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SUMMARY:Missing Financial Data
DTSTART:20220520T103000
DTEND:20220520T120000
DTSTAMP:20260407T043512Z
UID:2f0ade5cde24c1501cb27cfe315b031098b1dbc4669f9fa047489a8e
CATEGORIES:Conferences - Seminars
DESCRIPTION:Markus Pelger\, Stanford\nMissing data is a prevalent\, yet of
 ten ignored\, feature of company fundamentals. In this paper\, we document
  the structure of missing financial data and show how to systematically de
 al with it. In a comprehensive empirical study we establish four key styli
 zed facts. First\, the issue of missing financial data is profound: it aff
 ects over 70% of firms that represent about half of the total market cap. 
 Second\, the problem becomes particularly severe when requiring multiple c
 haracteristics to be present. Third\, firm fundamentals are not missing-at
 -random\, invalidating traditional ad-hoc approaches to data imputation an
 d sample selection. Fourth\, stock returns themselves depend on missingnes
 s. We propose a novel imputation method to obtain a fully observed panel o
 f firm fundamentals. It exploits both time-series and cross-sectional depe
 ndency of firm characteristics to impute their missing values\, while allo
 wing for general systematic patterns of missing data. Our approach provide
 s 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.\n\nPaper \n 
LOCATION:UniL Campus\, room Extranef 126
STATUS:CONFIRMED
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