Impact of Investor Sentiment on Stock Returns Using Fine-tune BERT.

Chien-Cheng Lee, Hung-Chun Huang,Chun-Li Tsai

ICCE-TW(2021)

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摘要
In this study, we explore the impact of investor sentiment on stock returns. We fine-tune the BERT language model to capture investor sentiment from messages posted on the social media platform StockTwits. Apple Inc. (AAPL) stock is selected in this investigation because it has more significance in statistics based on its tremendous messages on StockTwits. A linear regression model is constructed to analyze the relationship between investor sentiment and stock returns. The experimental results show that there is a positive correlation between stock returns and investor sentiment. The investor sentiment can impact the Apple Inc. stock return.
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关键词
fine-tune BERT,investor sentiment,BERT language model,social media platform,StockTwits,AAPL stock,linear regression model,Apple Inc. stock return,statistics
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