Keywords
DYNAMIC NELSON-SIEGEL MODEL (DNS)
KALMAN FILTER
VECTOR AUTOREGRESSIVE MODEL (VAR)
OPTIMIZATION
How to Cite
Abstract
This research seeks to contribute to the management of international reserves of central banks due to the importance of an adequate estimation of interest rates of U.S. Treasury bonds and the respective yield curve, where in recent years the strong influence exerted by global crises such as the COVID-19 pandemic and geopolitical conflicts on the evolution of these rates has been observed. The study is based on the case of the Central Bank of Costa Rica, for which three mathematical prediction models were proposed using a vector autoregressive model and two variants of the Nelson-Siegel dynamic model, based on the yield curve and using financial indexes and macroeconomic variables of the United States, such as consumer price indexes, inflation expectations, manufacturing capacity, and the federal funds rate, among others. The parameters of the models were adjusted with optimization techniques and linear estimators such as the Kalman Filter, validating the results with those previously published in the state of the art and with an updated database from 2000 to 2022. A comparison of the accuracy of the yield curve forecast was carried out, managing to approximate with very low error rates the interest rates with different maturities. The incorporation of the developed models has the potential to become an important support and reference to maintain and generate higher returns.
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Copyright (c) 2025 Leonardo Marín Paniagua, Mercedes Chacón Vásquez (Author)