Knowledge Management Research (지식경영연구)

The Knowledge Management Society of Korea (한국지식경영학회)
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Financial Footnote Analysis for Financial Ratio Predictions based on Text-Mining Techniques

재무제표 주석의 텍스트 분석 통한 재무 비율 예측 향상 연구

  • 최형규 (한양대학교 비즈니스인포매틱스학과) ;
  • 이상용 (한양대학교 비즈니스인포매틱스학과)
  • Received : 2020.05.28
  • Accepted : 2020.06.11
  • Published : 2020.06.30
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Abstract

Since the adoption of K-IFRS(Korean International Financial Reporting Standards), the amount of financial footnotes has been increased. However, due to the stereotypical phrase and the lack of conciseness, deriving the core information from footnotes is not really easy yet. To propose a solution for this problem, this study tried financial footnote analysis for financial ratio predictions based on text-mining techniques. Using the financial statements data from 2013 to 2018, we tried to predict the earning per share (EPS) of the following quarter. We found that measured prediction errors were significantly reduced when text-mined footnotes data were jointly used. We believe this result came from the fact that discretionary financial figures, which were hardly predicted with quantitative financial data, were more correlated with footnotes texts.

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References

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