  We quantify how co-jumps impact correlations in currency markets. To
disentangle the continuous part of quadratic covariation from co-jumps, and
study the influence of co-jumps on correlations, we propose a new wavelet-based
estimator. The proposed estimation framework is able to localize the co-jumps
very precisely through wavelet coefficients and identify statistically
significant co-jumps. Empirical findings reveal the different behaviors of
co-jumps during Asian, European and U.S. trading sessions. Importantly, we
document that co-jumps significantly influence correlation in currency markets.
