Linear Regression Slope (LINEARREG_SLOPE)

Summary

Slope 'm' of the least-squares best-fit line (y = b + m*x) over the last optInTimePeriod bars. Reports the per-bar rate of change of the fitted trend line. Positive slope = rising trend, negative = falling; magnitude is price change per bar.

Chart

Reference data (CSV) · Chart (SVG)

Chart metadata i

Outputs

outReal: line · zero · positive · negative

Formula

m = (n·SumXY − SumX·SumY) / Divisor SumX = n(n−1)/2, SumXSqr = n(n−1)(2n−1)/6, Divisor = SumX² − n·SumXSqr SumXY = Σ i·y[today−i], SumY = Σ y[today−i], i=0..n−1, n=period, y=inReal

Inputs

inReal — Data series to fit

Outputs

outReal — Slope m of the fitted line

Parameters

Parameter	Type	Default	Accepted values	Description
`optInTimePeriod`	integer	14	2–100000	Number of bars in the regression window

Properties

Numerical Stability: Start-Independent


☐ Overlap Input
✅ Independent Y-Axis i
☐ Candlestick
☐ Display Shift


☐ Can Output NaN or ±Inf
☐ Identity at Period 1
☐ Uses Transcendental
☐ Input Must Be Positive

Example

#include <stdio.h>
#include <ta_libc.h>

int n = 252;
double series[252]; /* your data, oldest first */
double out[252];
int outBegIdx, outNBElement;

TA_Initialize();
TA_LINEARREG_SLOPE( 0, n - 1, series, 14, &outBegIdx, &outNBElement, out );
printf( "%d values from bar %d; last out = %f\n", outNBElement, outBegIdx, out[outNBElement - 1] );

Rust

use ta_lib::Core;

let series = vec![0.0; 252]; // your data, oldest first
let mut out = vec![0.0; 252];

let core = Core::new();
let range = core.linearreg_slope(0, series.len() - 1, &series, 14, &mut out)?;
println!("{} values from bar {}; last out = {}", range.count, range.beg_idx, out[range.count - 1]);

Java

import io.github.talib.Core;
import io.github.talib.OutRange;

double[] series = new double[252]; // your data, oldest first
double[] out = new double[252];

Core core = Core.DEFAULT;
OutRange r = core.linearregSlope(0, series.length - 1, series, 14, out);
System.out.println(r.count() + " values from bar " + r.begIdx() + "; last out = " + out[r.count() - 1]);

using System;
using TALib;

var series = new double[252]; // your data, oldest first
var outReal = new double[252];

var core = Core.Default;
OutRange r = core.LinearregSlope(0, series.Length - 1, series, 14, outReal);
Console.WriteLine($"{r.Count} values from bar {r.BegIdx}; last outReal = {outReal[r.Count - 1]}");

TypeScript

import { linearregSlope } from 'ta-lib';

const series = new Float64Array(252); // your data, oldest first

const { begIdx, values } = linearregSlope(series, { timePeriod: 14 });
console.log(values.length + ' values from bar ' + begIdx + '; last values = ' + values[values.length - 1]);

Implementation

Added in 0.4.0.

TA-Lib Definition: linearreg_slope.c · linearreg_slope.yaml

Native	File
C	`ta_LINEARREG_SLOPE.c`
Rust	`linearreg_slope.rs`
Java	`Core_LINEARREG_SLOPE.java`
C#	`Core_LINEARREG_SLOPE.cs`
TypeScript	`linearregSlope.ts`

Python: talib.LINEARREG_SLOPE, see ta-lib-python.

TA-Lib is also available for R and more using a wrapper.

Aliases

Linear Regression Slope, LSMA slope, least squares slope