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Forecasting the Government Bond Term Structure in Australia
Author(s) -
Chen Rui,
Svec Jiri,
Peat Maurice
Publication year - 2016
Publication title -
australian economic papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 15
eISSN - 1467-8454
pISSN - 0004-900X
DOI - 10.1111/1467-8454.12071
Subject(s) - kalman filter , benchmark (surveying) , term (time) , government bond , econometrics , bond , government (linguistics) , state space , estimation , state space representation , economics , random walk , computer science , mathematics , statistics , geography , finance , algorithm , cartography , linguistics , physics , philosophy , management , quantum mechanics
In this paper, we evaluate the performance of the dynamic Nielsen and Siegel interest rate model in forecasting Australian government bond yields. We compare a two‐stage OLS estimation procedure to a more powerful and robust state‐space framework estimated via a Kalman filter. We show that the one‐step approach generates smaller forecast errors than the two‐step procedure or a benchmark random walk model when forecasting the Australian government term structure across various horizons.