Presentation 2019-02-22
Analysis of structural changes in domestic stock market
Yoshiki Kishi, Teruaki Hayashi, Yukio Ohsawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Grasping the trend of the stock market is important for people engaged in financial markets such as individual investors and institutional investors. In this study, we analyzed the stocks that were traded on the Tokyo Stock Exchange, using the clustering algorithm “k-Shape” which is appropriate for extracting the shape characteristics of the time series sequence. In addition, we introduced an index reflecting the trend of the stock market, and read the structural changes of the stock market from the change of the index. This indicator is thought to suggest the effectiveness of investment in stocks, and showed the possibility of a reference to the investment decision of other assets other than the stock.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Finance / Time series / Clustering
Paper # AI2018-47
Date of Issue 2019-02-15 (AI)

Conference Information
Committee AI
Conference Date 2019/2/22(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Tsunenori Mine(Kyushu Univ.)
Vice Chair Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.)
Secretary Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.)
Assistant Yuko Sakurai(AIST)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analysis of structural changes in domestic stock market
Sub Title (in English)
Keyword(1) Finance
Keyword(2) Time series
Keyword(3) Clustering
1st Author's Name Yoshiki Kishi
1st Author's Affiliation The University of Tokyo(UT)
2nd Author's Name Teruaki Hayashi
2nd Author's Affiliation The University of Tokyo(UT)
3rd Author's Name Yukio Ohsawa
3rd Author's Affiliation The University of Tokyo(UT)
Date 2019-02-22
Paper # AI2018-47
Volume (vol) vol.118
Number (no) AI-453
Page pp.pp.57-59(AI),
#Pages 3
Date of Issue 2019-02-15 (AI)