Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data

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.

KEYWORDS:

• Interest rates
• volatility
• GARCH models
• forecasting
• error distributions

JEL:

• C22
• C53
• G17

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Taylor [27] showed in some financial time series, the sample autocorrelation of absolute returns was larger than that of squared returns.

2 The test is applied using the ‘fUnitRoots’ package in R.

Additional information

Funding

Juncal Cuñado gratefully acknowledges financial support from the Ministerio de Economía y Competitividad (ECO2017-83183-R).