| Category | Assignment | Subject | Accounting |
|---|---|---|---|
| University | University of Exeter | Module Title | BEAM079: Coding Analytics for Accounting and Finance |
| Word Count | 7500 Word Limit |
|---|---|
| Assessment Type | Research Paper |
| Academic Year | 2025-26 |
This study integrates economic ratios and textual information to enhance the predictive accuracy of financial ruin models for excessive-profile US organizations in 2023. by using employing logistic regression and neural network models, it examines whether textual statistics from annual reports can boost the performance of traditional economic fashions. This dual method addresses the distance in present literature through merging quantitative monetary evaluation with qualitative textual insights, presenting a more comprehensive framework for predicting company financial ruin. The research highlights how sentiment and clarity rankings derived from company communications may also provide predictive insights that conventional monetary metrics would possibly forget about...........View More
Introduction ......................................................................................................................... 3
Aims and Objectives .......................................................................................................... 3
Research Objectives ......................................................................................................... 3
Literature Review .............................................................................................................. 5
Bankruptcy Prediction Literature ......................................................................................... 5
Textual/Sentiment Analysis Literature .................................................................................. 5
A Combination of Accounting Values and Textual Analysis in Bankruptcy Prediction ........ 6
Contribution of This Study .................................................................................................. 6
Methodology ....................................................................................................................... 8
Statistical Models and Tests Used ....................................................................................... 8
Logistic Regression ........................................................................................................... 8
Neural Network ................................................................................................................ 8
Sentiment Analysis and Textual Data Integration ............................................................ 9
Comparative Analysis of Methods ....................................................................................... 9
Data Description ............................................................................................................... 10
Financial Data ..................................................................................................................... 10
Textual Data ....................................................................................................................... 11
Univariate Analysis .......................................................................................................... 12
Tests of Difference ............................................................................................................. 13
Correlation Analysis ........................................................................................................... 13
Visual Comparisons: Word Clouds ..................................................................................... 13
Implementation in Python ................................................................................................. 22
Multivariate Analysis ........................................................................................................ 22
Model Development ........................................................................................................... 23
Comparative Analysis of Models ....................................................................................... 27
Results Interpretation ......................................................................................................... 29
Conclusions from Multivariate Analysis ............................................................................. 29
Conclusion .......................................................................................................................... 30
Key Findings ....................................................................................................................... 30
Implications ......................................................................................................................... 31
References ......................................................................................................................... 32
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