Factor-Selection

This repository contains a Python class that can be used to automatically compute criteria to determine the optimal number of factors for high-dimensional factor models.

Thus far, the class includes criteria from the following papers:

• Ahn, S.C. and Horenstein, A.R. (2013), Eigenvalue Ratio Test for the Number of Factors. Econometrica, 81: 1203-1227. https://doi.org/10.3982/ECTA8968
  • Growth Ratio Criterion (function: AH_crit_GR)
  • Eigenvalue Ratio Criterion (function: AH_crit_ER)

Example

Import the class and NumPy

from fsmodule import FactorSelection
import numpy as np

Simulate example data

X = np.random.rand(100,200)

Create a factor selection object and conduct all available tests using the selection function

fs = FactorSelection(X,6)
fs.selection()

Individual tests can be conducted by calling, for example,

r0 = fs.AH_crit_ER()