This is a repository of my work for Claremont McKenna College's Professor Kelly who is a member of the Financial Economic Institute. This research pretains to how Bond Pricing reacts to the processing of Risk Information.

Note: the data I am using for this project is a repository of SEC filings, specifically cleaned 10-X files, that can be easily sourced here: https://sraf.nd.edu/sec-edgar-data/cleaned-10x-files/ . I don't have this data pushed to this repository because of the pure size of it but it can all be accessed, for non-commercial usage, with the link provided thanks to the University of Notre Dame's Software Repository for Accounting and Finance and specifically Bill McDonald.

When running the riskfactors/evaluator.py file on all filings from 2023 QTR1 I get the results:

Successfully found Risk Factors content in 3975 out of 7145 documents.
Success rate: 55.63%