An efficient graph‐based peer selection method for financial statements

This is the authors' abstract. We don't add key points for this paper.

Summary Comparing companies can be useful for various purposes. Despite the widespread use of industry classification systems as a peer selection standard, these have been criticized for various reasons. Financial statements, however, offer a promising alternative to such classification systems. They are standardized, widely available, and offer deep insights into the nature of the company. In this paper, we present a graph distance metric for financial statements using the earth mover's distance. When using the distance metric on real‐world tasks such as peer identification and industry classification, it shows promising results in terms of accuracy and computational efficiency.