Yield Curve Forecasting with the Burg Model

Pierre Rostan, Rachid Belhachemi and François-Éric Racicot ()

Journal of Forecasting, 2017, vol. 36, issue 1, 91-99

Abstract: We introduce a versatile and robust model that may help policymakers, bond portfolio managers and financial institutions to gain insight into the future shape of the yield curve. The Burg model forecasts a 20‐day yield curve, which fits a pth‐order autoregressive (AR) model to the input signal by minimizing (least squares) the forward and backward prediction errors while constraining the autoregressive parameters to satisfy the Levinson–Durbin recursion. Then, it uses an infinite impulse response prediction error filter. Results are striking when the Burg model is compared to the Diebold and Li model: the model not only significantly improves accuracy, but also its forecast yield curves stick to the shape of observed yield curves, whether normal, humped, flat or inverted. Copyright © 2016 John Wiley & Sons, Ltd.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:36:y:2017:i:1:p:91-99

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