使用某种编程语言（JS/C#等）计算RSI（相对强弱指标）

Question

我正在努力计算RSI（相对强弱指数）。 我有这样的数据

**Date|Close|Change|Gain|Loss**

计算此项的公式为

RSI = 100 - 100/(1+RS)
where RS = Average Gain / Average Loss

来源

我想要用一些编程语言(JavaScript或C#)来计算，但我不知道如何将其转换为编程语言或需要哪些步骤。

如果您还有什么要了解的问题，我可以尽力解释。

- Blu

Answer 1

翻译 RSI 公式的简单方法：

public static double CalculateRsi(IEnumerable<double> closePrices)
{
    var prices = closePrices as double[] ?? closePrices.ToArray();

    double sumGain = 0;
    double sumLoss = 0;
    for (int i = 1; i < prices.Length; i++)
    {
        var difference = prices[i] - prices[i - 1];
        if (difference >= 0)
        {
            sumGain += difference;
        }
        else
        {
            sumLoss -= difference;
        }
    }

    if (sumGain == 0) return 0;
    if (Math.Abs(sumLoss) < Tolerance) return 100;

    var relativeStrength = sumGain / sumLoss;

    return 100.0 - (100.0 / (1 + relativeStrength));
}

有许多项目以不同的方式实现RSI。 这里可以找到一种增量方法

- Ricardo stands with Ukraine

---

@AmirFo 在这段代码中使用了 double Tolerance = 10e-20 只是为了避免在下面的除法运算中出现错误。 - Ricardo stands with Ukraine

对于相对强度指数，我们需要将其除以总收益和总亏损的平均值.. 所以我认为在上面的代码中，我们需要更改 var relativeStrength = (sumGain/Period) / (sumLoss/Period).. 参考自investopedia. RSI ​ =100−[ 100/( 1+ (平均亏损/平均收益)) ] https://www.investopedia.com/terms/r/rsi.asp - Mehul Talajia

Answer 2

这应该与Riga的答案没有区别，但似乎从未低于40，请小心，也许最好还是坚持使用TA_LIB？

    //Relative Strength Index
    function rsi($ar, $period, $opt, $offset=0) //opt: 0=none, 1=exponential, 2=wilder, 3=average all
    {
        GLOBAL $smoothsteps;
        $pag = 0; //Previous Average Losses
        $pal = 0; //Previous Average Gains

        //Count average losses and gains
        $len = sizeof($ar)-1-$offset;
        $end = $len-$period-$offset;
        for($i = $len; $i > $end; $i--)
        {
            if($ar[$i] > $ar[$i-1]) //Gain
                $pag += $ar[$i] - $ar[$i-1]; 
            else //Loss
                $pal += $ar[$i-1] - $ar[$i];
        }
        $pag /= $period;
        $pal /= $period;

        //Smooth
        $ag = 0; //Average Losses
        $al = 0; //Average Gains
        for($i = $len; $i > 0; $i--)
        {
            if($ar[$i] > $ar[$i-1]) //Gain
                $ag += $ar[$i] - $ar[$i-1]; 
            else //Loss
                $al += $ar[$i-1] - $ar[$i];
        }

        if($opt == 3) //Average All Three
        {
            $a = 1 / $smoothsteps;
            $tag = $a * $ag + (1 - $a) * $pag;
            $tal = $a * $al + (1 - $a) * $pal;
            $wag = $pag * 13 + $ag;
            $wal = $pal * 13 + $al;
            $ag = ($wag+$tag+$pag)/3;
            $al = ($wal+$tal+$pal)/3;
        }
        else if($opt == 2) //Wilder Exp
        {
            $ag = $pag * 13 + $ag;
            $al = $pal * 13 + $al;
        }
        else if($opt == 1) //Exponential (Lame) [Closest to Trading View]
        {
            $sa = 1 / $smoothsteps;
            $ag = $sa * $ag + (1 - $sa) * $pag;
            $al = $sa * $al + (1 - $sa) * $pal;
        }
        else if($opt == 0) //None
        {
            $ag = $pag;
            $al = $pal;
        }

        //Relative Strength
        $rs = $ag / $al;

        //Relative Strength Index
        return 100 - (100 / (1+$rs));
    }

- SirTames

Answer 3

我将用伪代码编写，您可以轻松地将其编写成任何语言。 最短的编码方式是：

v0 = 0 
v1 = 0 
v2 = 0 
v3 = 1/N                     
v4 = 0

if Step == 1: #initialisation
   v0 = (Price[t] - Price[t-N] ) / N
   v1 = mean( abs( diff(Price[(t-N):t] ) ) # average price change over previous N
else
   v2 = Price[t]  - Price[t-1] 
   v0 = vv[t-1] + v3 * ( v2 - v0[t-1] )
   v1 = v1[t-1] + v3 * ( abs( v2 ) - v1[t-1] )

if v1 != 0: 
   v4 = v0 / v1 
else
   v4 = 0

RSI = 50 * ( v4 + 1 )

这可能是在您的模拟中应用 RSI 最有效的方法。

- mm441