Within the series of singular spectrum analysis (SSA) methods, there exist several versions
of forecasting algorithms for signals corrupted by additive noise. In this paper, a technique is proposed
to estimate the asymptotic accuracy of the recurrent version of such forecasting when the length of a
series tends to infinity. Most elements of this construction can be reduced to already studied and published results, although some of them are hard to implement in specific situations. The article brings
together all these elements and augments and comments on them. Several examples of determining
estimates of accuracy for a recurrent forecast are given for specific signals and noises. The computational experiments carried out confirm the theoretical results.