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Fix warming up bug QCAlgorithm.WarmUpIndicator() (#8431)
* First draft of the solution * Add regression tests * Nit changes * Solve root issue * Improve regression tests * Reduce duplication * Nit change * Improve implementation * Address suggestions * Address requested improvements * Nit change * Nit changes * Nit change
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Algorithm.CSharp/StochasticIndicatorWarmsUpProperlyRegressionAlgorithm.cs
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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. | ||
*/ | ||
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using QuantConnect.Data; | ||
using QuantConnect.Data.Consolidators; | ||
using QuantConnect.Indicators; | ||
using QuantConnect.Interfaces; | ||
using System; | ||
using System.Collections.Generic; | ||
using System.Linq; | ||
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namespace QuantConnect.Algorithm.CSharp | ||
{ | ||
/// <summary> | ||
/// Regression algorithm that asserts Stochastic indicator, registered with a different resolution consolidator, | ||
/// is warmed up properly by calling QCAlgorithm.WarmUpIndicator | ||
/// </summary> | ||
public class StochasticIndicatorWarmsUpProperlyRegressionAlgorithm: QCAlgorithm, IRegressionAlgorithmDefinition | ||
{ | ||
private bool _dataPointsReceived; | ||
private Symbol _spy; | ||
private RelativeStrengthIndex _rsi; | ||
private RelativeStrengthIndex _rsiHistory; | ||
private Stochastic _sto; | ||
private Stochastic _stoHistory; | ||
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public override void Initialize() | ||
{ | ||
SetStartDate(2020, 1, 1); | ||
SetEndDate(2020, 2, 1); | ||
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_spy = AddEquity("SPY", Resolution.Hour).Symbol; | ||
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var dailyConsolidator = new TradeBarConsolidator(TimeSpan.FromDays(1)); | ||
_rsi = new RelativeStrengthIndex(14, MovingAverageType.Wilders); | ||
_sto = new Stochastic("FIRST", 14, 3, 3); | ||
RegisterIndicator(_spy, _rsi, dailyConsolidator); | ||
RegisterIndicator(_spy, _sto, dailyConsolidator); | ||
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WarmUpIndicator(_spy, _rsi, TimeSpan.FromDays(1)); | ||
WarmUpIndicator(_spy, _sto, TimeSpan.FromDays(1)); | ||
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_rsiHistory = new RelativeStrengthIndex(14, MovingAverageType.Wilders); | ||
_stoHistory = new Stochastic("SECOND", 14, 3, 3); | ||
RegisterIndicator(_spy, _rsiHistory, dailyConsolidator); | ||
RegisterIndicator(_spy, _stoHistory, dailyConsolidator); | ||
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var history = History(_spy, Math.Max(_rsiHistory.WarmUpPeriod, _stoHistory.WarmUpPeriod), Resolution.Daily); | ||
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// Warm up RSI indicator | ||
foreach (var bar in history) | ||
{ | ||
_rsiHistory.Update(bar.EndTime, bar.Close); | ||
} | ||
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// Warm up STO indicator | ||
foreach (var bar in history.TakeLast(_stoHistory.WarmUpPeriod)) | ||
{ | ||
_stoHistory.Update(bar); | ||
} | ||
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var indicators = new List<IIndicator>() { _rsi, _sto, _rsiHistory, _stoHistory }; | ||
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foreach (var indicator in indicators) | ||
{ | ||
if (!indicator.IsReady) | ||
{ | ||
throw new RegressionTestException($"{indicator.Name} should be ready, but it is not. Number of samples: {indicator.Samples}"); | ||
} | ||
} | ||
} | ||
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public override void OnData(Slice slice) | ||
{ | ||
if (IsWarmingUp) return; | ||
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if (slice.ContainsKey(_spy)) | ||
{ | ||
_dataPointsReceived = true; | ||
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if (_rsi.Current.Value != _rsiHistory.Current.Value) | ||
{ | ||
throw new RegressionTestException($"Values of indicators differ: {_rsi.Name}: {_rsi.Current.Value} | {_rsiHistory.Name}: {_rsiHistory.Current.Value}"); | ||
} | ||
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if (_sto.StochK.Current.Value != _stoHistory.StochK.Current.Value) | ||
{ | ||
throw new RegressionTestException($"Stoch K values of indicators differ: {_sto.Name}.StochK: {_sto.StochK.Current.Value} | {_stoHistory.Name}.StochK: {_stoHistory.StochK.Current.Value}"); | ||
} | ||
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if (_sto.StochD.Current.Value != _stoHistory.StochD.Current.Value) | ||
{ | ||
throw new RegressionTestException($"Stoch D values of indicators differ: {_sto.Name}.StochD: {_sto.StochD.Current.Value} | {_stoHistory.Name}.StochD: {_stoHistory.StochD.Current.Value}"); | ||
} | ||
} | ||
} | ||
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public override void OnEndOfAlgorithm() | ||
{ | ||
if (!_dataPointsReceived) | ||
{ | ||
throw new Exception("No data points received"); | ||
} | ||
} | ||
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/// <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; | ||
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/// <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 }; | ||
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/// <summary> | ||
/// Data Points count of all timeslices of algorithm | ||
/// </summary> | ||
public long DataPoints => 302; | ||
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/// <summary> | ||
/// Data Points count of the algorithm history | ||
/// </summary> | ||
public int AlgorithmHistoryDataPoints => 44; | ||
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/// <summary> | ||
/// Final status of the algorithm | ||
/// </summary> | ||
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed; | ||
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/// <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", "-0.016"}, | ||
{"Tracking Error", "0.101"}, | ||
{"Treynor Ratio", "0"}, | ||
{"Total Fees", "$0.00"}, | ||
{"Estimated Strategy Capacity", "$0"}, | ||
{"Lowest Capacity Asset", ""}, | ||
{"Portfolio Turnover", "0%"}, | ||
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"} | ||
}; | ||
} | ||
} |
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Algorithm.Python/StochasticIndicatorWarmsUpProperlyRegressionAlgorithm.py
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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. | ||
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from datetime import timedelta | ||
from AlgorithmImports import * | ||
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### <summary> | ||
### Regression algorithm that asserts Stochastic indicator, registered with a different resolution consolidator, | ||
### is warmed up properly by calling QCAlgorithm.WarmUpIndicator | ||
### </summary> | ||
class StochasticIndicatorWarmsUpProperlyRegressionAlgorithm(QCAlgorithm): | ||
def initialize(self): | ||
self.set_start_date(2020, 1, 1) # monday = holiday.. | ||
self.set_end_date(2020, 2, 1) | ||
self.set_cash(100000) | ||
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self.data_points_received = False; | ||
self.spy = self.add_equity("SPY", Resolution.HOUR).symbol | ||
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self.daily_consolidator = TradeBarConsolidator(timedelta(days=1)) | ||
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self._rsi = RelativeStrengthIndex(14, MovingAverageType.WILDERS) | ||
self._sto = Stochastic("FIRST", 14, 3, 3) | ||
self.register_indicator(self.spy, self._rsi, self.daily_consolidator) | ||
self.register_indicator(self.spy, self._sto, self.daily_consolidator) | ||
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# warm_up indicator | ||
self.warm_up_indicator(self.spy, self._rsi, timedelta(days=1)) | ||
self.warm_up_indicator(self.spy, self._sto, timedelta(days=1)) | ||
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self._rsi_history = RelativeStrengthIndex(14, MovingAverageType.WILDERS) | ||
self._sto_history = Stochastic("SECOND", 14, 3, 3) | ||
self.register_indicator(self.spy, self._rsi_history, self.daily_consolidator) | ||
self.register_indicator(self.spy, self._sto_history, self.daily_consolidator) | ||
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# history warm up | ||
history = self.history[TradeBar](self.spy, max(self._rsi_history.warm_up_period, self._sto_history.warm_up_period), Resolution.DAILY) | ||
for bar in history: | ||
self._rsi_history.update(bar.end_time, bar.close) | ||
if self._rsi_history.samples == 1: | ||
continue | ||
self._sto_history.update(bar) | ||
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indicators = [self._rsi, self._sto, self._rsi_history, self._sto_history] | ||
for indicator in indicators: | ||
if not indicator.is_ready: | ||
raise Exception(f"{indicator.name} should be ready, but it is not. Number of samples: {indicator.samples}") | ||
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def on_data(self, data: Slice): | ||
if self.is_warming_up: | ||
return | ||
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if data.contains_key(self.spy): | ||
self.data_points_received = True | ||
if self._rsi.current.value != self._rsi_history.current.value: | ||
raise Exception(f"Values of indicators differ: {self._rsi.name}: {self._rsi.current.value} | {self._rsi_history.name}: {self._rsi_history.current.value}") | ||
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if self._sto.stoch_k.current.value != self._sto_history.stoch_k.current.value: | ||
raise Exception(f"Stoch K values of indicators differ: {self._sto.name}.StochK: {self._sto.stoch_k.current.value} | {self._sto_history.name}.StochK: {self._sto_history.stoch_k.current.value}") | ||
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if self._sto.stoch_d.current.value != self._sto_history.stoch_d.current.value: | ||
raise Exception(f"Stoch D values of indicators differ: {self._sto.name}.StochD: {self._sto.stoch_d.current.value} | {self._sto_history.name}.StochD: {self._sto_history.stoch_d.current.value}") | ||
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def on_end_of_algorithm(self): | ||
if not self.data_points_received: | ||
raise Exception("No data points received") |
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