Missing Financial Data

80 Pages Posted: 13 May 2022

See all articles by Svetlana Bryzgalova

Svetlana Bryzgalova

London Business School - Department of Finance

Sven Lerner

Stanford University - Institute for Computational and Mathematical Engineering

Martin Lettau

University of California - Haas School of Business; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER)

Markus Pelger

Stanford University - Department of Management Science & Engineering

Date Written: May 11, 2022

Abstract

Missing data is a prevalent, yet often ignored, feature of company fundamentals. In this paper, we document the structure of missing financial data and show how to systematically deal with it. In a comprehensive empirical study we establish four key stylized facts. First, the issue of missing financial data is profound: it affects over 70% of firms that represent about half of the total market cap. Second, the problem becomes particularly severe when requiring multiple characteristics to be present. Third, firm fundamentals are not missing-at-random, invalidating traditional ad-hoc approaches to data imputation and sample selection. Fourth, stock returns themselves depend on missingness. We propose a novel imputation method to obtain a fully observed panel of firm fundamentals. It exploits both time-series and cross-sectional dependency of firm characteristics to impute their missing values, while allowing for general systematic patterns of missing data. Our approach provides a substantial improvement over the standard leading empirical procedures such as using cross-sectional averages or past observations. Our results have crucial implications for many areas of asset pricing.

Keywords: Missing data, firm characteristics, PCA, factor model, big data, asset pricing

JEL Classification: C14, C38, C55, G12

Suggested Citation

Bryzgalova, Svetlana and Lerner, Sven and Lettau, Martin and Pelger, Markus, Missing Financial Data (May 11, 2022). Available at SSRN: https://ssrn.com/abstract=4106794 or http://dx.doi.org/10.2139/ssrn.4106794

Svetlana Bryzgalova

London Business School - Department of Finance ( email )

Sussex Place
Regent's Park
London NW1 4SA
United Kingdom

Sven Lerner

Stanford University - Institute for Computational and Mathematical Engineering ( email )

Stanford, CA 94305
United States

Martin Lettau

University of California - Haas School of Business ( email )

Haas School of Business
545 Student Services Building
Berkeley, CA 94720
United States
5106436349 (Phone)

HOME PAGE: http://faculty.haas.berkeley.edu/lettau/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Markus Pelger (Contact Author)

Stanford University - Department of Management Science & Engineering ( email )

473 Via Ortega
Stanford, CA 94305-9025
United States

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