Forecasting Bond Yields with Segmented Term Structure Models

Caio Almeida (), Kym Ardison, Daniela Kubudi, Axel Simonsen and José Vicente

Journal of Financial Econometrics, 2018, vol. 16, issue 1, 1-33

Abstract: Inspired by the preferred habitat theory, we propose parametric interest rate models that split the term structure into segments. The proposed models are compared with successful term structure benchmarks based on out-of-sample forecasting exercises using U.S. Treasury data. We show that segmentation can improve long-horizon term structure forecasts when compared with nonsegmentation. Additionally, introducing cointegration in latent factor dynamics of segmented models makes them particularly strong to forecast short-maturity yields. Better forecasting is justified by the segmented models’ ability to accommodate idiosyncratic shocks in the cross-section of yields.

Keywords: Error Correction Model; exponential splines; local shocks; model selection; preferred habitat theory (search for similar items in EconPapers)
JEL-codes: C53 C58 E43 G17 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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Working Paper: Forecasting Bond Yields with Segmented Term Structure Models (2012)
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