How to identify breakpoints (trend lines edges) in a dataset?

Question

I've been performing some research, in order to find the best approach to identify break points (trend direction change) in a dataset (with pairs of x/y coordinates), that allow me to identify the trend lines behind my data collections.

However I had no luck, finding anything that brings me some light.

The yellow dots in the following image, represent the breakpoints I need to detect.

Any suggestion about an article, algorithm, or implementation example (typescript prefered) would be very helpful and appreciated.

Answer 1

Usually, people tend to filter the data by looking only maximums (support) or only minimums (resistance). A trend line could be the average of those. The breakpoints are when the data crosses the trend, but this gives a lot of false breakpoints. Because images are better than words, you can look at page 2 of http://www.meacse.org/ijcar/archives/128.pdf.

There are a lot of scripts available look for "ZigZag" in

https://www.tradingview.com/

e.g. https://www.tradingview.com/script/lj8djt1n-ZigZag/ https://www.tradingview.com/script/prH14cfo-Trend-Direction-Helper-ZigZag-and-S-R-and-HH-LL-labels/

Also you can find an interesting blog post here (but code in in python):

https://towardsdatascience.com/programmatic-identification-of-support-resistance-trend-lines-with-python-d797a4a90530

with code available: https://pypi.org/project/trendln/