Your objective is to produce a model to predict positive moves $($up trend$)$ using machine learning

models as specified in the below section. Your proposed solution should be comprehensive with the

detailed feature engineering and model architecture.

$$ Choose one ticker of your interest from the index, equity, ETF, crypto token, or commodity.

$$ Predict trend only, for a short$-$term return $($example: daily, $6$ hours$).$ Limit prediction to

binomial classification: the dependent variable is best labeled $[0,1].$ Avoid using $[-1,1]$ as class

labels.

$$ Analysis should be comprehensive with detailed feature engineering, data pre$-$processing, model

building, and evaluation.

Devise your own approach on how to categorise extremely small near$-$zero returns $($drop from

training sample, group with positive$/$negative$).$ The threshold will strongly depend on your

ticker. Example: small positive returns below $0\mathrm{.}25\%$ can be labelled as negative.