Thanks! Yes, you can do that. I've done this exercise in the past, many years ago (only standardizing with previous returns data), and my conclusion is that it doesn't influence the end result, provided that the train dataset is sufficiently large enough (which is the case here). In my past exercises & experience, doing that adds a ton of code/complexity, but the end result is the same. So, I don't add that anymore.
Thanks! Yes, you can do that. I've done this exercise in the past, many years ago (only standardizing with previous returns data), and my conclusion is that it doesn't influence the end result, provided that the train dataset is sufficiently large enough (which is the case here). In my past exercises & experience, doing that adds a ton of code/complexity, but the end result is the same. So, I don't add that anymore.
But it's a good catch, you have a good eye :)