I am trying to model some data using a random walk, but after the standard increment and log (financial data) transformations for stationarity have found that, over long time frames, there is still not constant variance.
What is the best way to now proceed? Or, are there further transformations I could consider to address the non-stationarity the standard transforms didnt address.