Measurement of Factor Strenght: Theory and Practice

106 Pages Posted: 11 Mar 2020

See all articles by Natalia Bailey

Natalia Bailey

Monash University

George Kapetanios

King's College, London

M. Hashem Pesaran

University of Southern California - Department of Economics

Date Written: 2020

Abstract

This paper proposes an estimator of factor strength and establishes its consistency and asymptotic distribution. The estimator is based on the number of statistically significant factor loadings, taking multiple testing into account. Both cases of observed, and unobserved factors are considered. The small sample properties of the proposed estimator are investigated using Monte Carlo experiments. It is shown that the proposed estimation and inference procedures perform well, and have excellent power properties, especially when the factor strength is sufficiently high. Empirical applications to factor models for asset returns show that out of 146 factors recently considered in the literature, only the market factor is truly strong, while all other factors are at best semi-strong, with their strength varying considerably over time. Similarly, we only find evidence of semi-strong factors using a large number of U.S. macroeconomic indicators.

Keywords: factor models, factor strength, measures of pervasiveness, cross-sectional dependence, market factor

JEL Classification: C380, E200, G200

Suggested Citation

Bailey, Natalia and Kapetanios, George and Pesaran, M. Hashem, Measurement of Factor Strenght: Theory and Practice (2020). CESifo Working Paper No. 8146, Available at SSRN: https://ssrn.com/abstract=3552386

Natalia Bailey (Contact Author)

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

M. Hashem Pesaran

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

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