  This paper proposes a novel test for simultaneous jumps in a bivariate It\^o
semimartingale when observation times are asynchronous and irregular. Inference
is built on a realized correlation coefficient for the jumps of the two
processes which is estimated using bivariate power variations of
Hayashi-Yoshida type without an additional synchronization step. An associated
central limit theorem is shown whose asymptotic distribution is assessed using
a bootstrap procedure. Simulations show that the test works remarkably well in
comparison with the much simpler case of regular observations.
