Masahiro Suzuki

Masahiro Suzuki
The University of Tokyo | Todai · Department of Systems Innovation

Bachelor of Engineering

About

9
Publications
350
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
9
Citations
Introduction
Financial Text Mining, Natural Language Processing, Language Model

Publications

Publications (9)
Article
Full-text available
This article proposes a methodology to forecast the movements of analysts' estimated net income and stock prices using analyst profiles. Our methodology is based on applying natural language processing and neural networks in the context of analyst reports. First, we apply the proposed method to extract opinion sentences from the analyst report whil...
Conference Paper
Full-text available
本研究では決算短信や有価証券報告書を用い,言語モデルの BERT と ELECTRA につ いて,事前学習や追加で事前学習 (追加事前学習) を行いモデルを構築する.構築したモデルについて,金融ドメインのタスクによって汎用コーパスを用いたモデルとの性能を比較する.その際,ファインチューニングを行う層の数などパラメーターによる性能についても比較を行う.構築した一部のモデルについては一般に公開する.
Conference Paper
This study demonstrates whether analysts' sentiment toward individual stocks is useful in predicting the macroeconomic index. This can be achieved by using natural language processing to create polarity indexes from analyst reports. In this study, the created polarity indexes were analyzed using the Vector Autoregressive model with various macroeco...
Conference Paper
Full-text available
BERT を始めとする事前学習言語モデルは,様々な自然言語処理のタスクにおいて成果を上げている.これらのモデルの多くは Wikipedia やニュース記事などの一般的なコーパスを用いているため,専門的な単語が使用される金融分野においては十分な効果が得られない.本研究では決算短信や有価証券報告書から事前学習言語モデルを構築する.また金融ドメインのタスクによって汎用モデルとの性能を比較する.
Conference Paper
Full-text available
本研究では, アナリストの個別銘柄に対するセンチメントが, マクロ経済指標の予測に役 立つかを実証する. これはアナリストレポートのテキスト情報を自然言語処理を使用して極性指標を作成することで実現可能となる. 本研究では, 作成した極性指標に対し, 各種マクロ経済指標を使用し,VAR モデルを用いた分析を行った. 結果, 極性指標から物価, 為替, 国債等の指標へのグレンジャー因果性があることが確認された. これにより, 極性指標が先行しており, マクロ経済指標の予測に役立つことが示唆された.
Conference Paper
Recently, general-purpose language models pre-trained on large corpora such as BERT have been widely used. In Japanese, several pre-trained models based on Wikipedia have been published. On the other hand, general-purpose models may not be sufficiently effective in the financial domain because of the use of specialized phrases. In this study, we co...
Conference Paper
In this paper, we propose a methodology of forecasting the change rate of net income which an analyst estimates by applying natural language processing and neural networks in the context of analyst reports. We examine the contents of the reports for useful information on forecasting the direction of revision in analyst estimate earnings. First, our...
Article
Full-text available
This paper proposes and analyzes a methodology of forecasting movements of the analysts’ net income estimates and those of stock prices. We achieve this by applying natural language processing and neural networks in the context of analyst reports. In the pre-experiment, we applied our method to extract opinion sentences from the analyst report whil...

Network

Cited By