Custom technical indicators#

This article shows how to create custom technical indicators, in this case, linear regression. To read more about technical indicators offered by Highcharts click here.

Be sure to have at least the Highcharts version 6, as previous Highcharts versions don’t support technical indicators.


There are two main steps to create a technical indicator series:

  1. Set up the technical indicator structure.
  2. Create the technical indicator functionality.
1. Set up the structure#

Each technical indicator requires the method getValues() to be implemented. This method takes two arguments and returns an object. The arguments are the main series and the parameters. The parameters are specific to a technical indicator. Check the structure of the method getValues():

function getValues(series, params) {
// calculations
// end of calculations
return {
xData: [...], // array of x-values
yData: [...] // array of y-values
values: [...], // array of points

All technical indicators are series types, and to create a new series, in Highcharts, the following method Highcharts.seriesType() is used.

<script type="text/javascript" src=""></script>
name: 'Linear Regression',
params: {} // linear regression doesn’t need params
getValues: function (series, params) {
return this.getLinearRegression(series.xData, series.yData);
getLinearRegression: getLinearRegression

The method getLinearRegression() includes the technical indicator functionality (mathematical calculation). Notice that the indicators module indicators.js is included when creating technical indicators, as it includes the core-logic for all indicators.

Now the structure is set, the next step is to create the main indicator functionality.

2. Technical indicator functionality#

The technical indicator functionality is represented by the following method getLinearRegression(), that calculates the regression points according to xData and yData.

Here is a simple mathematical representation of the linear regression:

Screen Shot 2017-11-03 at 14.11.43.png

Where the slope is: 

Screen Shot 2017-11-03 at 14.11.51.png

And offset:

Screen Shot 2017-11-03 at 14.12.06.png

The JavaScript representation of the formulas above is as follows:

function getLinearRegression(xData, yData) {
var sumX = 0,
sumY = 0,
sumXY = 0,
sumX2 = 0,
linearData = [],
linearXData = [],
linearYData = [],
n = xData.length,
alpha, beta, i, x, y;
// Get sums:
for (i = 0; i < n; i++) {
x = xData[i];
y = yData[i];
sumX += x;
sumY += y;
sumXY += x * y;
sumX2 += x * x;
// Get slope and offset:
alpha = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX);
if (isNaN(alpha)) {
alpha = 0;
beta = (sumY - alpha * sumX)/ n;
// Calculate linear regression:
for (i = 0; i < n; i++) {
x = xData[i];
y = alpha * x + beta;
// Prepare arrays required for getValues() method
linearData[i] = [x, y];
linearXData[i] = x;
linearYData[i] = y;
return {
xData: linearXData,
yData: linearYData,
values: linearData

Notice that Linear regression series in this example is still a line series, and that means data has to be sorted ascending by x-values.

That’s it; the technical indicator is ready to be used. Keep in mind that the technical indicator is connected to the main series by the linkedTo option:

series: [{
id: 'main',
type: 'scatter',
data: [ ... ]
}, {
type: 'linearregression',
linkedTo: 'main'

For live demos check the links below:


To improve the user experience when using the linear regression series, try to disable tooltip and/or markers. Go to the seriesType() and set the default options as follows:

name: 'Linear Regression',
enableMouseTracking: false, // default options
marker: {
enabled: false
params: {} // linear regression doesn’t need params
getValues: ... ,
getLinearRegression: ...

Module The indicator is available as a indicators/trendline.js main module.

For more detailed samples and documentation check the API.