Paper: SSRN 2959518

Abstract

Relative to quantitative methods traditionally used in accounting and finance, textual analysis is substantially less precise. Thus, understanding the art is of

Complexity vs Empirical Score

  • Math Complexity: 1.0/10
  • Empirical Rigor: 2.0/10
  • Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: 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.

Research Flowchart

  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