Classification of RBA monetary policy announcements using ChatGPT

Lee A. Smales

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Monetary Policy and Economic Impact Financial Markets and Investment Strategies Stock Market Forecasting Methods

Abstract

ChatGPT is a tool that has gained much attention and has accelerated the adoption of Artificial Intelligence across many applications. Using monetary policy decisions made by the Reserve Bank of Australia (RBA), we test whether ChatGPT’s classifications of monetary policy announcements are consistent with market-observed characteristics and whether this provides additional informativeness for changes in the yield implied by interest rate futures. Our results indicate that, regardless of statement readability, ChatGPT provides a classification of hawkish / dovish tone that is consistent with “Target Surprises” and “Path Surprises”. This information does not appear to help to explain changes in interest rate markets on the day of the policy announcement.

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References

2001Monetary policy surprises and interest rates: Evidence from the Fed funds futures market 2003A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables 2004Do Actions Speak Louder Than Words? The Response of Asset Prices to Monetary Policy Actions and Statements 2023ChatGPT is fun, but not an author 2008Central Bank Communication and Monetary Policy: A Survey of Theory and Evidence 2013Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks 2007Communication by Central Bank Committee Members: Different Strategies, Same Effectiveness?2011Global asset prices and FOMC announcements

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