2023 Fiscal Year Final Research Report
Development of Software for Estimating the Price of Intangible Assets Using Multivariate Analysis
| Project/Area Number |
21K01819
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 07100:Accounting-related
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| Research Institution | Teikyo Heisei University |
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Principal Investigator |
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | 無形資産評価 / 多変量解析 / 機械学習 / 回帰モデル / 財務分析 / 企業価値評価 |
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| Outline of Final Research Achievements |
This research developed a method to estimate a company's intangible assets using multivariate analysis and machine learning, and implemented it as software. Based on the financial data of companies listed on the Tokyo Stock Exchange Prime Market, a predictive model for intangible fixed assets was constructed. By using generative AI to create synthetic data, the accuracy and generalizability of the model were enhanced. As a result, companies and industries with a high probability of unrecorded intangible fixed assets were identified, proposing a new evaluation method that contributes to an accurate reflection of corporate value. This is expected to provide investors and managers with information for more accurate decision-making and enhance the transparency and reliability of corporate financial reporting.
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| Free Research Field |
データサイエンス
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| Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義は、無形資産の評価において従来の評価手法を補完する新しい方法を開発し、生成AIを活用して合成データを作成することで、モデルの精度と汎用性を向上させた点にある。これにより、従来の評価手法と併用することで、より正確で客観的な無形資産評価が可能となり、学術的に重要な貢献を果たしている。社会的意義としては、企業価値の正確な評価が投資家や経営者にとって重要な情報を提供し、より適切な意思決定を支援する点が挙げられる。特に、無形資産の存在が企業の財務報告に適切に反映されることで、財務報告の透明性と信頼性が向上し、経済全体の健全性にも寄与することが期待される。
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