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.

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

optInTimePeriod — Number of bars in the regression window

Implementation

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

Native	File
C	`ta_LINEARREG_SLOPE.c`
Rust	`linearreg_slope.rs`
Java	`Core.java`

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

Aliases

Linear Regression Slope, LSMA slope, least squares slope