@techreport{oai:ipsj.ixsq.nii.ac.jp:00233577,
 author = {鈴木, 智也 and 望月, 孝太郎 and 田村, 空生 and 加唐, 丈裕},
 issue = {2},
 month = {Mar},
 note = {2023 年に東京証券取引所が PBR1 倍未満の企業に対して是正要求したことを背景に，上場企業の自社株買い行動が注目されている．自社株買いを行う背景や動機はある程度パターン化できると仮定し，過去の自社株買い実績と当時の企業財務状況の関係性を機械学習することで予測モデルを構築し，自社株買い行動の予測可能性および発生パターンを分析する．さらに自社株買いは株価上昇効果を期待できるため，株式ポートフォリオ運用への応用可能性を検証する．, With the Tokyo Stock Exchange requiring the companies whose PBR is less than 1 for its improvements in 2023, corporate stock buybacks have been attracting attention. Assuming that the background and motivation of corporate stock buybacks can be patterned to some extent, we made its prediction model using machine learning tools and analyzed the predictability and occurrence patterns of corporate stock buybacks. Moreover, since stock buybacks might have some impact to increase stock prices, we examined the applicability of our prediction model to asset management business such as stock portfolio management.},
 title = {機械学習による企業の自社株買い行動の予測可能性},
 year = {2024}
}