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)
机构:
Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, SAC, New York, NY 10027 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, SAC, New York, NY 10027 USA
Thompson, LLP
Levy, G
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机构:
Columbia Univ, Mailman Sch Publ Hlth, Dept Biostat, SAC, New York, NY 10027 USAColumbia Univ, Mailman Sch Publ Hlth, Dept Biostat, SAC, New York, NY 10027 USA