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Numerical issues in threshold autoregressive modelling of\ud time series

By Jerry Coakley, Ana-Maria Fuertes and Maria-Teresa Pérez

Abstract

This paper analyses the contribution of various numerical approaches to making the estimation of threshold autoregressive time series more efficient. It relies on the computational advantages of QR factorizations and proposes Givens transformations to update these factors for sequential LS problems. By showing that the residual sum of squares is a continuous rational function over threshold intervals it develops a new fitting method based on rational interpolation and the standard necessary optimality condition. Taking as benchmark a simple grid search, the paper illustrates via Monte Carlo simulations the efficiency gains of the proposed tools

Topics: QA
Publisher: Warwick Business School Financial Econometrics Research Centre
Year: 2001
OAI identifier: oai:wrap.warwick.ac.uk:1819

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