Forecasting interest rate volatility of the United Kingdom : evidence from over 150 years of data
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Date
Authors
Hassani, Hossein
Yeganegi, Mohammad Reza
Cunado, Juncal
Gupta, Rangan
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis
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 long-term term forecasting horizons, GARCH models with generalized error distribution for the error term are the most accurate models in forecasting UK's interest rates.
Description
Keywords
Interest rates, Volatility, GARCH models, Forecasting, Error distributions, United Kingdom (UK)
Sustainable Development Goals
Citation
Hossein Hassani, Mohammad Reza Yeganegi, Juncal Cuñado & Rangan Gupta (2020): Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data, Journal of Applied Statistics 47(6): 1128-1143, DOI: 10.1080/02664763.2019.1666093. NYP.