[2K1] AI応用-テキスト処理応用

[2K1-04] 高頻度データを用いたニュースと韓国株式の分析：ニュース分類の条件探索

尹 聖在¹、〇菅 愛子¹、高橋 大志¹ (1. 慶應義塾大学)

キーワード：ハイパーパラメータ、LSTM、高頻度データ、文書分類

News articles play an important role in financial markets.　This study　analyzes the relationship between news articles and stock price fluctuations using high frequency trading data in Korean stock markets.　Especially, we analyze differences in market reactions according to　languages of news articles. In order to understand the influences of　news articles, this study explores conditions of Long Short Term Memory　(LSTM) models that classify news articles.