[英]Calculate Exponential Moving Average on a Queue in C#
I have a simple class for calculating the moving average of values I add to it.我有一个简单的类来计算我添加到它的值的移动平均值。 I use it like this:我像这样使用它:
MovingAverage ma = new MovingAverage();
ma.push(value1);
ma.push(value2);
...
Console.Writeline(average.Average);
//the class
public class MovingAverage
{
public int Period = 5;
private Queue<double> Quotes = new Queue<double>();
public void Push(double quote)
{
if (Quotes.Count == Period)
Quotes.Dequeue();
Quotes.Enqueue(quote);
}
public void Clear()
{
Quotes.Clear();
}
public double Average { get { if (Quotes.Count == 0) return 0; return Quotes.Average(); } }
public double ExponentialMovingAverage
{
get
{
???
}
}
}
I would like to extend this class to also return the ExponentialMovingAverage.我想扩展这个类以返回 ExponentialMovingAverage。 How would you write return the Exponential Average of the Queued items in Quotes?您将如何编写返回报价中排队项目的指数平均值?
I realize you will need to add an Alpha property to the class but I'm not sure how to complete the math for the calculation.我意识到您需要在类中添加一个 Alpha 属性,但我不确定如何完成计算的数学运算。
How about with LINQ:使用 LINQ 怎么样:
return Quotes.DefaultIfEmpty()
.Aggregate((ema, nextQuote) => alpha * nextQuote + (1 - alpha) * ema);
I would point out that for real-time financial data, this is highly inefficient.我要指出的是,对于实时财务数据,这是非常低效的。 A much better way would be to cache the previous EMA value and update it on a new quote with the above (constant-time) recurrence-formula.更好的方法是缓存之前的 EMA 值并使用上述(恒定时间)重复公式在新报价上更新它。
Do do not need a queue for an Exponential Moving Average because you only need to keep track of the previous EMA.不需要指数移动平均线的队列,因为您只需要跟踪之前的 EMA。
public class ExponentialMovingAverageIndicator
{
private bool _isInitialized;
private readonly int _lookback;
private readonly double _weightingMultiplier;
private double _previousAverage;
public double Average { get; private set; }
public double Slope { get; private set; }
public ExponentialMovingAverageIndicator(int lookback)
{
_lookback = lookback;
_weightingMultiplier = 2.0/(lookback + 1);
}
public void AddDataPoint(double dataPoint)
{
if (!_isInitialized)
{
Average = dataPoint;
Slope = 0;
_previousAverage = Average;
_isInitialized = true;
return;
}
Average = ((dataPoint - _previousAverage)*_weightingMultiplier) + _previousAverage;
Slope = Average - _previousAverage;
//update previous average
_previousAverage = Average;
}
}
Here's a minimal version of @MattWolf's answer with a slightly different API, and using C# 7.这是@MattWolf 答案的最小版本,其 API 略有不同,并使用 C# 7。
public sealed class FloatExponentialMovingAverageCalculator
{
private readonly float _alpha;
private float _lastAverage = float.NaN;
public FloatExponentialMovingAverageCalculator(int lookBack) => _alpha = 2f / (lookBack + 1);
public float NextValue(float value) => _lastAverage = float.IsNaN(_lastAverage)
? value
: (value - _lastAverage)*_alpha + _lastAverage;
}
I think there's a small tweak required to @Ani's answer.我认为@Ani 的回答需要进行一些小调整。 The initial value would get set to "alpha * nextQuote" instead of just "nextQuote".初始值将设置为“alpha * nextQuote”,而不仅仅是“nextQuote”。 Easiest fix is to set the initial seed value to match the first record, then the first iteration becomes alpha * S1 + (1 - alpha) * S1:最简单的解决方法是设置初始种子值以匹配第一条记录,然后第一次迭代变为 alpha * S1 + (1 - alpha) * S1:
return Quotes
.DefaultIfEmpty()
.Aggregate(Quotes.FirstOrDefault() ?? 0.0,
(ema, nextQuote) => alpha * nextQuote + (1 - alpha) * ema);
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