Research on Application of Financial Large Language Models

With the increasing use of large language models such as chatgpt, it is not difficult to apply their capabilities to the research of natural language processing in the financial field, including but not limited to text extraction, sentiment analysis, etc. This paper analyzes the construction ideas and applications of three financial big language models, including BloombergGPT, PIXIU and FinBERT, and concludes that the current application of big language models in the financial field is possible, multi-faceted and suitable, but there are still shortcomings in ethics, data processing and other aspects. The application of large language models in the field of finance is still something to look forward to. Through this study and the comparative exploration of various models, we hope to provide valuable modeling experience for practitioners in the field of finance or computer. At the same time, it is hoped that each researcher can follow the ideas of these model-making teams to make up for the shortcomings in their own models and make their own financial big language models better.