Missing data is a prevalent, yet often ignored, feature of company fundamentals. Join this webinar to understand the structure of missing financial data and learn how you can systematically deal with it.

We’ll cover four key stylized facts established through a comprehensive empirical study:

• The issue of missing financial data is profound: It affects over 70 percent of firms that represent about half of the total market cap.
• The problem becomes particularly severe when multiple characteristics need to be present.
• Firm fundamentals aren’t missing at random, invalidating traditional ad-hoc approaches to data imputation and sample selection.
• Stock returns themselves depend on missingness.

Together, we’ll then explore a novel imputation method that can provide a fully observed panel of firm fundamentals. We’ll look at what improvements this delivers over traditional methods and what that means for asset pricing.

• Empirical facts about the structure of missing firm fundamentals

• A novel imputation method that utilizes both time-series and cross-sectional dependency of firm characteristics to impute their missing values

• How to substantially improve standard empirical procedures, such as using cross-sectional averages or past observations

• Crucial implications for missing financial data in different areas of investment and asset pricing

Content

content goes here