Forecasting the exchange rate using non-linear Taylor rule based models

Wang, Rudan, Morley, Bruce and Stamatogiannis, Michalis P ORCID: 0000-0002-7283-7550 (2019) Forecasting the exchange rate using non-linear Taylor rule based models. International Journal of Forecasting, 32 (2). pp. 429-442.

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Abstract

This research utilises a non-linear Smooth Transition Regression (STR) approach to modelling and forecasting the exchange rate, based on the Taylor rule model of exchange rate determination. The separate literatures on exchange rate models and the Taylor rule have already shown that the non-linear specification can outperform the equivalent linear one. In addition the Taylor rule based exchange rate model used here has been augmented with a wealth effect to reflect the increasing importance of the asset markets in monetary policy. Using STR models, the results offer evidence of non-linearity in the variables used and that the interest rate differential is the most appropriate transition variable. We conduct the conventional out-of-sample forecasting performance test, which indicates that the non-linear models outperform their linear equivalents as well as the non-linear UIP model and random walk.

Item Type:	Article
Uncontrolled Keywords:	Smooth Transition Regression, exchange rate forecasting, Taylor rule model
Depositing User:	Symplectic Admin
Date Deposited:	12 Sep 2018 06:56
Last Modified:	19 Jan 2023 01:17
DOI:	10.1016/j.ijforecast.2018.07.017
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3026143