EMA计算的C#实现（c# Exponential Moving Average (EMA) indicator ）

原来国外有个源码（TechnicalAnalysisEngine src 1.25）内部对EMA的计算是：

var copyInputValues = input.ToList();

for (int i = period; i < copyInputValues.Count; i++) { var resultValue = (copyInputValues[i] - returnValues.Last()) * multiplier + returnValues.Last();

returnValues.Add(resultValue); }

var result = new EMAResult() { Values = returnValues, StartIndexOffset = period - 1 };

可以明显看出，这样的计算方式与我们传统的不一致，甚至可能无法得出结果。经过对国内通达信等主力软件内的EMA算法研究得出用一下方法可以实现对EMA的计算。贴上C#的实现方法。

using System;using System.Collections.Generic;using System.Linq;using System.Text;using System.Threading.Tasks;

namespace myEMA{ public class myEMA { static void Main(string[] args){double[] arr;arr = new double[5]{2077,2077,2078,2083,2082};List<double> dd=new List<double>(){2077,2077,2077,2078,2083,2082};//EMAResult du= ;var result=EMA(dd,5);Console.WriteLine("{0}个result的值",result.Values.Count);for(int i=0;i<result.Values.Count;i++ ){Console.WriteLine("第{0}的ema={1}",i,result.Values[i]);}Console.WriteLine("emaR={0}",result.EmaR );} /// <summary> /// Contains calculation results for EMA indicator /// </summary> public class EMAResult { public List<double> Values { get; set; } public int StartIndexOffset { get; set; } public double EmaR { get; set; } }

//-------------------------------------------------------------------------------------------------------------------------------

/// <summary> /// Calculates Exponential Moving Average (EMA) indicator /// </summary> /// <param name="input">Input signal</param> /// <param name="period">Number of periods</param> /// <returns>Object containing Operation results</returns> public static EMAResult EMA(IEnumerable<double> input, int period) { var returnValues = new List<double>();

double multiplier = (2.0 / (period + 1)); //double initialSMA = input.Take(period).Average();

//returnValues.Add(initialSMA); var copyInputValues = input.ToList(); int j=0; for (int i = copyInputValues.Count-period; i < copyInputValues.Count; i++) { if(j<1){var resultValue =copyInputValues[i]; returnValues.Add(resultValue); }else{var resultValue = (copyInputValues[i]*multiplier )+(1- multiplier)* returnValues.Last(); returnValues.Add(resultValue);}j++; }

var result = new EMAResult() { EmaR=returnValues.Last(),Values = returnValues,StartIndexOffset = period - 1};

return result; }

}}