Proposal for Turning Point Detection Method Using Financial Text and Transformer

Author:

Taguchi Rei,Watanabe Hikaru,Sakaji Hiroki,Izumi Kiyoshi,Hiramatsu Kenji

Publisher

Springer Nature Switzerland

Reference18 articles.

1. Ito, T., Tsubouchi, K., Sakaji, H., Yamashita, T., Izumi, K.: Contextual sentiment neural network for document sentiment analysis. Data Sci. Eng. 5(2), 180–192 (2020)

2. Sakaji, H., Kuramoto, R., Matsushima, H., Izumi, K., Shimada, T., Sunakawa, K.: Financial text data analytics framework for business confidence indices and inter-industry relations. In: Proceedings of the First Workshop on Financial Technology and Natural Language Processing, pp. 40–46 (2019)

3. Yono, K., Sakaji, H., Matsushima, H., Shimada, T., Izumi, K.: Construction of macroeconomic uncertainty indices for financial market analysis using a supervised topic model. J. Risk Finan. Manag. 13(4), 79 (2020)

4. Jin, Z., Yang, Y., Liu, Y.: Stock closing price prediction based on sentiment analysis and LSTM. Neural Comput. Appl. 32(13), 9713–9729 (2020)

5. Hiramatsu, K., Miwa, K., Sakai, H., Sakaji, H.: [Analyst Report Tone Information Value] Anarisutorepōto no tōn no jōhō kachi (in Japanese), Shōken anarisutojānaru 59(2), Securities Anal. J. 59(2), 86–97 (2021)

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