On the Uncertainties of Stellar Mass Estimates via Colour Measurements
  Mass-to-light versus colour relations (MLCRs), derived from stellar
population synthesis models, are widely used to estimate galaxy stellar masses
(M$_*$) yet a detailed investigation of their inherent biases and limitations
is still lacking. We quantify several potential sources of uncertainty, using
optical and near-infrared (NIR) photometry for a representative sample of
nearby galaxies from the Virgo cluster. Our method for combining multi-band
photometry with MLCRs yields robust stellar masses, while errors in M$_*$
decrease as more bands are simultaneously considered. The prior assumptions in
one's stellar population modelling dominate the error budget, creating a
colour-dependent bias of up to 0.6 dex if NIR fluxes are used (0.3 dex
otherwise). This matches the systematic errors associated with the method of
spectral energy distribution (SED) fitting, indicating that MLCRs do not suffer
from much additional bias. Moreover, MLCRs and SED fitting yield similar
degrees of random error ($\sim$0.1-0.14 dex) when applied to mock galaxies and,
on average, equivalent masses for real galaxies with M$_* \sim$ 10$^{8-11}$
M$_{\odot}$. The use of integrated photometry introduces additional uncertainty
in M$_*$ measurements, at the level of 0.05-0.07 dex. We argue that using
MLCRs, instead of time-consuming SED fits, is justified in cases with complex
model parameter spaces (involving, for instance, multi-parameter star formation
histories) and/or for large datasets. Spatially-resolved methods for measuring
M$_*$ should be applied for small sample sizes and/or when accuracies less than
0.1 dex are required. An Appendix provides our MLCR transformations for ten
colour permutations of the $grizH$ filter set.
