimeZones.HongKong);
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UniverseSettings.Resolution = Resolution;
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_index = AddIndex("HSI", Resolution).Symbol;
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var future = AddFuture(Futures.Indices.HangSeng, Resolution);
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future.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
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_futureSymbol = future.Symbol;
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var seeder = new FuncSecuritySeeder(GetLastKnownPrices);
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SetSecurityInitializer(security => seeder.SeedSecurity(security));
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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="data">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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foreach (var changedEvent in slice.SymbolChangedEvents.Values)
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{
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Debug($"{Time} - SymbolChanged event: {changedEvent}");
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if (Time.TimeOfDay != TimeSpan.Zero)
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{
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throw new RegressionTestException($"{Time} unexpected symbol changed event {changedEvent}!");
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}
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_symbolChangeEvent++;
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}
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if (!Portfolio.Invested)
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{
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foreach (var chain in slice.FutureChains)
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{
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// find the front contract expiring no earlier than in 90 days
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var contract = (
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from futuresContract in chain.Value.OrderBy(x => x.Expiry)
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select futuresContract
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).FirstOrDefault();
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// if found, trade it
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if (contract != null)
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{
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_contractSymbol = contract.Symbol;
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MarketOrder(_contractSymbol, 1);
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}
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}
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}
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else
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{
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Liquidate();
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (_symbolChangeEvent != 1)
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{
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throw new RegressionTestException($"Got no expected symbol changed event count {_symbolChangeEvent}!");
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}
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// Get the margin requirements
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var buyingPowerModel = Securities[_contractSymbol].BuyingPowerModel;
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var futureMarginModel = buyingPowerModel as FutureMarginModel;
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if (buyingPowerModel == null)
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{
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throw new RegressionTestException($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
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}
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var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
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var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
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var initialIntraday = futureMarginModel.InitialIntradayMarginRequirement;
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var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
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var lastDataFuture = Securities[_futureSymbol].GetLastData();
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if (lastDataFuture == null || (lastDataFuture.EndTime - lastDataFuture.Time) != TimeSpan.FromHours(Resolution == Resolution.Hour ? 1 : 7.25)
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|| lastDataFuture.EndTime.Date != lastDataFuture.Time.Date)
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{
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throw new RegressionTestException($"Unexpected data for symbol {_futureSymbol}!");
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}
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var lastDataIndex = Securities[_index].GetLastData();
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if (lastDataIndex == null || (lastDataIndex.EndTime - lastDataIndex.Time) != TimeSpan.FromHours(Resolution == Resolution.Hour ? 1 : 6.5)
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|| lastDataFuture.EndTime.Date != lastDataFuture.Time.Date)
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{
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throw new RegressionTestException($"Unexpected data for symbol {_index}!");
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}
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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foreach (var addedSecurity in changes.AddedSecurities)
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{
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if (addedSecurity.Symbol.SecurityType == SecurityType.Future
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&& !addedSecurity.Symbol.IsCanonical()
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&& !addedSecurity.HasData)
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{
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throw new RegressionTestException($"Future contracts did not work up as expected: {addedSecurity.Symbol}");
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}
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}
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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 => 654;
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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 virtual int AlgorithmHistoryDataPoints => 133;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public virtual 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", "44"},
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{"Average Win", "3.60%"},
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{"Average Loss", "-2.01%"},
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{"Compounding Annual Return", "-86.799%"},
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{"Drawdown", "21.100%"},
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{"Expectancy", "-0.118"},
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{"Start Equity", "100000"},
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{"End Equity", "94080"},
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{"Net Profit", "-5.920%"},
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{"Sharpe Ratio", "-0.569"},
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{"Sortino Ratio", "-0.673"},
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{"Probabilistic Sharpe Ratio", "36.148%"},
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{"Loss Rate", "68%"},
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{"Win Rate", "32%"},
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{"Profit-Loss Ratio", "1.79"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "1.109"},
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{"Annual Variance", "1.231"},
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{"Information Ratio", "-0.563"},
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{"Tracking Error", "1.109"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$1520.00"},
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{"Estimated Strategy Capacity", "$3400000.00"},
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{"Lowest Capacity Asset", "HSI VL6DN7UV65S9"},
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{"Portfolio Turnover", "4585.54%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "b51907531791771ca92599e32ce2c2f8"}
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};
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}
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}
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