Exchange Rate Models

2017 ◽  
Author(s):  
Francis E. Warnock
2011 ◽  
Author(s):  
H. Takizawa ◽  
Jaewoo Lee ◽  
David Hauner

Author(s):  
Yin-Wong Cheung ◽  
Menzie David Chinn ◽  
Antonio I. Garcia Pascual

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hon Chung Hui

PurposeThe purpose of this paper is to analyse the long-run relationship between geopolitical risk and exchange rates in four ASEAN countries.Design/methodology/approachWe augment theoretical nominal exchange rate models available in the literature with the geopolitical risk index developed by Caldara and Iacoviello (2019), and then estimate these models using the ARDL approach to Cointegration.FindingsOur analysis uncovers evidence of Cointegration in the exchange rate models when the MYR-USD, IDR-USD, THB-USD and PHP-USD exchange rates are used as dependent variable. Next, geopolitical risk is a significant long-run driver for these exchange rates. Third, in all countries higher geopolitical risk leads to a depreciation of domestic currency.Research limitations/implicationsThere are implications for entrepreneurs, central banks, portfolio managers and arbitrageurs who actively trade in financial markets. Financial market players can benefit from a better understanding of how geopolitical events affect the portfolio of financial assets across various countries, while entrepreneurs can work out hedging strategies.Originality/valueThis is a contribution to the study of interlinkages between political risk and foreign exchange markets. It is the first study to adopt the geopolitical risk index of Caldara and Iacoviello (2019) to the study the foreign exchange markets of ASEAN countries.


2019 ◽  
Vol 24 (02) ◽  
Author(s):  
L. Espinoza-Audelo ◽  
E. Aviles-Ochoa ◽  
E. Leon-Castro ◽  
F. Blanco-Mesa

2008 ◽  
Vol 22 (9) ◽  
pp. 3491-3530 ◽  
Author(s):  
Pasquale Della Corte ◽  
Lucio Sarno ◽  
Ilias Tsiakas

2017 ◽  
Vol 9 (9) ◽  
pp. 94
Author(s):  
Augustine C. Arize ◽  
Ioannis N. Kallianiotis ◽  
Ebere Eme Kalu ◽  
John Malindretos ◽  
Moschos Scoullis

This paper studies a diversity of exchange rate models, applies both parametric and nonparametric techniques to them, and examines said models’ collective predictive performance. We shall choose the forecasting predictor with the smallest root mean square forecast error (RMSE); the empirical evidence for a better type of exchange rate model is in equation (34), although none of our evidence gives an optimal forecast. At the end, these models’ error correction versions will be fit so that plausible long-run elasticities can be imposed on each model’s fundamental variables.


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