- Bert stock prediction. The growth in the inflation rate has compelled people to invest in the stock and commodity markets and other areas rather than saving. However, due to the high volatility of the stock market and its sensitivity to news events, it is difficult to accurately predict the market trends. When breaking news occurs, stock quotes can change abruptly in a matter of seconds. This method Jun 25, 2024 · By processing a series of news articles, the BERT model can extract relevant information that reflects market sentiment, which is then used to enhance the input data for stock price Jan 21, 2025 · The Bert-BiLSTM based stock prediction model is established by collecting the stock price data of CSI 300 sector from 1 May 2021 to 1 May 2024 and obtaining the related news text using crawler technology. Dec 9, 2023 · Utilizing the BERT language model, known for its advanced text-encoding capabilities, FinancialBERT integrates semantic analysis of financial news into stock market forecasting. Starting with the data itself, Chen et al[9] and Long et al [24] used historical prices only for predicting stock prices. Stock price prediction has been done with a variety of techniques ranging from empirical, numerical, statistical to machine learning. Such challenging scenarios require faster ways to support investors. Dec 19, 2024 · Stock market prediction: Analyze the sentiment around companies and sectors in the news to predict stock price movements. Abstract : This comprehensive review paper extensively explores the transformative possibilities offered by BERT (Bidirectional Encoder Representations from Transformers) within the context of stock market prediction, emphasizing the incorporation of stock news titles and historical stock prices. ie6 3dz azd247 dijd2 d6jb 88n 30v cha re3l3 vgbhpwzs
