  In this study, we introduce the first-of-its-kind class of tests for
detecting change points in the distribution of a sequence of independent
matrix-valued random variables. The tests are constructed using the weighted
square integral difference of the empirical orthogonal Hankel transforms. The
test statistics have a convenient closed-form expression, making them easy to
implement in practice. We present their limiting properties and demonstrate
their quality through an extensive simulation study. We utilize these tests for
change point detection in cryptocurrency markets to showcase their practical
use. The detection of change points in this context can have various
applications in constructing and analyzing novel trading systems.
