EDGAR Extraction System: An Automated Approach to Analyze Employee Stock Option Disclosures

Abstract

Past alternative accounting choices and new accounting standards for stock options have hindered analysts' ability to compare corporate financial statements. Financial analysts need specific information about stock options in order to accurately assess the financial position of companies. Finding this information is often a tedious task. The SEC's EDGAR database is the richest source of financial statement information on the Web. However, the information is stored in text or HTML files making it difficult to search and extract data. Information Extraction (IE), the process of finding and extracting useful information in unstructured text, can effectively help users find vital financial information. This paper examines the development and use of the EDGAR Extraction System (EES), a customized, automated system that extracts relevant information about employee stock options from financial statement disclosure notes on the EDGAR database.