Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Standard portfolio analysis presumes one can blend different securities continuously. When one must choose all of one portfolio or all of another, we are in stochastic digital programming: either-or, zero-or-one choice. The algorithm for doing this optimally is shown to be simpler than in real variable maximizing, a switch from the usual extra complexities of digital programming. The Bellman multi-period dynamic programming is shown, paradoxically, to make it possible for a risk-averse investor to want sometimes to embrace an unfair gamble. The superiority of within-time diversification over across-time diversification carries over to this flip-flop case. Copyright 1997 by Kluwer Academic Publishers