The beautiful idea has been around for ages. Find the N closest H-histories to the current H-history (you choose/tune N and H), for each H-history see what followed, take an average, and use that as your forecast. Of course there are many variations and extensions. Interesting new work by Dendramis, Kapetanios, and Marcellino is in exactly that tradition, except that Dendramis et al.  don't show much awareness of the tradition, or attempt to stand on its shoulders, which I find odd. I find myself hungry for tighter connections, for example to my favorite old nearest-neighbor prediction piece, Sid Yakowitz's well-known "Nearest-Neighbor Methods for Time Series Analysis,” Journal of Time Series Analysis, 1987.