I have multivariate time series data of the EURUSD financial vehicle. In this data each variable represents a different metric. There are ~200,000 rows and ~20 variables. There are no NULL values for any variable at any row. All data is numerical.
Alongside this data, at each time point I have the univariate data "Profit."
I want to curve-fit a function to transforms my multivariate data set into a new univariate data set which having the MAXIMAL correlation to my "Profit" variable.
In other words, I want to iterate through different mathematical transformations of my multivariate data set until I find the one that is optimally correlated with my "Profit" data.
What is the best way to do this? From what I understand, a genetic algorithm should work well.