Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs
Securities and Exchange Commission (SEC) which can be found in EDGAR. We were preprocessing those data and than sending via API to gpt-4o model in a Retrieval-Augmented Generation (RAG) like regime. We prepared as well a document describing an exemplar investor knowledge based on Kitchin cycles.
- ▪Securities and Exchange Commission (SEC) which can be found in EDGAR.
- ▪We were preprocessing those data and than sending via API to gpt-4o model in a Retrieval-Augmented Generation (RAG) like regime.
- ▪We prepared as well a document describing an exemplar investor knowledge based on Kitchin cycles.
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Computer Science > Computation and Language arXiv:2607.09121 (cs) [Submitted on 10 Jul 2026] Title:Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs Authors:Bartosz Ziółko, Kacper Dobrzeniewski View a PDF of the paper titled Augmenting Fundamental Analysis with Large Language Models: A RAG-Based System for Generating Investor Briefs, by Bartosz Zi\'o{\l}ko and Kacper Dobrzeniewski View PDF HTML (experimental) Abstract:In this study, we examine the opportunities brought by Large Language Models (LLMs) to various aspects of fundamental analysis of companies based on their reports as well as data and documents describing macroeconomic situation like GDP and inflation changes as well as documents filled to the U.S.
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