Shrinkage was much en-vogue before random matrix theory (RMT) took everybody's attention in covariance matrix estimation, however the latter also showed its limits. A plethora of other estimators has been presented, but I could not yet spot a golden standard. What is nowadays used most in practice (or what are you using), and why? Also, shrinkage came in different flavours, so I'd like to know which is the favourite among them.
Note that I'm not just asking for the statistical properties of different methods (this would be on Cross Validated in that case), but also their interplay with practical considerations here in the quant world, which might include even non-technical factors.