Three essays on the predictive content and predictability of the nominal exchange rates in a changing world

Promponas, Pantelis and Peel, David and Tsionas, Mike (2017) Three essays on the predictive content and predictability of the nominal exchange rates in a changing world. PhD thesis, Lancaster University.

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Abstract

This thesis examines the predictive power and the predictability of the nominal USD/GBP exchange rate changes in a world with structural instabilities. In Chapter 2 we mainly focus on the predictive content of the exchange rates in an attempt to forecast the Taylor rule fundamentals, such as the output gap, the inflation rate and the real exchange rate of the U.S. and the U.K. We employ time-varying econometric techniques, taking into account possible non-linearities and time-variations of the Taylor rule relationships, while we also use Bayesian methods and real-time (vintage) data for the variables that suffer from consecutive revisions. Chapter 3 reviews the well-known ‘Meese and Rogoff’ puzzle which describes the inability of the macroeconomic fundamentals to forecast the exchange rate returns. Starting with a critical survey of the exchange rate forecasting literature, we move on to testing a wide range of traditional and empirical macro fundamentals-based models using various linear and non-linear models, as well as a DSGE model. We examine whether making provisions for the instability and predictive relevance of the fundamental, the out-of-sample performance of our models is improved or not. Finally, Chapter 4 is motivated by the disaster risk literature, examining the in-sample and out-of-sample predictive impact of the foreign policy crises of the U.S. and the U.K. on the USD/GBP exchange rate returns. Using the foreign policy crisis as an approximation for the time-varying disaster risk of these two economies, we study how exchange rate returns are affected by crises of different severity and violence, once combined with other macroeconomic predictors.

Item Type:
Thesis (PhD)
ID Code:
89184
Deposited By:
Deposited On:
15 Dec 2017 09:50
Refereed?:
No
Published?:
Published
Last Modified:
01 Oct 2024 23:43