Deriving Nonlinear Correlation Coefficients from Partial Moments

25 Pages Posted: 19 Sep 2012 Last revised: 3 Aug 2017

See all articles by Fred Viole

Fred Viole

OVVO Financial Systems; Fordham University

David N. Nawrocki

Villanova University - Department of Finance

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

Viole, Fred and Nawrocki, David N., Deriving Nonlinear Correlation Coefficients from Partial Moments (September 18, 2012). Available at SSRN: https://ssrn.com/abstract=2148522 or http://dx.doi.org/10.2139/ssrn.2148522

Fred Viole (Contact Author)

OVVO Financial Systems ( email )

NJ
United States

Fordham University ( email )

Bronx, NY 10458
United States

David N. Nawrocki

Villanova University - Department of Finance ( email )

800 Lancaster Avenue
Villanova, PA 19085-1678
United States
610-519-4323 (Phone)
610-519-6881 (Fax)

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