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Missing Financial Data

delete2024-07-02
delete3
PRE
AI
S
Svetlana Bryzgalova
S
Sven Lerner
M
Martin Lettau
M
Markus Pelger *
DOI：10.1093/rfs/hhae036delete
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Abstract

Abstract

En 中文
We document the widespread nature and structure of missing observations of firm fundamentals and show how to systematically handle them. Missing financial data affects more than 70% of firms that represent about half of the total market cap. Firm fundamentals have complex systematic missing patterns, invalidating traditional approaches to imputation. We propose a novel imputation method to obtain a fully observed panel of firm fundamentals that exploits both time-series and cross-sectional dependency of data to impute missing values and allows for general systematic patterns of missingness. We document important implications for risk premiums estimates, cross-sectional anomalies, and portfolio construction. (JEL C14, C38, C55, G12)
Keywords:
CROSS-SECTION
FACTOR MODELS
INFERENCE
RISK
EQUILIBRIUM
INFORMATION
REGRESSION
RETURNS

Journal

Review of Financial Studies cover
Review of Financial Studies
IF:
5.4
Papers:
2.8K
Citations:
3.0W

Organization

L
London Business School
Scholars:
502
Papers: 525
Citations: 3.4K
S
Stanford University
Scholars:
9.6W
Papers: 8.2W
Citations: 17.0W
U
university of london
Scholars:
21.5W
Papers: 19.7W
Citations: 305
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