A recent study has thrown light on the potential of AI-driven chatbot ChatGPT to replace human investment analysts. The study conducted by University of Florida professors discovered that ChatGPT displays remarkable abilities in accurately predicting stock market trends. As a result, this has caused speculations regarding the possibilities of replacing human investment analysts with artificial intelligence.
According to the research, ChatGPT outperforms traditional sentiment analysis methods which involves analyzing news headlines. To assess its predictive capabilities, the researchers gave the chatbot more than 50,000 dated news headlines related to certain companies. Subsequently, questions were posed about the impact the headlines would have on the firm’s stock prices.
To measure its performance, the chatbot was assigned a unique scoring system referred to as the “ChatGPT” score. After that, the score was analyzed to gauge the effects on the stock performance of the companies the following day. When compared to traditional sentiment analysis, the ChatGPT score proved to be more reliable for evaluating stock performance.
AI is quickly seeing more acceptance in the finance sector with bots like ChatGPT leading the race. According to Fortune Magazine interview with the researchers, use of AI-driven models can result in increased accuracy and efficiency in analyzing vast data sets within the realms of asset management, stock trading, and finance regulation. While the chatbot lacks the ability to detect the negative implications of certain news headlines, its performance in predicting stock movements is still encouraging.
ChatGPT is a project developed by OpenAI and was propounded by researchers of the University of Florida. OpenAI is a major AI research laboratory with the mission to ensure that ‘friendly AI’ benefits all of humanity. It works in the space of artificial general intelligence, natural language processing, computer vision, and robotics. With the help of ChatGPT, OpenAI looks to improve accuracy and efficiency of then present AI models.
The research team at University of Florida is headed by Professor Eric Brown. He is a leading authority in the areas of segmentation, recommendation systems and natural language processing. His research interests cover a variety of fields such as machine learning, artificial intelligence, and computer vision. Professor Brown’s publications and conference presentations revolve around the development of new algorithms and models for better understanding of human behavior and preferences.
