Forecasting the Taylor rule exchange rate model using directional change tests

Rudan Wang; Bruce Morley; Rudan Wang; Bruce Morley

doi:10.3934/QFE.2018.4.931

Quantitative Finance and Economics

2018, Volume 2, Issue 4: 931-951. doi: 10.3934/QFE.2018.4.931

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Research article

Forecasting the Taylor rule exchange rate model using directional change tests

Rudan Wang ¹,
Bruce Morley ^{2
,
,}

1.
Coventry University, UK
2.
Department of Economics, University of Bath, Bath, UK, BA2 7AY

Received: 17 September 2018 Accepted: 21 November 2018 Published: 03 December 2018
JEL Codes: C53, E44, F37, F41

This study uses the Taylor rule model of exchange rate determination, to analyse how accurately it can predict directional changes in the exchange rate. Using bilateral exchange rate data for the US, UK, Sweden and Australia, we conduct the Pesaran-Timmermann test to determine how accurately this model can forecast changes in direction. The results suggest that although in many studies the standard out-of-sample forecasting ability of this model has been successful, the performance of the change of direction predictions are not consistently accurate over all specifications tested, in which case they may not prove profitable in a trading environment.
- forecast,
- Taylor rule,
- exchange rate,
- prediction accuracy
Citation: Rudan Wang, Bruce Morley. Forecasting the Taylor rule exchange rate model using directional change tests[J]. Quantitative Finance and Economics, 2018, 2(4): 931-951. doi: 10.3934/QFE.2018.4.931

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Abstract

This study uses the Taylor rule model of exchange rate determination, to analyse how accurately it can predict directional changes in the exchange rate. Using bilateral exchange rate data for the US, UK, Sweden and Australia, we conduct the Pesaran-Timmermann test to determine how accurately this model can forecast changes in direction. The results suggest that although in many studies the standard out-of-sample forecasting ability of this model has been successful, the performance of the change of direction predictions are not consistently accurate over all specifications tested, in which case they may not prove profitable in a trading environment.

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