主催: 横断型基幹科学技術研究団体連合
会議名: 第10回横幹連合コンファレンス
回次: 10
開催地: 新潟県長岡市 長岡技術科学大学
開催日: 2019/11/30 - 2019/12/01
News has great impacts on asset prices in the financial markets. Many attempts have been reported to ascertain how news influences stock prices. However, the limitations in the number of available data sets usually become the hurdle for the model accuracy. In this study, Reuter's news texts were classified based on each return through LSTM models. As a result of the analysis, we found the prediction accuracy could be improved by using texts generated by GPT-2. Further examination of the classification model will be planned.
