Predicting the term structure of interest rates incorporating parameter uncertainty, model uncertainty and macroeconomic information
Michiel De Pooter,
Francesco Ravazzolo () and
Dick van Dijk ()
MPRA Paper from University Library of Munich, Germany
We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been used in the literature. We assess the relevance of parameter uncertainty by examining the added value of using Bayesian inference compared to frequentist estimation techniques, and model uncertainty by combining forecasts from individual models. Following current literature we also investigate the benefits of incorporating macroeconomic information in yield curve models. Our results show that adding macroeconomic factors is very beneficial for improving the out-of-sample forecasting performance of individual models. Despite this, the predictive accuracy of models varies over time considerably, irrespective of using the Bayesian or frequentist approach. We show that mitigating model uncertainty by combining forecasts leads to substantial gains in forecasting performance, especially when applying Bayesian model averaging.
Keywords: Term structure of interest rates; Nelson-Siegel model; Affine term structure model; forecast combination; Bayesian analysis (search for similar items in EconPapers)
JEL-codes: C53 E47 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac and nep-mon
Date: 2006-11-06, Revised 2007-03-03
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Working Paper: Predicting the Term Structure of Interest Rates: Incorporating Parameter Uncertainty, Model Uncertainty and Macroeconomic Information (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:2512
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