Efficient Yield Curve Estimation and Forecasting in Brazil

Revista Economia, January/April 2010

25 Pages Posted: 21 Jun 2012

See all articles by João Caldeira

João Caldeira

Universidade Federal do Rio Grande do Sul (UFRGS)

Guilherme V. Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Marcelo Savino Portugal

affiliation not provided to SSRN

Date Written: 2010

Abstract

Modeling the term structure of interest rate is very important to macroeconomists and financial market practitioners in general. In this paper, we used the Diebold-Li interpretation to the Nelson Siegel model in order to fit and forecast the Brazilian yield curve. The data consisted of daily observations of the most liquid future ID yields traded in the BM&F from January 2006 to February 2009. Differently from the literature on the Brazilian yield curve, where the Diebold-Li model is estimated through the two-step method, the model herein is put in the state-space form, and the parameters are simultaneously and efficiently estimated using the Kalman filter. The results obtained for the fit and for the forecast showed that the Kalman filter is the most suitable method for the estimation of the model, generating better forecast for all maturities when we consider the forecasting horizons of one and three months.

Keywords: Term Structure of the Interest Rate, Yield Curve, State-Space Model, Kalman Filter

JEL Classification: C53, E43, G17

Suggested Citation

Caldeira, João and Moura, Guilherme Valle and Savino Portugal, Marcelo, Efficient Yield Curve Estimation and Forecasting in Brazil (2010). Revista Economia, January/April 2010. Available at SSRN: https://ssrn.com/abstract=2089007

João Caldeira (Contact Author)

Universidade Federal do Rio Grande do Sul (UFRGS) ( email )

Av. Carlos Gomes 1111
Porto Alegre, Rio Grande do Sul 90480-004
Brazil

Guilherme Valle Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )

PO Box 476
Florianopolis, SC 88010-970
Brazil

Marcelo Savino Portugal

affiliation not provided to SSRN ( email )

Register to save articles to
your library

Register

Paper statistics

Downloads
126
Abstract Views
695
rank
223,230
PlumX Metrics