Deriving Nonlinear Correlation Coefficients from Partial Moments
25 Pages Posted: 19 Sep 2012 Last revised: 3 Aug 2017
Date Written: September 18, 2012
Abstract
We introduce a nonlinear correlation coefficient metric derived from partial moments that can be substituted for the Pearson correlation coefficient in linear instances as well. The flexibility offered by partial moments enables ordered partitions of the data whereby linear segments are aggregated for an overall correlation coefficient. Our coefficient works without the need to perform a linear transformation on the underlying data, and can also provide a general measure of nonlinearity between two variables. We also extend the analysis to a multiple nonlinear regression without the adverse effects of multicollinearity.
Supplemental information is available at: https://ssrn.com/abstract=3010414
Keywords: Partial Moments, Nonlinear Correlation, Nonlinear Regression, Pearson
JEL Classification: C13, C14
Suggested Citation: Suggested Citation