Honors Theses
Date of Award
2017
Document Type
Undergraduate Thesis
Department
Computer and Information Science
First Advisor
Dawn Wilkins
Relational Format
Dissertation/Thesis
Abstract
The objective of this thesis is to improve upon the most commonly utilized, entirely manual financial modeling process. This thesis gives guidance for implementing a set of technical tools that can be utilized in an individual's financial modeling process to automate repetitive and predictable tasks. The goal is not to provide a robust set of tools that can be implemented across all financial models; in fact, this may not be possible. The goal is to provide a basis for anyone who utilizes financial modeling to study their own modeling processes and adapt the given tools to fit into and improve their unique process.
Recommended Citation
Short, Robert Forrest, "Utilizing Natural Language Processing and other Technical Tools to Automate the Financial Modeling Process while Maintaining Robustness in the Model" (2017). Honors Theses. 797.
https://egrove.olemiss.edu/hon_thesis/797
Accessibility Status
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