This might seem very elementary or even silly, but all comments are much appreciated. As science major I do not have deep technical knowledge in statistics, so any guidance is much appreciated.
Say we have this hypothetical problem:
Say I would like to come up with a model to predict returns of some financial instrument $I$ for a next day. I have the return values $R_n$ of the $I$ for the past $n$ days.
Additionally for each day $d$ I have some independent data $P_d$ (say $m$ numbers) that could be used to predict return value $R_d$ of today, but I have no idea what this data means and where it came from.
Are there any standard ways of finding how data $P_d$ relates to $R_d$, for example some kind of software package that loops through many possible models and check how well they fit?
Or what would be a way to tackle this type of problems, because it seems to me there could be infinite number of ways to use $P_d$ to predict $R_d$?