We document how the distribution of exchange rate returns responds to changes in global financial conditions. We measure global financial conditions as the common component of country-specific financial condition indices, computed consistently across a large panel of developed and emerging economies. Based on quantile regression results, we provide a characterisation and ranking of the tail behaviour of a large sample of currencies in response to a tightening of global financial conditions, corroborating (and quantifying) some of the prevailing narratives about safe haven and risky currencies. Our approach delivers a more nuanced picture than one based on standard OLS regression. We then carry out a portfolio sorting exercise to identify the macroeconomic fundamentals associated with such different tail behaviour, and find that currency portfolios sorted on the basis of net foreign asset positions, relative interest rates, current account balances and levels of international reserves display a higher likelihood of large losses in response to a tightening of global financial conditions.
exchange rates tail risks financial conditions indices global financial cycle quantile regression