Patent Citations and Stock Performance: Constructing a Dynamic Industry Classification

46 Pages Posted: 17 Sep 2014 Last revised: 11 Sep 2015

See all articles by Sebastien Gay

Sebastien Gay

The University of Chicago

Ezra Karger

Federal Reserve Bank of Chicago

Date Written: September 15, 2014

Abstract

Commonly used industry classifications do not reliably predict stock co-movement because companies change their core structure quickly relative to the slow and haphazard updating of widely used subjective industry classifications. We construct an objective industry classification that clusters companies using patent citations to better measure changes in company structure over time. Our classification predicts daily stock co-movement between 5% and 25% better than SIC and NAICS classifications and is a statistically significant addition to a 3-factor Fama-French model. We validate our use of patent citations to classify companies by showing that companies which cite each other’s patents are significantly more likely to merge.

Keywords: classifications, stocks, industry, cluster, return, growth, Industrial Organisation, patents

JEL Classification: C38, O3, G00, G3

Suggested Citation

Gay, Sebastien and Karger, Ezra, Patent Citations and Stock Performance: Constructing a Dynamic Industry Classification (September 15, 2014). Available at SSRN: https://ssrn.com/abstract=2496414 or http://dx.doi.org/10.2139/ssrn.2496414

Sebastien Gay (Contact Author)

The University of Chicago ( email )

Department of Economics
1126 East 59th Street
Chicago, IL 60637
United States
773-834-0887 (Phone)

HOME PAGE: http://www.sebastiengay.com

Ezra Karger

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

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