Unveiling Market Regimes: A Hidden Markov Model Application for Central Bank Interest Rate Prediction

Tampouris Achilleas () and Chaido Dritsaki ()
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Tampouris Achilleas: University of Western Makedonia, Kila Campus
Chaido Dritsaki: University of Western Makedonia, Kila Campus

Chapter Chapter 15 in Advances in Applied Macroeconomics, 2025, pp 283-297 from Springer

Abstract: Abstract Accurately predicting central bank interest rates is crucial for understanding future economic conditions and formulating effective monetary policy. This study leverages a linear regression model trained on historical interest rate and inflation data to forecast the central bank interest rates for various countries in 2024. In addition, this research employs Hidden Markov Models (HMMs) to provide deeper insights into the underlying economic conditions influencing these predictions. HMM analysis assigns countries to different hidden states, reflecting various economic environments and challenges. These methodologies together offer a comprehensive framework for anticipating and preparing for future monetary policy actions. The findings hold valuable implications for policymakers and financial market participants, guiding them in navigating complex economic landscapes and addressing potential challenges effectively.

Keywords: Central bank interest rates; Inflation; Hidden Markov Models (HMMs); Forecasting (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-76658-9_15

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DOI: 10.1007/978-3-031-76658-9_15

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