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Multifactorial Heath-Jarrow-Morton model using principal component analysis
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Multifactorial Heath-Jarrow-Morton model using principal component analysis
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Multifactorial Heath-Jarrow-Morton model using principal component analysis
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Multifactorial Heath-Jarrow-Morton model using principal component analysis
Multifactorial Heath-Jarrow-Morton model using principal component analysis
Journal Article

Multifactorial Heath-Jarrow-Morton model using principal component analysis

2024
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Overview
In this study, we propose an implementation of the multifactor Heath-Jarrow-Morton (HJM) interest rate model using an approach that integrates principal component analysis (PCA) and Monte Carlo simulation (MCS) techniques. By integrating PCA and MCS with the multifactor HJM model, we successfully capture the principal factors driving the evolution of short-term interest rates in the US market. Additionally, we provide a framework for deriving spot interest rates through parameter calibration and forward rate estimation. For this, we use daily data from the US yield curve from June 2017 to December 2019. The integration of PCA, MCS with multifactor HJM model in this study represents a robust and precise approach to characterizing interest rate dynamics and compared to previous approaches, this method provided greater accuracy and improved understanding of the factors influencing US Treasury Yield interest rates.

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