wehub-resource-sync
239 lines
10 KiB
C#
239 lines
10 KiB
C#
/*
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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.Market;
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using QuantConnect.Interfaces;
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using QuantConnect.Indicators;
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using QuantConnect.Data;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression test to check custom indicators warms up properly
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/// when one of them define WarmUpPeriod parameter and the other doesn't
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/// </summary>
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public class CustomWarmUpPeriodIndicatorAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private CSMANotWarmUp _customNotWarmUp;
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private CSMAWithWarmUp _customWarmUp;
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private SimpleMovingAverage _customNotInherit;
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private SimpleMovingAverage _duplicateSMA;
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public override void Initialize()
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{
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SetStartDate(2013, 10, 7);
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SetEndDate(2013, 10, 11);
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AddEquity("SPY", Resolution.Second);
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// Create two custom indicators, where one of them defines WarmUpPeriod parameter
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_customNotWarmUp = new CSMANotWarmUp("_customNotWarmUp", 60);
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_customWarmUp = new CSMAWithWarmUp("_customWarmUp", 60);
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_customNotInherit = new SimpleMovingAverage("_customNotInherit", 60);
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// using 2nd SMA to match counterpart python algorithm ( CustomSMA + csharpIndicator )
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// so that AlgorithmHistoryDataPoints are the same in both
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_duplicateSMA = new SimpleMovingAverage("_duplicateSMA", 60);
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// Register the daily data of "SPY" to automatically update both indicators
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RegisterIndicator("SPY", _customWarmUp, Resolution.Minute);
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RegisterIndicator("SPY", _customNotWarmUp, Resolution.Minute);
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RegisterIndicator("SPY", _customNotInherit, Resolution.Minute);
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RegisterIndicator("SPY", _duplicateSMA, Resolution.Minute);
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// Warm up _customWarmUp indicator
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WarmUpIndicator("SPY", _customWarmUp, Resolution.Minute);
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// Check _customWarmUp indicator has already been warmed up with the requested data
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if (!_customWarmUp.IsReady)
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{
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throw new RegressionTestException("_customWarmUp indicator was expected to be ready");
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}
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if (_customWarmUp.Samples != 60)
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{
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throw new RegressionTestException("_customWarmUp indicator was expected to have processed 60 datapoints already");
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}
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// Try to warm up _customNotWarmUp indicator. It's expected from LEAN to skip the warm up process
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// because this indicator doesn't implement IIndicatorWarmUpPeriodProvider
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WarmUpIndicator("SPY", _customNotWarmUp, Resolution.Minute);
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// Check _customNotWarmUp indicator is not ready, because the warm up process was skipped
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if (_customNotWarmUp.IsReady)
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{
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throw new RegressionTestException("_customNotWarmUp indicator wasn't expected to be warmed up");
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}
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WarmUpIndicator("SPY", _customNotInherit, Resolution.Minute);
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// Check _customWarmUp indicator has already been warmed up with the requested data
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if (!_customNotInherit.IsReady)
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{
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throw new RegressionTestException("_customNotInherit indicator was expected to be ready");
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}
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if (_customNotInherit.Samples != 60)
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{
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throw new RegressionTestException("_customNotInherit indicator was expected to have processed 60 datapoints already");
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}
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WarmUpIndicator("SPY", _duplicateSMA, Resolution.Minute);
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// Check _customWarmUp indicator has already been warmed up with the requested data
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if (!_duplicateSMA.IsReady)
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{
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throw new RegressionTestException("_duplicateSMA indicator was expected to be ready");
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}
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if (_duplicateSMA.Samples != 60)
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{
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throw new RegressionTestException("_duplicateSMA indicator was expected to have processed 60 datapoints already");
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}
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}
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested)
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{
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SetHoldings("SPY", 1);
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}
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if (Time.Second == 0)
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{
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// Compute the difference between the indicators values
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var diff = Math.Abs(_customNotWarmUp.Current.Value - _customWarmUp.Current.Value);
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diff += Math.Abs(_customNotInherit.Current.Value - _customNotWarmUp.Current.Value);
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diff += Math.Abs(_customNotInherit.Current.Value - _customWarmUp.Current.Value);
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diff += Math.Abs(_duplicateSMA.Current.Value - _customWarmUp.Current.Value);
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diff += Math.Abs(_duplicateSMA.Current.Value - _customNotWarmUp.Current.Value);
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diff += Math.Abs(_duplicateSMA.Current.Value - _customNotInherit.Current.Value);
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// Check _customNotWarmUp indicator is ready when the number of samples is bigger than its period
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if (_customNotWarmUp.IsReady != (_customNotWarmUp.Samples >= 60))
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{
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throw new RegressionTestException("_customNotWarmUp indicator was expected to be ready when the number of samples were bigger that its WarmUpPeriod parameter");
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}
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// Check their values are the same when both are ready
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if (diff > 1e-10m && _customNotWarmUp.IsReady && _customWarmUp.IsReady)
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{
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throw new RegressionTestException($"The values of the indicators are not the same. The difference is {diff}");
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}
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}
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}
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/// <summary>
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/// Custom implementation of SimpleMovingAverage.
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/// Represents the traditional simple moving average indicator (SMA) without WarmUpPeriod parameter defined
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/// </summary>
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private class CSMANotWarmUp : IndicatorBase<IBaseData>
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{
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private Queue<IBaseData> _queue;
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private int _period;
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public CSMANotWarmUp(string name, int period)
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: base(name)
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{
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_queue = new Queue<IBaseData>();
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_period = period;
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}
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public override bool IsReady => _queue.Count == _period;
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protected override decimal ComputeNextValue(IBaseData input)
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{
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_queue.Enqueue(input);
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if (_queue.Count > _period)
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{
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_queue.Dequeue();
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}
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var items = (_queue.ToArray());
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var sum = 0m;
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Array.ForEach(items, i => sum += i.Value);
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return sum / _queue.Count;
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}
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}
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/// <summary>
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/// Custom implementation of SimpleMovingAverage.
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/// Represents the traditional simple moving average indicator (SMA) with WarmUpPeriod defined
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/// </summary>
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private class CSMAWithWarmUp : CSMANotWarmUp, IIndicatorWarmUpPeriodProvider
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{
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public CSMAWithWarmUp(string name, int period)
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: base(name, period)
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{
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WarmUpPeriod = period;
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}
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public int WarmUpPeriod { get; private set; }
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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, 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 long DataPoints => 234043;
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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 => 360;
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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 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", "272.157%"},
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{"Drawdown", "2.200%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "101694.38"},
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{"Net Profit", "1.694%"},
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{"Sharpe Ratio", "8.863"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "67.460%"},
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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", "-0.003"},
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{"Beta", "0.998"},
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{"Annual Standard Deviation", "0.222"},
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{"Annual Variance", "0.049"},
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{"Information Ratio", "-14.534"},
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{"Tracking Error", "0.001"},
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{"Treynor Ratio", "1.972"},
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{"Total Fees", "$3.45"},
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{"Estimated Strategy Capacity", "$310000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "19.96%"},
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{"Drawdown Recovery", "2"},
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{"OrderListHash", "8c925e7c6c10ff1da3a40669accba91a"}
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};
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}
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}
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