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Fix bug when consolidating hourly bars into daily ones (#8442)
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* First draft of the solution

* Add regression tests

* Improve solution and add unit test

* Address suggestions

* Improve unit tests

* Nit changes

* Fix regression algorithms
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Marinovsky authored Dec 6, 2024
1 parent 22e0491 commit 81d7774
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/*
* 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 QuantConnect.Data;
using QuantConnect.Indicators;
using QuantConnect.Interfaces;
using System;
using System.Collections.Generic;
using QuantConnect.Data.Market;

namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This regression algorithm asserts the consolidated US equity daily bars from the hour bars exactly matches
/// the daily bars returned from the database
/// </summary>
public class ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _spy;
private RelativeStrengthIndex _rsi;
private RelativeStrengthIndex _rsiTimeDelta;
private Dictionary<DateTime, decimal> _values = new();
private int _count;
private bool _indicatorsCompared;

public override void Initialize()
{
SetStartDate(2020, 5, 1);
SetEndDate(2020, 6, 5);

_spy = AddEquity("SPY", Resolution.Hour).Symbol;

// We will use these two indicators to compare the daily consolidated bars equals
// the ones returned from the database. We use this specific type of indicator as
// it depends on its previous values. Thus, if at some point the bars received by
// the indicators differ, so will their final values
_rsi = new RelativeStrengthIndex("FIRST", 15, MovingAverageType.Wilders);
RegisterIndicator(_spy, _rsi, Resolution.Daily, selector: (bar) =>
{
var tradeBar = (TradeBar)bar;
return (tradeBar.Close + tradeBar.Open) / 2;
});

// We won't register this indicator as we will update it manually at the end of the
// month, so that we can compare the values of the indicator that received consolidated
// bars and the values of this one
_rsiTimeDelta = new RelativeStrengthIndex("SECOND" ,15, MovingAverageType.Wilders);
}

public override void OnData(Slice slice)
{
if (IsWarmingUp) return;

if (slice.ContainsKey(_spy) && slice[_spy] != null)
{
if (Time.Month == EndDate.Month)
{
var history = History(_spy, _count, Resolution.Daily);
foreach (var bar in history)
{
var time = bar.EndTime.Date;
var average = (bar.Close + bar.Open) / 2;
_rsiTimeDelta.Update(bar.EndTime, average);
if (_rsiTimeDelta.Current.Value != _values[time])
{
throw new RegressionTestException($"Both {_rsi.Name} and {_rsiTimeDelta.Name} should have the same values, but they differ. {_rsi.Name}: {_values[time]} | {_rsiTimeDelta.Name}: {_rsiTimeDelta.Current.Value}");
}
}
_indicatorsCompared = true;
Quit();
}
else
{
_values[Time.Date] = _rsi.Current.Value;

// Since the symbol resolution is hour and the symbol is equity, we know the last bar received in a day will
// be at the market close, this is 16h. We need to count how many daily bars were consolidated in order to know
// how many we need to request from the history
if (Time.Hour == 16)
{
_count++;
}
}
}
}

public override void OnEndOfAlgorithm()
{
if (!_indicatorsCompared)
{
throw new RegressionTestException($"Indicators {_rsi.Name} and {_rsiTimeDelta.Name} should have been compared, but they were not. Please make sure the indicators are getting SPY data");
}
}

/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;

/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };

/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 290;

/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 20;

/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;

/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100000"},
{"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", "-5.215"},
{"Tracking Error", "0.159"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}
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# 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.

from AlgorithmImports import *

### <summary>
### This regression algorithm asserts the consolidated US equity daily bars from the hour bars exactly matches
### the daily bars returned from the database
### </summary>
class ConsolidateHourBarsIntoDailyBarsRegressionAlgorithm(QCAlgorithm):
def initialize(self):
self.set_start_date(2020, 5, 1)
self.set_end_date(2020, 6, 5)

self.spy = self.add_equity("SPY", Resolution.HOUR).symbol

# We will use these two indicators to compare the daily consolidated bars equals
# the ones returned from the database. We use this specific type of indicator as
# it depends on its previous values. Thus, if at some point the bars received by
# the indicators differ, so will their final values
self._rsi = RelativeStrengthIndex("First", 15, MovingAverageType.WILDERS)
self.register_indicator(self.spy, self._rsi, Resolution.DAILY, selector= lambda bar: (bar.close + bar.open) / 2)

# We won't register this indicator as we will update it manually at the end of the
# month, so that we can compare the values of the indicator that received consolidated
# bars and the values of this one
self._rsi_timedelta = RelativeStrengthIndex("Second", 15, MovingAverageType.WILDERS)
self._values = {}
self.count = 0;
self._indicators_compared = False;

def on_data(self, data: Slice):
if self.is_warming_up:
return

if data.contains_key(self.spy) and data[self.spy] != None:
if self.time.month == self.end_date.month:
history = self.history[TradeBar](self.spy, self.count, Resolution.DAILY)
for bar in history:
time = bar.end_time.strftime('%Y-%m-%d')
average = (bar.close + bar.open) / 2
self._rsi_timedelta.update(bar.end_time, average)
if self._rsi_timedelta.current.value != self._values[time]:
raise Exception(f"Both {self._rsi.name} and {self._rsi_timedelta.name} should have the same values, but they differ. {self._rsi.name}: {self._values[time]} | {self._rsi_timedelta.name}: {self._rsi_timedelta.current.value}")
self._indicators_compared = True
self.quit()
else:
time = self.time.strftime('%Y-%m-%d')
self._values[time] = self._rsi.current.value

# Since the symbol resolution is hour and the symbol is equity, we know the last bar received in a day will
# be at the market close, this is 16h. We need to count how many daily bars were consolidated in order to know
# how many we need to request from the history
if self.time.hour == 16:
self.count += 1

def on_end_of_algorithm(self):
if not self._indicators_compared:
raise Exception(f"Indicators {self._rsi.name} and {self._rsi_timedelta.name} should have been compared, but they were not. Please make sure the indicators are getting SPY data")
7 changes: 6 additions & 1 deletion Common/Data/Consolidators/MarketHourAwareConsolidator.cs
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Expand Up @@ -132,7 +132,12 @@ public virtual void Update(IBaseData data)
{
Initialize(data);

if (_extendedMarketHours || ExchangeHours.IsOpen(data.Time, false))
// US equity hour data from the database starts at 9am but the exchange opens at 9:30am. Thus, we need to handle
// this case specifically to avoid skipping the first hourly bar. To avoid this, we assert the period is daily,
// the data resolution is hour and the exchange opens at any point in time over the data.Time to data.EndTime interval
if (_extendedMarketHours ||
ExchangeHours.IsOpen(data.Time, false) ||
(Period == Time.OneDay && (data.EndTime - data.Time == Time.OneHour) && ExchangeHours.IsOpen(data.Time, data.EndTime, false)))
{
Consolidator.Update(data);
}
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17 changes: 14 additions & 3 deletions Common/Data/Consolidators/PeriodCountConsolidatorBase.cs
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Expand Up @@ -322,10 +322,21 @@ protected DateTime GetRoundedBarTime(DateTime time)
protected DateTime GetRoundedBarTime(IBaseData inputData)
{
var potentialStartTime = GetRoundedBarTime(inputData.Time);
if(_period.HasValue && potentialStartTime + _period < inputData.EndTime)
if (_period.HasValue && potentialStartTime + _period < inputData.EndTime)
{
// whops! the end time we were giving is beyond our potential end time, so let's use the giving bars star time instead
potentialStartTime = inputData.Time;
// US equity hour bars from the database starts at 9am but the exchange opens at 9:30am. Thus, the method
// GetRoundedBarTime(inputData.Time) returns the market open of the previous day, which is not consistent
// with the given end time. For that reason we need to handle this case specifically, by calling
// GetRoundedBarTime(inputData.EndTime) as it will return our expected start time: 9:30am
if (inputData.EndTime - inputData.Time == Time.OneHour && potentialStartTime.Date < inputData.Time.Date)
{
potentialStartTime = GetRoundedBarTime(inputData.EndTime);
}
else
{
// whops! the end time we were giving is beyond our potential end time, so let's use the giving bars star time instead
potentialStartTime = inputData.Time;
}
}

return potentialStartTime;
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65 changes: 65 additions & 0 deletions Tests/Common/Data/MarketHourAwareConsolidatorTests.cs
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Expand Up @@ -117,6 +117,71 @@ public void Daily(bool strictEndTime)
Assert.AreEqual(1, latestBar.Low);
}

[Test]
public void BarIsSkippedWhenDataResolutionIsNotHourAndMarketIsClose()
{
var symbol = Symbols.SPY;
using var consolidator = new MarketHourAwareConsolidator(true, Resolution.Daily, typeof(TradeBar), TickType.Trade, false);
var consolidatedBarsCount = 0;
TradeBar latestBar = null;

consolidator.DataConsolidated += (sender, bar) =>
{
latestBar = (TradeBar)bar;
consolidatedBarsCount++;
};

var time = new DateTime(2020, 05, 01, 09, 30, 0);
// this bar will be ignored because it's during market closed hours and the bar resolution is not Hour
consolidator.Update(new TradeBar() { Time = time.Subtract(Time.OneMinute), Period = Time.OneMinute, Symbol = symbol, Open = 1 });
Assert.IsNull(latestBar);
Assert.AreEqual(0, consolidatedBarsCount);
}

[Test]
public void DailyBarCanBeConsolidatedFromHourData()
{
var symbol = Symbols.SPY;
using var consolidator = new MarketHourAwareConsolidator(true, Resolution.Daily, typeof(TradeBar), TickType.Trade, false);
var consolidatedBarsCount = 0;
TradeBar latestBar = null;

consolidator.DataConsolidated += (sender, bar) =>
{
latestBar = (TradeBar)bar;
consolidatedBarsCount++;
};

var time = new DateTime(2020, 05, 01, 09, 0, 0);
var hourBars = new List<TradeBar>()
{
new TradeBar() { Time = time, Period = Time.OneHour, Symbol = symbol, Open = 2 },
new TradeBar() { Time = time.AddHours(1), Period = Time.OneHour, Symbol = symbol, High = 200 },
new TradeBar() { Time = time.AddHours(2), Period = Time.OneHour, Symbol = symbol, Low = 0.02m },
new TradeBar() { Time = time.AddHours(3), Period = Time.OneHour, Symbol = symbol, Close = 20 },
new TradeBar() { Time = time.AddHours(4), Period = Time.OneHour, Symbol = symbol, Open = 3 },
new TradeBar() { Time = time.AddHours(5), Period = Time.OneHour, Symbol = symbol, High = 300 },
new TradeBar() { Time = time.AddHours(6), Period = Time.OneHour, Symbol = symbol, Low = 0.03m, Close = 30 },
};

foreach (var bar in hourBars)
{
consolidator.Update(bar);
}

consolidator.Scan(time.AddHours(7));

// Assert that the bar emitted
Assert.IsNotNull(latestBar);
Assert.AreEqual(time.AddHours(7), latestBar.EndTime);
Assert.AreEqual(time.AddMinutes(30), latestBar.Time);
Assert.AreEqual(1, consolidatedBarsCount);
Assert.AreEqual(2, latestBar.Open);
Assert.AreEqual(300, latestBar.High);
Assert.AreEqual(0.02, latestBar.Low);
Assert.AreEqual(30, latestBar.Close);
}

[TestCase(true)]
[TestCase(false)]
public void DailyExtendedMarketHours(bool strictEndTime)
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