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Gaussian estimation and forecasting of the U.K. yield curve with multi-factor continuous-time models

Diana Tunaru

International Review of Financial Analysis, 2017, vol. 52, issue C, 119-129

Abstract: In this paper we will estimate the term structure of daily U.K. interest rates using a range of more flexible continuous-time models. A multivariate framework is employed for the dynamic estimation and forecasting of four classic models over the eventful period of 2000–2013. The extensions are applied in two stages to four- and five-factor formulations, allowing us to assess the potential benefit of gradually increasing the model-flexibility. The Gaussian estimation methods for dynamic continuous-time models yield insightful comparative results concerning the two different segments of the yield curve, short- and long-term, respectively. In terms of in-sample performance the newly extended multi-factor general model is superior to all other restricted models. When compared to benchmark discrete-time models, the out-of-sample performance of the extended continuous-time models seems to be consistently superior with regards to the short-term segment of the yield curve.

Keywords: Continuous-time models; Forecasting; Gaussian estimation; Multi-factor diffusion models with feedbacks; Term structure of interest rates (search for similar items in EconPapers)
JEL-codes: G12 G17 C51 C58 (search for similar items in EconPapers)
Date: 2017
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