Intraday Trading Dynamics of Characteristics and Sentiment Tendencies of Past News in the Tokyo Stock Exchange Market

Sungjae Yoon () and Hiroshi Takahashi ()
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Sungjae Yoon: Keio University
Hiroshi Takahashi: Keio University

Computational Economics, 2025, vol. 66, issue 5, No 13, 3983-4007

Abstract: Abstract This study investigates the impact of characteristics and sentiment tendencies of past news on stocks on the Tokyo Stock Exchange (TSE) by focusing on the intraday trading volume fluctuation of multiple stocks due to news using news data, tick data, and two FinBERT*models based on $$\hbox {BERT}^{\dag }$$ BERT † that were proposed to analyze sentiments of texts in the finance sector. We find that small-capitalization stocks have a higher intraday volume fluctuation by dispersion and asymmetry of information-effects that are consistent with those of previous studies. Moreover, negative news is more volatile than other sentiments, which effect is stronger for small-capitalization stocks. Furthermore, the intraday volume fluctuation tends to be higher when urgent news is released or when volatility is high, suggesting that relatively small-capitalization stocks lean toward being traded more sensitively. The results of this analysis focusing on intraday trading volume fluctuation were derived using tick data and the most advanced analytical methodologies; they are consistent with those of previous studies that used daily data. The findings are interesting, as they contribute to the clarification of the price mechanism of the stock market. This type of analytical approach will be useful for similar studies in the future.

Keywords: Intraday trading dynamics; News; Natural Language Processing; Sentiment analysis; Information asymmetry; Market reaction (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-024-10768-1

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