Missing Financial Data
Отсутствующие финансовые данные
2024-07-02
SCID: 54.1/h9bfy6b9
Discuss with AI
imputation methodmissing financial datamissing observations of firm fundamentalssystematic patterns of missingnesstime-series and cross-sectional dependency
Figures from the paper
Abstract (AI)
Abstract 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)
Key Findings
1
Firm fundamentals exhibit complex, systematic missingness patterns that invalidate traditional imputation approaches.
2
Missing financial data is widespread: over 70% of firms (representing about half of total market capitalization) have missing firm fundamentals.
3
The authors propose a novel imputation method that leverages both time-series and cross-sectional dependencies and accommodates general systematic missingness.
4
Using the proposed fully observed panel of firm fundamentals has important implications for estimates of risk premiums, cross-sectional anomalies, and portfolio construction.
Research Object
Missing observations of firm fundamentals in financial datasets (firms' fundamental variables across time and cross-section)
Research Subject
Structure, prevalence, and systematic imputation of missing financial data to produce a fully observed panel and its implications for risk-premium estimates, cross-sectional anomalies, and portfolio construction
Publication Details
Publication Date
2024-07-02
Journal
Publisher
ISSN
Cited by
30
Access Type
Author Information
Download PDF
Subscribe to digest