PCA

reconstruct_portfolio.py

import numpy as np


# ROD, PB, PE, DivP, netIncomeTTM, ROA
px_0 = np.array([40, 40, 40, 40, 40, 40])
px_1 = np.array([-49.54, -37.51, -16.38, 3.82, 27.54, 71.29])

pc_0 = 0.01
pc_1 = -0.02

reconstructred_portfolio = pc_0 * px_0 + pc_1 * px_1
# It won't be an exact match since we are only using two principal components, but it's a good approximation.
# Since we know our weights must sum up to one we can normalize using something like e^X/sum(e^X)