An Infinite Hidden Markov Model with GARCH for Short-Term Interest Rates

Li, Chenxing and Yang, Qiao (2025): An Infinite Hidden Markov Model with GARCH for Short-Term Interest Rates.

Abstract

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury bill rates, the GARCH-IHMM reveals both structural and persistent changes in volatility, thereby enhancing the accuracy of density forecasts compared to existing benchmark models. Out-of-sample evaluations demonstrate the superior performance of our model in density forecasts and in capturing volatility dynamics due to its adaptivity to different macroeconomic environments.

• Item Type: MPRA Paper
• Language: English
• Keywords: Interest rates; Bayesian nonparametrics; GARCH; density forecasts
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E43 - Interest Rates: Determination, Term Structure, and Effects; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E47 - Forecasting and Simulation: Models and Applications; G - Financial Economics > G1 - General Financial Markets > G17 - Financial Forecasting and Simulation

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