CAREER
Prof Yukari SHIROTA (Professor of Gakushuin University) graduated from the Department of Information Science, Faculty of Science, the University of Tokyo, and then received a D.Sc. in computer science in 1998. As a researcher in the private sector, she conducted research for 13 years and then in 2001 she was involved in Faculty of Economics, Gakushuin University, Tokyo as Associate Professor. In 2002, she has become Professor, Faculty of Economics, Gakushuin University. In 2006 to 2007, she stayed at University of Oxford, Oxford, UK as an academic visitor. She is Fellow of Information Processing Society of Japan, a Board Member of the Japan Society of Business Mathematics, and a Board Member of the Japanese Operations Management and Strategy Association. Research fields are industry analysis by AI, visualization of data on the web, social media analysis, and visual education methods for business mathematics. She has read the paper in the top conference of the "AI in Finance" field: "An Analysis of Political Turmoil Effects on Stock Prices - a case study of US-China trade friction -" (ACM AI in Finance 2020). She organized the special session titled "Awareness Technology for Economic and Social Data Analysis" in IEEE iCAST in 2019 and 2020, so that they can discuss the economics/social themes with the latest machine learning technologies.
For over 23 years, she has developed visual teaching materials for business mathematics and statistics, and for mathematics used in AI (see the following sites):
https://www-cc.gakushuin.ac.jp/~20010570/mathABC/SELECTED/
https://www-cc.gakushuin.ac.jp/~20010570/SHIROTABASABI/
https://www-cc.gakushuin.ac.jp/~20010570/mathABC/SELECTED/ShapeAnalysis/
She has visited Indonesia for lectures and research, and published many papers with Indonesia researchers (see https://www-cc.gakushuin.ac.jp/~20010570/Indonesia/). Using tweets related to disasters such as COVID-19 and East Japan Great Earthquake, she has published topic extraction papers from the humanitarian standpoints with researchers of India, Indonesia, and Thailand.
Grants-in-Aid for Scientific Research (KAKENHI) B
"Industry Behavioral Structure Analysis by Machine Learning" (from 2020 to 2023)
Main Papers of the KAKENHI Project:
Y. Shirota, K. Yamaguchi, A. Murakami, and M. Morita, "An analysis of political turmoil effects on stock prices: a case study of US-China trade friction," in Proceedings of the First ACM International Conference on AI in Finance, 2020, pp. 1-7.
The conference is the top conference in the field of financial AI. It is great honor to be published as the first paper. In the analysis of the automakers' stock prices, we made the hypothesis that immediately after the stock price crashed, country-based clusters appear, and verified the hypothesis with the dual approach of hierarchical clustering HRP (Hierarchical Risk Parity) and singular value decomposition (SVD). (VIDEO)
Y. Shirota, M. Fujimaki, E. Tsujiura, M. Morita, and J. A. D. Machuca, "A SHAP Value-Based Approach to Stock Price Evaluation of Manufacturing Companies," in 2021 4th International Conference on Artificial Intelligence for Industries (AI4I), 2021, pp. 75-78: IEEE.
This paper applies SHAP-based regression analysis to the Japanese manufacturing industry, and proved that corporate skills related to supply chain management, such as inventory turnover, and sales growth rates are important factors for the stock growth. (VIDEO)