[blackcat] L1 Adaptive Choppiness Index

2023年2月12日

Level: 1

Background

I have been working with choppiness index type indicator for long. However, there are several problems in tradintional one.

Function
One of the issue of conventional choppiness index is the noise or ripple is too obvious. I was wondering several ways to smooth it. As you may know, choppiness index is "one line" indicator. There is little room of freedom to change it too much. Then, I introduced adaptation algorithm to make "length" parameter adaptive, which can smooth choppiness index indicator to some degree. Meanwhile, I use ALMA to smooth the output again.

Remarks

I used my published dc_ta lib, which collects several dominant cycle algorithm from Elhers to make many indicator adaptive possible.

Feedbacks are appreciated.