Glimpses into the offices of modern financial institutions reveal dizzyingly-intricate algorithmic and computationally-driven investment strategies. AssumptionMainstream academia’s modus operandi in the field of economics is the development of contrived quantitative models constructed from unrealistic premises concerning human behavior. Yet the most fundamental assumption held within quantitative finance is the treatment of economic and financial data as generally homogenous both temporally and between individuals. HeterogeneityBut as quantitative financial models themselves admit, human action—the likes of which generates financial data—is undeniably heterogeneous both between distinct acting individuals and across time. They could understandably highlight the tremendous returns attained by various probabilistic trading strategies as examples of the successful application of probability theory in predicting financial market outcomes.