rank

Defined in fynance.signal

rank(pred, top, bottom)

Cross-sectional long/short by rank.

For each time step (row of a 2-D (T, n_assets) prediction), go long the top highest-ranked assets and short the bottom lowest, equally weighted within each leg (dollar-neutral).

Parameters:

predarray-like, shape (T, n_assets)

Cross-sectional predictions.

top, bottomint

Number of assets in the long and short legs.

Returns:

numpy.ndarray

Weights of shape (T, n_assets).