Forecasting Interest Rate Volatility of the United Kingdom: Evidence from over 150 Years of Data

Hossein Hassani (), Mohammad Yeganegi (), Juncal Cunado () and Rangan Gupta
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Hossein Hassani: The Statistical Research Centre, Bournemouth University, Bournemouth, UK
Mohammad Yeganegi: Department of Accounting, Islamic Azad University Central Tehran Branch, Iran
Juncal Cunado: University of Navarra, School of Economics, Edificio Amigos, E-31080 Pamplona, Spain

No 201873, Working Papers from University of Pretoria, Department of Economics

Abstract: This study examines the very short, short, medium and long-term forecasting ability of different univariate GARCH models of United Kingdom (UK)'s interest rate volatility, using a long span monthly data from May 1836 to June 2018. The main results show the relevance of considering alternative error distributions to the normal distribution when estimating GARCH-type models. Thus, we obtain that the Asymmetric Power ARCH (A-PARCH) models with skew generalized error distribution are the most accurate models when forecasting UK interest rates, while for the short, medium and longterm term forecasting horizons (h=3 and h=6, h=12), GARCH models with generalized error distribution for the error term are the most accurate models in forecasting UK's interest rates.

Keywords: interest rates; volatility; GARCH models; forecasting; error distributions (search for similar items in EconPapers)
JEL-codes: C22 C53 G17 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2018-11
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Journal Article: Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data (2020)
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