Textual Analysis in Accounting and Finance: A Survey
Textual Analysis in Accounting and Finance: A Survey ArXiv ID: ssrn-2959518 “View on arXiv” Authors: Unknown Abstract Relative to quantitative methods traditionally used in accounting and finance, textual analysis is substantially less precise. Thus, understanding the art is of Keywords: Textual Analysis, Accounting Research, Finance Research, Natural Language Processing, General (Accounting & Finance) Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a survey of textual analysis methods, which are conceptually oriented and less mathematically dense, and while it discusses empirical applications, it lacks the specific implementation details, code, or backtests required for high empirical rigor. flowchart TD A["Research Goal:<br>Textual Analysis in Accounting & Finance"] --> B["Data Collection"] B --> C["Preprocessing & Normalization"] C --> D["Textual Analysis Methodology"] D --> E["Statistical & Computational Processing"] E --> F["Key Findings/Outcomes"] subgraph B ["Data/Inputs"] B1["Financial Statements"] B2["Regulatory Filings"] B3["Earnings Calls"] B4["News & Social Media"] end subgraph C ["Preprocessing"] C1["Tokenization"] C2["Stopword Removal"] C3["Stemming/Lemmatization"] end subgraph D ["Methodology"] D1["Linguistic Metrics"] D2["Sentiment Analysis"] D3["Topic Modeling"] D4["Machine Learning"] end subgraph E ["Computational Processes"] E1["Feature Extraction"] E2["Statistical Inference"] E3["Model Validation"] end subgraph F ["Outcomes"] F1["Financial Prediction"] F2["Risk Assessment"] F3["Market Efficiency Insights"] end