Abstract:
We study the importance of economic uncertainty so as to predict realized jumps (hereafter jumps)
in the pound-dollar exchange rate. The empirical analysis covers the time period from February 1900 to May
2018 on amonthly basis, incorporating several market states, including various booms and crashes. First, we
apply a standard linear Granger causality test in order to identify causal effects fromeconomic uncertainty to
jumps.We show that the standard linear Granger causality test fails to capture such casual effects. Providing
the misspecification of the linear model, we next make use of a nonparametric causality-in-quantiles test.
This test allows us to take into account the substantial evidence of nonlinearity along with the structural
breaks between economic uncertainty and jumps. In applying this data-driven robust procedure, we find
strong evidence of uncertainty causing jumps of the dollar-pound exchange rate. These results are robust
over the entire conditional distribution of jumps, exhibiting the strongest impact at the lowest conditional
quantiles considered. In addition, our results are generally found to be robust to alternative measures of
uncertainty, jumps generated at a daily frequency based on shorter samples of intraday data, and across three
other dollar-based exchange rates.
