Forecasting the Exchange Rate using Non-linear Taylor Rule Based Models

Rudan Wang, Bruce Morley, Michalis Stamatogiannis

Research output: Contribution to journalArticle

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.
Original languageEnglish
Pages (from-to)429-442
Number of pages14
JournalInternational Journal of Forecasting
Volume35
Issue number2
Early online date28 Dec 2018
DOIs
Publication statusPublished - 1 Apr 2019

Fingerprint

Exchange rates
Taylor rule
Rule-based
Smooth transition regression
Nonlinearity
Random walk
Regression model
Monetary policy
Asset markets
Wealth effect
Forecasting performance
Out-of-sample forecasting
Exchange rate determination
Modeling
Interest rate differentials

Keywords

  • Exchange rates, forecasting, Taylor rule, wealth effect, Smooth Transition

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)

Cite this

Forecasting the Exchange Rate using Non-linear Taylor Rule Based Models. / Wang, Rudan; Morley, Bruce; Stamatogiannis, Michalis.

In: International Journal of Forecasting, Vol. 35, No. 2, 01.04.2019, p. 429-442.

Research output: Contribution to journalArticle

Wang, Rudan ; Morley, Bruce ; Stamatogiannis, Michalis. / Forecasting the Exchange Rate using Non-linear Taylor Rule Based Models. In: International Journal of Forecasting. 2019 ; Vol. 35, No. 2. pp. 429-442.
@article{04298b4531e54789a665f537e7b0e60a,
title = "Forecasting the Exchange Rate using Non-linear Taylor Rule Based Models",
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 literatureson 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 beenaugmented 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 ratedifferential 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 asthe non-linear UIP model and random walk.",
keywords = "Exchange rates, forecasting, Taylor rule, wealth effect, Smooth Transition",
author = "Rudan Wang and Bruce Morley and Michalis Stamatogiannis",
year = "2019",
month = "4",
day = "1",
doi = "10.1016/j.ijforecast.2018.07.017",
language = "English",
volume = "35",
pages = "429--442",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier",
number = "2",

}

TY - JOUR

T1 - Forecasting the Exchange Rate using Non-linear Taylor Rule Based Models

AU - Wang, Rudan

AU - Morley, Bruce

AU - Stamatogiannis, Michalis

PY - 2019/4/1

Y1 - 2019/4/1

N2 - 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 literatureson 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 beenaugmented 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 ratedifferential 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 asthe non-linear UIP model and random walk.

AB - 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 literatureson 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 beenaugmented 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 ratedifferential 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 asthe non-linear UIP model and random walk.

KW - Exchange rates, forecasting, Taylor rule, wealth effect, Smooth Transition

UR - http://www.scopus.com/inward/record.url?scp=85059141487&partnerID=8YFLogxK

U2 - 10.1016/j.ijforecast.2018.07.017

DO - 10.1016/j.ijforecast.2018.07.017

M3 - Article

VL - 35

SP - 429

EP - 442

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 2

ER -