Gaussian Rank Correlation and Regression

57 Pages Posted: 29 Jun 2020

See all articles by Dante Amengual

Dante Amengual

Centre for Monetary and Financial Studies (CEMFI)

Enrique Sentana

Centro de Estudios Monetarios y Financieros (CEMFI); Financial Markets Group; Centre for Economic Policy Research (CEPR)

Zhanyuan Tian

Boston University

Date Written: June 2020

Abstract

We study the statistical properties of Pearson correlation coefficients of Gaussian ranks, and Gaussian rank regressions -- OLS applied to those ranks. We show that these procedures are fully efficient when the true copula is Gaussian and the margins are non-parametrically estimated, and remain consistent for their population analogues otherwise. We compare them to Spearman and Pearson correlations and their regression counterparts theoretically and in extensive Monte Carlo simulations. Empirical applications to migration and growth across US states, the augmented Solow growth model, and momentum and reversal effects in individual stock returns confirm that Gaussian rank procedures are insensitive to outliers.

Keywords: Copula, Growth regressions, migration, Misspecification, Momentum, robustness, Short-term reversals

JEL Classification: C13, C46, G14, O47

Suggested Citation

Amengual, Dante and Sentana, Enrique and Tian, Zhanyuan, Gaussian Rank Correlation and Regression (June 2020). CEPR Discussion Paper No. DP14914, Available at SSRN: https://ssrn.com/abstract=3638018

Dante Amengual (Contact Author)

Centre for Monetary and Financial Studies (CEMFI) ( email )

Casado del Alisal 5
28014 Madrid
Spain

Enrique Sentana

Centro de Estudios Monetarios y Financieros (CEMFI) ( email )

Casado del Alisal 5
28014 Madrid
Spain
+34 91 429 0551 (Phone)
+34 91 429 1056 (Fax)

HOME PAGE: http://www.cemfi.es/~sentana/

Financial Markets Group

Houghton Street
London School of Economics & Political Science (LSE)
London WC2A 2AE
United Kingdom
+44 20 7955 7002 (Phone)
+44 20 7852 3580 (Fax)

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Zhanyuan Tian

Boston University ( email )

595 Commonwealth Avenue
Boston, MA 02215
United States

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