Benzina reported — a new study by the professor of finance at the university of florida revealed the potential value of chatgpt in forecasting stock market movements。
In this study, more than 50,000 news headlines about major companies have been entered into this chat robot since october 2021, allowing it to assess whether the news is good or bad or whether it has nothing to do with the company's share price. Through emotional analysis, the chat robot produced a “chatgpt scores”, which were analysed by researchers to determine whether it could predict the stock market performance of the companies the next day。
The study found a significant positive correlation between chatgpt scores and the stock performance of the company analysed the following day. Higher-scoring companies tend to have better investment returns than lower-scoring companies. Chatgpt performed better than traditional methods of emotional analysis, although the latter also used headline news and social media data to predict stock movements。
Researchers concluded that incorporating advanced language models such as chatgpt into investment decision-making processes could lead to more accurate forecasts and improve the performance of quantitative trading strategies. Research shows that traditional models do not provide any higher predictive capacity than the emotional scores derived from chatgpt. These findings suggest that chatgpt may offer hope to investors seeking to predict future stock market movements。
At the same time, while the potential use of chatgpt and other advanced language models in predicting returns on the stock market is promising, if it fails to provide the desired accuracy and help, there are concerns in the market about the risks it may pose. Nevertheless, bloomberg recently released a new gpt-based language model called bloomberg gpt, which is training on a data set of english-language financial documents, news, regulatory documents, press releases and social media. The company stated that the new model would improve existing natural language processing tasks such as emotional analysis, classification of news, title generation, question and answer questions and other missions related to queries。
Bloomberg is not the only company to innovate in this area. Enterprises around the globe are eager to integrate artificial intelligence into existing business models, but supply is scarce. That's why genesisai is creating a market designed to help any enterprise integrate artificial intelligence into their existing models. The company is raising millions of dollars from diaspora investors to achieve this goal。
A few decades ago, jim simons, founder of hedge fund renaissance technologies, pioneered the use of machine learning to create algorithms that enable computers to use past data for investment decisions with minimal manual input. However, companies like it have not yet fully transitioned to automated operations using cutting-edge artificial intelligence (ai) methods such as self-learning or enhanced learning. Instead, they continue to rely on advanced statistical data and " theory first " approaches。
Whatever the concerns, the use of artificial intelligence in the financial sector is growing rapidly and may become a real changer in the industry's rules of the game。
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