人工知能学会第二種研究会資料
Online ISSN : 2436-5556
第28回金融情報学研究会
機械学習を用いたアナリストレポート分析と投資判断レーティング予測
鈴木 章悟小澤 誠一渡辺 一男廣瀨 勇秀池田 佳弘飯塚 正昭西田 大輔
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研究報告書・技術報告書 フリー

2022 年 2022 巻 FIN-028 号 p. 164-

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Fund managers at investment trust management companies make investment policy decisions by referring to the results of research on candidate companies for investment compiled by analysts. However, when there are many candidate companies, it is necessary to refer to a considerable number of reports, which is considered dificult to read carefully. Therefore, technology is required to (1) accurately determine the business sentiment of the companies concerned and (2) extract important information for investment decisions from the contents of the reports. In this study, we developed a machine learning model that predicts the rating, which is a rating index for investment decisions, in order to support the work of fund managers, especially for the requirement (1). There are two types of ratings that afiect investment decisions: outperform and underperform. Since the number of cases that fall into these two categories is small compared to other ratings, we attempted to expand the data of documents that give the same rating. As an existing data expansion method, there is a method to expand data by synonyms that can be obtained from WordNet. In this study, we propose a method to expand data based on the frequency of occurrence in financial documents. As a result of experiments, we verified the efiectiveness of the proposed data expansion method.

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