UCSgears_Linear Regression Slope
This is version 1 of the Linear Regression Slope. In ideal world the Linear regression slope values will remain same for any time period length. because the equation is y = mx+b, where m is the slope. All I did here is m = y/x
The Main Purpose of this indicator is to see, if the Trend is accelerating or decelerating.
The first Blue bar will caution when a strong trend is losing strength. I will leave the rest for you to explore.
I picked AAPL again, because it does have both up and down trend, in the recent time.
Mistake in the code
Corrected Version -
The Main Purpose of this indicator is to see, if the Trend is accelerating or decelerating.
The first Blue bar will caution when a strong trend is losing strength. I will leave the rest for you to explore.
I picked AAPL again, because it does have both up and down trend, in the recent time.
Mistake in the code
Corrected Version -
Uday C Santhakumar
// Created by UCSgears -- Version 1 // Simple linear regression slope - Good way see if the trend is accelarating or decelarating study(title="UCSGEARS - Linear Regression Slope", shorttitle="UCS-LRS", overlay=false) src = close len = input(defval=5, minval=1, title="Slope Length") lrc = linreg(src, 50, 0) lrs = (lrc[-len] - lrc)/len alrs = sma(lrs,9) loalrs = sma(lrs,50) uacce = lrs > alrs and lrs > 0 and lrs > loalrs dacce = lrs < alrs and lrs < 0 and lrs < loalrs scolor = uacce ? green : dacce ? red : blue plot(lrs, color = scolor, title = "Linear Regression Slope", style = histogram, linewidth = 4) plot(alrs, color = black, title = "Average Slope") plot(0, title = "Zero Line")