A time-varying study of investor sentiment, stock market liquidity and volatility ——Based on deep learning BERT model and TVP-VAR model

Subjects: Computer Science >> Natural Language Understanding and Machine Translation submitted time 2022-05-10

张宸瑞 吴心怡 邓海露 张荟蔚

Abstract： <p>"Based on the review data of Shenzhen stock index BBS from January 1, 2018 to December 31, 2019, this paper extracts the investor sentiment contained in it by using the deep learning BERT model, and studies the time-varying linkage relationship among investment sentiment, stock market liquidity and volatility by using TVP-VAR model. The experimental results show that investor sentiment has a stronger impact on the liquidity and volatility of the stock market, while the reverse impact is relatively small, but it changes more significantly with the state of the stock market. In addition, in all cases, the short-term response is more significant than that in the medium and long term, and the impact is asymmetric, and the impact in the market downturn is stronger.</p>

Peer Review Status:Awaiting Review

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