Bayesian extensions to Diebold-Li term structure model

This paper proposes a statistical model to adjust, interpolate, and forecast the term structure of interest rates. The model is based on the extensions for the term structure model of interest rates proposed by Diebold and Li (2006), through a Bayesian estimation using Markov Chain Monte Carlo (MCMC). The proposed extensions involve the use of a more flexible parametric form for the yield curve, allowing all the parameters to vary in time using a structure of latent factors, and the addition of a stochastic volatility structure to control the presence of conditional heteroskedasticity observed in the interest rates. The Bayesian estimation enables the exact distribution of the estimators in finite samples, and as a by-product, the estimation enables obtaining the distribution of forecasts of the term structure of interest rates. Unlike some econometric models of term structure, the methodology developed does not require a pre-interpolation of the yield curve. The model is fitted to the daily data of the term structure of interest rates implicit in SWAP DI-PRÉ contracts traded in the Mercantile and Futures Exchange (BM&F) in Brazil. The results are compared with the other models in terms of fitting and forecasts.