ORDINARY LEAST SQUARES Slope by @XeL_Arjona
Ver. 1 by Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
WHAT'S THIS?
This is a REAL mathematically approach of an ORDINARY LEAST SQUARES LINE FITTING SLOPE as TradingView currently don't have a native one embedded, neither as a pine function. Other "Sope" indicators from this linear regression model I found on public library are currently based on "momentum" rather tan slope.
Any modifications or additions are quite welcome!
Cheers!
@XeL_Arjona
Ver. 1 by Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
WHAT'S THIS?
This is a REAL mathematically approach of an ORDINARY LEAST SQUARES LINE FITTING SLOPE as TradingView currently don't have a native one embedded, neither as a pine function. Other "Sope" indicators from this linear regression model I found on public library are currently based on "momentum" rather tan slope.
Any modifications or additions are quite welcome!
Cheers!
@XeL_Arjona
//@version=2 study("ORDINARY LEAST SQUARES Slope by @XeL_Arjona",shorttitle="LinReg Slope", overlay=false,precision=4) p = input(title="Lookback Window:",defval=21) src = input(title="Series Source:",type=source,defval=close) // SLOPE FUNCTION ols_slope(array,lookback) => x1 = n[lookback] x2 = n y1 = linreg(array,lookback,lookback) y2 = linreg(array,lookback,0) dx = x2-x1 dy = y2-y1 out = (dy/dx) // STUDY VARIABLES TO OUTPUT slp = ols_slope(src,p) // PLOTTING DIRECTIVES plot(slp,style=columns,color=slp>0?blue:red,title="OLS Slope",transp=55)