In a previous blog post we’ve described some of the problems that are encountered when processing corporate filings from the SEC’s EDGAR database in XBRL. Today we present a system that overcomes these issues by downloading and processing XBRL filings on a daily basis, normalizing the financial data, computing common financial ratios, storing all data into a SQLite database, and then presenting the corporate reporting data for financial analysis through a mobile app for iOS, Android, and Windows Phone.
We are making all the sources for the data ingestion and normalization process available as Python scripts on GitHub under an Apache 2.0 license. The actual normalization rules as well as the financial ratios being computed are defined in external JSON files that can easily be modified without the need to edit the Python sources. In addition the MobileTogether Design file describing the mobile app is also available as open source in the same repository on GitHub so the mobile application can be easily customized as well to graph different data, show other financial ratios, or do more sophisticated financial analysis.