BreakGPT: A Large Language Model with Multi-stage Structure for Financial Breakout Detection

PAPER LINK: https://arxiv.org/pdf/2402.07536.pdf

Recently, large language models have achieved success in various downstream domains, but their effectiveness in the field of financial breaktout detection is at a lower level. This is specifically manifested in three aspects: 1. Lack of professional knowledge; 2. There are errors in the answers, and the accuracy on the task is low; 3. The model output is unstable. For the same output, repeated output will give different judgment results.

In response to the above problems, we introduced BreakGPT, with specific contributions in the following three aspects:

1. This is the first financial breakout detection model. It has expertise in breakthrough trading areas;
2. We innovatively established a new framework for this large language model, namely the Multi-stage Structure, which effectively reduces errors in downstream applications and improves the stability of the output. In terms of accuracy, it has improved by 44% compared to ChatGPT-3.5 and 42.07% compared to ChatGPT-4;
3. The first dataset in the field of financial breakout detection is established, which can help subsequent research.