Apologies if it's not a definite answer, but would like to share my experience on this topic.
I have been researching EMD for the last 2 years now after reading multiple one-step ahead forecasting papers for financial time series.
I have been interested in using each IMF separately to regress them with Relevance Vector Machine and NNs.
I have used NI-EMD, EEMD, Statistical-EMD (R package), CEEMDAN, NLMS-EMD and some others.
I implemented different versions all with different ways to avoid mode mixing and extrapolating the end point issue. IMF are not only repainting (no memory).
Also because of the splines, all artefacts to extrapolate prevent any one-step ahead prediction as we are making assumptions as to which direction last few data are projecting .
I even had one researcher working on EMD coding for me this latest implementation Derivative-optimized-EMD, but it failed badly in one-step ahead forecasting. Below is the link to the paper:
I have had conversation with researchers like Flandrin and I have been told that the EMD is suitable to denoise but quite unstable for doing prediction on IMFs in the future as modes will repaint and end point is always improper.
Hope this help.