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.
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Notes
- 1.
Refer to the paper for details of the formula Dheeraj et al. [6].
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Fujiwara, S., Matsumoto, Y., Suge, A., Takahashi, H. (2020). Constructing a Valuation System Through Patent Document Analysis. In: Jezic, G., Chen-Burger, J., Kusek, M., Sperka, R., Howlett, R., Jain, L. (eds) Agents and Multi-Agent Systems: Technologies and Applications 2020. Smart Innovation, Systems and Technologies, vol 186. Springer, Singapore. https://doi.org/10.1007/978-981-15-5764-4_30
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