StandardDeviation.efs

[eSignal_JasonK]

File Name: StandardDeviation.efs


Description:
This formula is intended to be used within custom formulas through the callFunction() function to get the standard deviation of one of the following price sources (Open, High, Low, Close, Volume). It may also be used as a non-price study.

Formula Parameters:
nLength - 25
sPriceSource - "Close"

Notes:
Here’s an example for calling this formula from a custom formula. If the formula is in a different folder than the calling formula, change the first input parameter to the correct path (i.e. “/Other/StandardDeviation.efs”).

var nStdev = callFunction("StandardDeviation", "main", 10, "Close");
if (nStdev == null) return;  // null check 

Download File:
StandardDeviation.efs




EFS Code:

/*********************************
Provided By : eSignal. (c) Copyright 2004
Study:  Standard Deviation

Version 1.0 - 4/8/204

Formula Parameters:     Defaults:
    nLength             25
    sPriceSource        "Close"

Notes:
    This formula is intended to be used within custom formulas
    through the callFunction() function to get the standard 
    deviation of one of the following price sources.  It may also
    be used as a non-price study.
        "Open"
        "High"
        "Low"
        "Close"
        "Volume"

    Example Usage:
    var nStdev = callFunction("StandardDeviation.efs", "main", 10, "Close");
    if (nStdev == null) return;
    
********************************/


function preMain() {
    setStudyTitle("Standard Deviation ");
    setDefaultBarFgColor(Color.blue);
    setCursorLabelName("Stdev");
}

function main(nLength, sPriceSource) {
    if (nLength == null) nLength = 25;
    if (sPriceSource == null) sPriceSource = "Close";
    
    var aSource = getValue(sPriceSource, 0, -nLength);
    if (aSource == null) return null;
    
    var sumX = 0;
    var sumX2 = 0;
    for (i = 0; i < nLength; ++i) {
        sumX += aSource[i];
        sumX2 += (aSource[i] * aSource[i])
    }
    var meanX = (sumX/nLength);
    var stdev = Math.sqrt((sumX2/nLength) - (meanX*meanX));

    return stdev;
}