DOI: 10.11606/d.104.2022.tde-09082022-085154
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Bayesian inference for term structure models

Abstract: We explore recent advances in Bayesian methods in order to estimate the Vasicek, CIR and dynamic Nelson-Siegel (DNS) models for term structure of interest rates. The models are specified as state space time series. The main goal of this work is assessing and comparing the forecasting abilities of each model with respect to the observed data via mean absolute error. When estimated with synthetic simulated datasets, the models are able to successfully recover the latent vectors. As for the forecasting abilities,… Show more

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