Investment banks use OpenAI’s ChatGPT to sniff out trade signals from Federal Reserve policy statements.
Investment banking giant JPMorgan has reportedly launched an artificial intelligence (AI) tool to dissect Federal Reserve statements and speeches to describe implicit trade signals.
On April 27, Bloomberg reported that the Wall Street investment bank used a ChatGPT-based language model to digest comments from the governors of the United States central bank.
These Fed policy signals will be graded on a scale from easy to restrictive to decide on what the bank calls the Hawk-Dove Score.
“Hawish” is a financial policy term that refers to raising interest rates to keep the pretense under control. The opposite is “Dovish,” which supports expansionary financial policies and lower interest rates.
AI tools will give judges a way to describe policy changes which can provide banks with more information about trading signals. “Primary surgery has been very encouraging,” said JPMorgan economist Joseph Lupton.
The tool can be used to forecast changes in central bank tightening. A hawkish policy statement as an illustration can affect one-off government bond yields.
According to JPMorgan’s model, which can dissect a statement 25 times, Fed sentiment has changed recently but remains hawkish in general.
The Federal Reserve is expected to raise its standard interest rate by another 25 basis points to 5.25% next week, according to Bloomberg.
A 10 point increase in the Hawk-Dove Score indicates a ten percent chance that there will be a rate hike at the upcoming policy meeting and vice versa.
JPMorgan is interested in operating AI for its benefit but not so interested in letting its workers use it.
In February, the company restricted its staff from using ChatGPT, according to reports. No specific incidents prompted the decision to block workers from penetrating AI chatbots and other companies have made similar moves.
In a periodic letter to shareholders earlier this month, JPMorgan CEO Jamie Dimon revealed that the bank has more than 300 AI use cases in products.
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