Eh, don't bother reading any financial literature that other commentators suggest you for this competition. With anonymized input data and even the nature of the problem (is it even short or long term prediction? the two are very different beasts), you're not going to use any financial domain knowledge here. Besides, the good stuff is rarely if ever openly published. Just keep in mind two useful unchanging truths about finance here: it's time series data and with very low signal-to-noise ratio, so overfitting is a major concern.

Start by reading/running notebooks ("kernels") and winners solutions from this and previous competitions with tabular/time series data, building models and then grid searching, stacking, bagging, boosting 'em up. Here's a bit aged but still useful guide how pros do it: https://mlwave.com/kaggle-ensembling-guide/