In an extensive study published earlier this year, researchers found that ChatGPT outperformed traditional sentiment analysis methods for accurately predicting stock movements.

“Our results suggest that incorporating advanced language models into the investment decision-making process can lead to more accurate predictions and improve the performance of quantitative trading strategies,” the pair wrote in their paper, titled, Can ChatGPT predict stock price movements? Return predictability and large language patterns.

Their research is based on sentiment analysis of news headlines over a sample period beginning in October 2021. and ending in December 2022.

"To perform our analysis, we first obtain daily stock returns for all US common stocks from the CRSP database and then construct a comprehensive set of news headlines related to those stocks from mainstream media and news channels," the researchers said.

“For each headline, we use ChatGPT to assess whether it is good, bad or neutral for the companies' share prices.

“We convert these responses into numerical results and use them to predict stock returns on the next trading day. We document a significantly positive correlation between ChatGPT scores and subsequent daily stock returns.”

The researchers believe their findings have important implications for the financial industry employment landscape.

"The results could potentially lead to a change in the methods used to forecast the market and make investment decisions," the pair said.

In addition to employment implications, the researchers said their findings could help regulators and policymakers understand the potential benefits and risks associated with the growing adoption of such AI tools in financial markets, while also benefiting asset managers and institutional investors.

"This insight can help these professionals make more informed decisions about including LLMs." [large language models] in their investment strategies, potentially leading to improved performance and reduced reliance on traditional, more labor-intensive methods of analysis,” said Mr. Lopez-Lira and Mr. Tang.

In short, the pair noted, "our study demonstrates the value of ChatGPT in predicting stock market returns."

"As the field of AI-driven finance continues to expand, the insights gleaned from this research can help guide the development of more accurate, efficient and responsive models that improve the efficiency of financial decision-making processes .”

Earlier this year, Alvin Chia, senior vice president - head of digital asset innovation at Northern Trust, and Krishan Dave, head of investment risk and analytics services at Northern Trust, said in a joint post that while ChatGPT and generative AI are new to public consciousness, they have the power to change the face of every industry on the planet.

"But we believe that in the short term, the role of generative AI will be limited to supporting existing research and data collection, rather than being the primary driver of decisions," the pair said.

“Our current knowledge of generative AI does not allow us to distinguish false positives from real data, which leads to additional risk for portfolio managers. But that doesn't stop us from taking a longer-term view of how generative AI could shape the investment management industry.

As for exactly how AI might impact investment management in the future, Mr Chia and Mr Dave said real-time dashboards powered by generative AI could help managers spot trends.

"Along with market data, generative AI can combine esoteric data sets such as sentiment analysis or keyword searches that generative AI deems most relevant," they said.

"It can reveal hidden trends or 'black swan' events that have not been seen before, providing a unique view of the investment horizon faster than ever before."

Ultimately, the pair reckoned, the actual integration of generative AI has yet to fully materialize today.

"An organization should consider where it is comfortable to introduce AI and the areas that are 'off limits.'

"Having a clear vision describing what needs to be achieved and what success looks like can help drive development, while of course being aware of potential biases and emerging ethical issues based on the datasets."

Maja Garatsa Djurdjevic

Maya's career in journalism spans more than a decade in finance, business and politics. Now an experienced editor and reporter in all elements of the financial services sector, before joining Momentum Media, Maya reported for several established news outlets in South East Europe, looking at key processes in post-conflict societies.