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quantconnect--lean/Algorithm.Framework/Alphas/EmaCrossAlphaModel.cs
T
Ricardo Andrés Marino Rojas cde4743ca7
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Warm up EmaCrossAlphaModel indicators (#6270)
* Warm up EmaCrossAlphaModel

Warm Up EmaCrossAlphaModel indicators

* Fix regression test bug

When using the default `EmaCrossAlphaModel()` the period of both indicators to be ready is bigger than the difference between the start date and the end date of the algorithm. Then, as the algorithm didn't warm up the data both indicators of EmaCrossAlpha never were ready, but now as the model warms up the data both indicators are ready so we get different statistics

* Requested change

* Fix unit tests

As there wasn't items in `AddedSecurities`, when trying to remove the items in ´RemovedSecurities´ there was nothing to remove because there was never a security in `_symbolDataBySymbol`. That's why, in order to test, the behavior of `EmaCrossAlphaModel` when removing a security we need to first add one to then remove it.

* Requested changes in Python

- Requested changes in Python
- Nit changes

* Nit change

* Requested Changes

* Add RemoveConsolidators() method in Python version
2022-04-01 12:15:35 -03:00

192 lines
8.0 KiB
C#

/*
* 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 System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Data.Consolidators;
using QuantConnect.Indicators;
using QuantConnect.Securities;
namespace QuantConnect.Algorithm.Framework.Alphas
{
/// <summary>
/// Alpha model that uses an EMA cross to create insights
/// </summary>
public class EmaCrossAlphaModel : AlphaModel
{
private readonly int _fastPeriod;
private readonly int _slowPeriod;
private readonly Resolution _resolution;
private readonly int _predictionInterval;
/// <summary>
/// This is made protected for testing purposes
/// </summary>
protected readonly Dictionary<Symbol, SymbolData> SymbolDataBySymbol;
/// <summary>
/// Initializes a new instance of the <see cref="EmaCrossAlphaModel"/> class
/// </summary>
/// <param name="fastPeriod">The fast EMA period</param>
/// <param name="slowPeriod">The slow EMA period</param>
/// <param name="resolution">The resolution of data sent into the EMA indicators</param>
public EmaCrossAlphaModel(
int fastPeriod = 12,
int slowPeriod = 26,
Resolution resolution = Resolution.Daily
)
{
_fastPeriod = fastPeriod;
_slowPeriod = slowPeriod;
_resolution = resolution;
_predictionInterval = fastPeriod;
SymbolDataBySymbol = new Dictionary<Symbol, SymbolData>();
Name = $"{nameof(EmaCrossAlphaModel)}({fastPeriod},{slowPeriod},{resolution})";
}
/// <summary>
/// Updates this alpha model with the latest data from the algorithm.
/// This is called each time the algorithm receives data for subscribed securities
/// </summary>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="data">The new data available</param>
/// <returns>The new insights generated</returns>
public override IEnumerable<Insight> Update(QCAlgorithm algorithm, Slice data)
{
var insights = new List<Insight>();
foreach (var symbolData in SymbolDataBySymbol.Values)
{
if (symbolData.Fast.IsReady && symbolData.Slow.IsReady)
{
var insightPeriod = _resolution.ToTimeSpan().Multiply(_predictionInterval);
if (symbolData.FastIsOverSlow)
{
if (symbolData.Slow > symbolData.Fast)
{
insights.Add(Insight.Price(symbolData.Symbol, insightPeriod, InsightDirection.Down));
}
}
else if (symbolData.SlowIsOverFast)
{
if (symbolData.Fast > symbolData.Slow)
{
insights.Add(Insight.Price(symbolData.Symbol, insightPeriod, InsightDirection.Up));
}
}
}
symbolData.FastIsOverSlow = symbolData.Fast > symbolData.Slow;
}
return insights;
}
/// <summary>
/// Event fired each time the we add/remove securities from the data feed
/// </summary>
/// <param name="algorithm">The algorithm instance that experienced the change in securities</param>
/// <param name="changes">The security additions and removals from the algorithm</param>
public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
{
foreach (var added in changes.AddedSecurities)
{
SymbolData symbolData;
if (!SymbolDataBySymbol.TryGetValue(added.Symbol, out symbolData))
{
SymbolDataBySymbol[added.Symbol] = new SymbolData(added, _fastPeriod, _slowPeriod, algorithm, _resolution);
}
else
{
// a security that was already initialized was re-added, reset the indicators
symbolData.Fast.Reset();
symbolData.Slow.Reset();
}
}
foreach (var removed in changes.RemovedSecurities)
{
SymbolData symbolData;
if (SymbolDataBySymbol.TryGetValue(removed.Symbol, out symbolData))
{
// clean up our consolidators
symbolData.RemoveConsolidators();
SymbolDataBySymbol.Remove(removed.Symbol);
}
}
}
/// <summary>
/// Contains data specific to a symbol required by this model
/// </summary>
public class SymbolData
{
private readonly QCAlgorithm _algorithm;
private readonly IDataConsolidator _fastConsolidator;
private readonly IDataConsolidator _slowConsolidator;
private readonly ExponentialMovingAverage _fast;
private readonly ExponentialMovingAverage _slow;
private readonly Security _security;
public Symbol Symbol => _security.Symbol;
public ExponentialMovingAverage Fast => _fast;
public ExponentialMovingAverage Slow => _slow;
/// <summary>
/// True if the fast is above the slow, otherwise false.
/// This is used to prevent emitting the same signal repeatedly
/// </summary>
public bool FastIsOverSlow { get; set; }
public bool SlowIsOverFast => !FastIsOverSlow;
public SymbolData(
Security security,
int fastPeriod,
int slowPeriod,
QCAlgorithm algorithm,
Resolution resolution)
{
_algorithm = algorithm;
_security = security;
_fastConsolidator = algorithm.ResolveConsolidator(security.Symbol, resolution);
_slowConsolidator = algorithm.ResolveConsolidator(security.Symbol, resolution);
algorithm.SubscriptionManager.AddConsolidator(security.Symbol, _fastConsolidator);
algorithm.SubscriptionManager.AddConsolidator(security.Symbol, _slowConsolidator);
// create fast/slow EMAs
_fast = new ExponentialMovingAverage(security.Symbol, fastPeriod, ExponentialMovingAverage.SmoothingFactorDefault(fastPeriod));
_slow = new ExponentialMovingAverage(security.Symbol, slowPeriod, ExponentialMovingAverage.SmoothingFactorDefault(slowPeriod));
algorithm.RegisterIndicator(security.Symbol, _fast, _fastConsolidator);
algorithm.RegisterIndicator(security.Symbol, _slow, _slowConsolidator);
algorithm.WarmUpIndicator(security.Symbol, _fast, resolution);
algorithm.WarmUpIndicator(security.Symbol, _slow, resolution);
}
/// <summary>
/// Remove Fast and Slow consolidators
/// </summary>
public void RemoveConsolidators()
{
_algorithm.SubscriptionManager.RemoveConsolidator(Symbol, _fastConsolidator);
_algorithm.SubscriptionManager.RemoveConsolidator(Symbol, _slowConsolidator);
}
}
}
}