Dynamic Factor Estimate

Problem

Estimate a single dynamic factor from cross-sectional observations by least squares: f = sum(loading_i * x_i) / sum(loading_i^2).

Return 0.0 when all loadings are zero.

Hint

This is a one-factor regression with unit-variance factor normalization.

case 1

in: [[0.5,0.5],[2,4]]

expected: 6

case 2

in: [[1,2,3],[1,2,3]]

expected: 1

case 3

in: [[0,0],[5,7]]

expected: 0

case 4

in: [[2,-1],[4,-2]]

expected: 2

Starter codePython

def dynamic_factor_estimate(loadings, observations):
    # Your code here
    pass

4 test cases · run your code against them in the editor