I am looking for some suggestions on what techniques to use for stock data. Specifically i am looking for some methods to both de-noise data, and then find ways to transform the smoother data into a zero-centered format (i believe stock data is referred to as a non-stationary signal, is that correct?). I realize that to zero center my data, i'm probably going to want to look at chunks of the data and work on those individually. Was wondering if there was a standard or recommended technique for this. From there it should be far easier to pick the peaks and valleys i want.
I'm planning on using optimization methods to find the peaks and valleys i find, so the method doesn't need to be static but hopefully will have a few params i can play around with to determine the granularity and scope of the peak detection.