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 System.Collections.Generic;
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm to validate Security.Session functionality.
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/// Verifies that daily session bars (Open, High, Low, Close, Volume) are correctly
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/// </summary>
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public class SecuritySessionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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protected int ProcessedDataCount { get; set; }
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protected bool SecurityWasRemoved { get; set; }
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protected decimal Open { get; set; }
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protected decimal High { get; set; }
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protected decimal Low { get; set; }
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protected decimal Close { get; set; }
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protected decimal Volume { get; set; }
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protected Security Security { get; set; }
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protected virtual Resolution Resolution => Resolution.Hour;
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protected virtual bool DailyPreciseEndTime => true;
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protected virtual bool ExtendedMarketHours => false;
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protected TradeBar PreviousSessionBar { get; set; }
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protected DateTime CurrentDate { get; set; }
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/// <summary>
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/// Initialise the data
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/// </summary>
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public override void Initialize()
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{
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AddSecurityInitializer((security) =>
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{
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// activate session tracking
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security.Session.Size = 3;
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});
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Settings.DailyPreciseEndTime = DailyPreciseEndTime;
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InitializeSecurity();
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// Check initial session values
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var session = Security.Session;
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if (session == null)
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{
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throw new RegressionTestException("Security.Session is null");
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}
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if (session.Open != 0
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|| session.High != 0
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|| session.Low != 0
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|| session.Close != 0
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|| session.Volume != 0
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|| session.OpenInterest != 0)
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{
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throw new RegressionTestException("Session should start with all zero values.");
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}
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ProcessedDataCount = 0;
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Low = decimal.MaxValue;
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CurrentDate = StartDate;
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ConfigureSchedule();
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}
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public virtual void InitializeSecurity()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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Security = AddEquity("SPY", Resolution, extendedMarketHours: ExtendedMarketHours);
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}
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protected virtual void ConfigureSchedule()
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{
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Schedule.On(DateRules.EveryDay(), TimeRules.AfterMarketClose(Security.Symbol, 1), ValidateSessionBars);
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}
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protected virtual void ValidateSessionBars()
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{
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if (ProcessedDataCount == 0)
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{
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return;
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}
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var session = Security.Session;
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// At this point the data was consolidated (market close)
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// Save previous session bar
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PreviousSessionBar = new TradeBar(CurrentDate, Security.Symbol, Open, High, Low, Close, Volume);
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if (SecurityWasRemoved)
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{
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PreviousSessionBar = null;
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SecurityWasRemoved = false;
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return;
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}
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// Check current session values
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if (session.Open != Open
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|| session.High != High
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|| session.Low != Low
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|| session.Close != Close
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|| session.Volume != Volume)
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{
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throw new RegressionTestException("Mismatch in current session bar (OHLCV)");
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}
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}
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protected virtual bool IsWithinMarketHours(DateTime currentDateTime)
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{
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var marketOpen = Security.Exchange.Hours.GetNextMarketOpen(currentDateTime.Date, false).TimeOfDay;
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var marketClose = Security.Exchange.Hours.GetNextMarketClose(currentDateTime.Date, false).TimeOfDay;
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var currentTime = currentDateTime.TimeOfDay;
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return (marketOpen < currentTime && currentTime <= marketClose) || (!DailyPreciseEndTime && Resolution == Resolution.Daily);
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}
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public override void OnData(Slice slice)
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{
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if (ProcessedDataCount == 0)
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{
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CurrentDate = slice.Time;
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}
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if (!IsWithinMarketHours(slice.Time) || !slice.ContainsKey(Security.Symbol))
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{
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// Skip data outside market hours
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return;
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}
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// Accumulate data within regular market hours
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// to later compare against the Session values
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AccumulateSessionData(slice);
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ProcessedDataCount++;
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}
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protected virtual void AccumulateSessionData(Slice slice)
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{
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var symbol = Security.Symbol;
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if (CurrentDate.Date == slice.Time.Date)
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{
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// Same trading day
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if (Open == 0)
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{
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Open = slice[symbol].Open;
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}
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High = Math.Max(High, slice[symbol].High);
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Low = Math.Min(Low, slice[symbol].Low);
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Close = slice[symbol].Close;
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Volume += slice[symbol].Volume;
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}
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else
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{
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// New trading day
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if (PreviousSessionBar != null)
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{
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var session = Security.Session;
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if (PreviousSessionBar.Open != session[1].Open
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|| PreviousSessionBar.High != session[1].High
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|| PreviousSessionBar.Low != session[1].Low
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|| PreviousSessionBar.Close != session[1].Close
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|| PreviousSessionBar.Volume != session[1].Volume)
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{
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throw new RegressionTestException("Mismatch in previous session bar (OHLCV)");
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}
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}
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// This is the first data point of the new session
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Open = slice[symbol].Open;
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Close = slice[symbol].Close;
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High = slice[symbol].High;
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Low = slice[symbol].Low;
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Volume = slice[symbol].Volume;
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CurrentDate = slice.Time;
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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 virtual List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
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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 => 78;
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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 => 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", "0"},
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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", "100000"},
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{"End Equity", "100000"},
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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", "-8.91"},
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{"Tracking Error", "0.223"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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