Quadratic Regression Slope [DW]

This is a study geared toward identifying price trends using Quadratic regression.

Quadratic regression is the process of finding the equation of a parabola that best fits the set of data being analyzed.

In this study, first a quadratic regression curve is calculated, then the slope of the curve is calculated and plotted.

Custom bar colors are included. The color scheme is based on whether the slope is positive or negative, and whether it is increasing or decreasing.
Notas de Lançamento: Updates:

-> Migrated to v4.
-> Updated QRS function for improved performance.
-> Added an offset parameter to the script, which will base current value on offset values of the extrapolated QR curve.
-> Included some experimental signal processing procedures:
- Added an option to normalize the oscillator scale using RMS.
- Added an optional compression algorithm to the script. This can be used to reduce transients (short duration, high amplitude values) by a specified level of intensity.
-> Updated color scheme.
Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.

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Great work. It’s great to see you publishing again. I’m looking forward to see what demons you release over the next while.
+2 Resposta
+1 Resposta
Awesome. Thanks for sharing your work, much appreciated!
+1 Resposta
What would be your entry point and exit point of this indicator?
Yea I can't get smoothing to work with V4, nothing happens when I change it. It's always level 1 smoothness no matter what number is entered in the field. My opinion is that version 3 was better and V4 should be a different indicator entirely. V3 which had the ideal level of functionality should have been left alone and preserved as the impressive work that it was.
DonovanWall Skipper86
@Skipper86, Ah, thanks for pointing that out. It appears when I reconstructed the function, I left out the final smoothing stage. I'll fix that in the next update.
Would variables x, t, and n take the place of the out of the function declared variables such as src, per and smper? Thanks.
DonovanWall syracusepro
@syracusepro, my apologies on the late response. I've been working on a lot of projects lately.
To answer your question, QRS requires two inputs, x and t, which correspond to src and per in the script, respectively. smper is the sampling period for exponential smoothing of the QRS outside the function's definitions. n is the current bar number.
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