The depreciation of the pound post-Brexit: Could it have been predicted?

Abstract

The decision of the United Kingdom to leave the European Union (Brexit) after 43 years caused turmoil in exchange rate and global stock markets. More specifically, the pound relative to the dollar has lost close to 15 percent of its value in the weeks after the Brexit decision. In this paper we attempt to examine whether this sudden depreciation of the (pound-dollar) exchange rate is the reaction of market participants to the Brexit or whether the exodus of UK from the EU had little impact on the exchange rate. In doing so, we train linear and nonlinear econometric and machine learning models and evaluate out-of-sample forecasts of the exchange rate and its realized volatility in the pre-and post-Brexit period. We quantify uncertainty caused by the Brexit according to an index based on news related to economic uncertainty.We argue that in daily forecasting horizon our models adhere closely to the evolution of the exchange rate and that most of the depreciation is based on the uncertainty caused by the Brexit.

The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions

“…Exchange rate returns are defined as the first-differences of the natural logarithmic values of the exchange rates. Following Plakandaras et al (2017), realized volatility is computed from the sum of daily squared returns over a month or quarter. As shown in the summary statistics of Table A1, the exchange rate returns and volatilities are nonnormal and hence provide an initial motivation to use quantile regressions.…”

“…In this regard, the literature on predictability of exchange rate returns and volatility is voluminous, to say the least. Detailed literature reviews are provided by Rapach and Wohar (2002, 2004, 2006, Bacchetta and Van Wincoop (2013), Rossi (2013), Plakandaras, Papadimitriou, and Gogas (2013), , Plakandaras, Papadimitriou, Gogas, and Konstantinos (2015), Plakandaras, Gupta, and Wohar (2017), Pilbeam and Langeland (2015), Huber (2016Huber ( , 2017, Papadimitriou, Gogas, and Plakandaras (2016), Ribeiro (2016, 2018). One common observation that emerges out of this literature is that, despite the great need, the task of forecasting exchange rate movements based on fundamentals is an arduous task.…”

The Impacts of Brexit on European Equity Markets

“…Sita (2017) investigated sensitivity of the stock volatility to the market and exchange rate volatility one day after the Brexit vote with Ushape pattern result. Plakandaras et al (2017) argued that depreciation of the FX rate GBP to USD is related to the uncertainty caused by Brexit while uncertainty is quantified according to an index based on news related to economic uncertainty EPU. They used linear, nonlinear and machine learning models to predict the exchange rate and its realized volatility in pre-and post-Brexit period.…”

Uncertainty and adaptation in the context of Brexit

“…The referendum held in the United Kingdom (UK) in June of 2016, which resulted in voters' decision to leave the European Union (EU), has created various unprecedented scenarios (e.g., Fuller, 2017), including for entrepreneurs and their affiliated industries, particularly increased business and economic uncertainty (Dhingra et al, 2017). Notably, following the 2 referendum's result, the British Pound experienced an unprecedented depreciation (Plakandaras et al, 2017), with potentially important consequences for businesses and consumers (Bounds, 2017).…”