Constructing a valuation system through patent document analysis

Shohei Fujiwara, Yusuke Matsumoto, Aiko Suge, Hiroshi Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the Initial Public Offering (IPO), many prior studies have discussed underpricing, where the public price is below the initial price. In this study, we propose a novel system for company valuation employing patent document analysis. Specifically, we first extracted patent document data published from 2001 to 2015 and vectorize them through Sparse Composite Document Vectors (SCDV). Similar companies in this study refer to the same industry, products handled, and business scale. However, there are various theories on what should be treated as similar companies. Next, the center of gravity is calculated from the vectorized patent document, and comparable companies are selected by expressing the distance between companies. A detailed analysis is planned for further study.

Original languageEnglish
Title of host publicationAgents and Multi-Agent Systems
Subtitle of host publicationTechnologies and Applications - 14th KES International Conference, KES-AMSTA 2020, Proceedings
EditorsG. Jezic, M. Kusek, J. Chen-Burger, R. Sperka, Robert J. Howlett, Robert J. Howlett, Lakhmi C. Jain, Lakhmi C. Jain, Lakhmi C. Jain
PublisherSpringer
Pages321-330
Number of pages10
ISBN (Print)9789811557637
DOIs
Publication statusPublished - 2020 Jan 1
Event14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2020 - Split, Croatia
Duration: 2020 Jun 172020 Jul 19

Publication series

NameSmart Innovation, Systems and Technologies
Volume186
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2020
CountryCroatia
CitySplit
Period20/6/1720/7/19

Keywords

  • Corporate finance
  • Natural language processing
  • Patent
  • Sparse Composite Document Vectors
  • Valuation

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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