Glimpses into the offices of modern financial institutions reveal dizzyingly-intricate algorithmic and computationally-driven investment strategies. Machine learning techniques and the methods of applied physics confound the layman and foster a reputation of unapproachable complexity around the realm of quantitative finance. The intricate probabilistic methods of academic economics and their required mathematical erudition seem to bar entrance to those more intent on cultivating the techniques of causal realism. Yet such models ultimately rest upon a fundamental assumption concerning the