The AI model analyzed speeches from the U.S. Federal Reserve from the past 25 years to determine the nature of policy signals and gain a trading advantage.
Analysts at JPMorgan Chase & Co. have used a ChatGPT-based artificial intelligence model to analyze statements and speeches from the U.S. Federal Reserve in the past 25 years to determine the nature of policy signals.
The researchers found that when the AI tool showed a rise in hawkishness in Fed speakers between meetings, the next policy statement was indeed more hawkish. Hawkish is the term used to describe the outlook of central bankers when they intend to increase interest rates to fight inflation. On the other hand, a dovish outlook aims to reduce interest rates to promote growth.
According to the JPMorgan AI model, Fed statements in recent months have shown fluctuations, and hawkishness had relatively reduced. However, it was still close to the highest levels of hawkishness seen in the past two decades. This suggests that the Fed policy is unlikely to change, which can be confirmed when the US central bank announces interest rates next week.
The JPMorgan model has also analyzed the monetary policy outlook for the Bank of England and the European Central Bank. In the coming months, it is expected to expand to another 30 central banks around the world.
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