Julian Faraway (whose work has had a strong influence on Dr. Harrell’s regression modelling strategies) had written a 2016 paper that discusses the contexts where data splitting might be worth considering:
Faraway, J. J. (2016). Does data splitting improve prediction?. Statistics and computing, 26, 49-60.
A link to the paper is available in this thread.
Because of the lack of data and non-stationarity of time series, you are going to need to work backward from what is taught in financial theory textbooks to the actual market context in which you work.
I recommend a study of the book Expectations Investing, where you use financial theory to infer what factors investors are discounting. You can then apply your stats background to ferret out contrary information that suggests the current consensus is wrong, and how to implement it.
Recommended Reading
Johnstone, D. (2018). Accounting theory as a Bayesian discipline. Foundations and Trends® in Accounting, 13(1-2), 1-266.