  In this work we address the question of the Multifractal detrended
cross-correlation analysis method that has been subject to some controversies
since its inception almost two decades ago. To this end we propose several new
options to deal with negative cross-covariance among two time series, that may
serve to construct a more robust view of the multifractal spectrum among the
series. We compare these novel options with the proposals already existing in
the literature, and we provide fast code in C, R and Python for both new and
the already existing proposals. We test different algorithms on synthetic
series with an exact analytical solution, as well as on daily price series of
ethanol and sugar in Brazil from 2010 to 2023.
