In this case, Prescio helped a major financial trading firm used an existing general time series model capable of capturing salient features of data, but solving for the conditional distribution of the asset price or total returns associated with arbitrary dates in the future proved to be extremely difficult.

Prescio was approached by this firm to develop a solution to this problem. Although substantial academic literature existed relating to unconditional moments, very little research existed to provide a solution for the moments which are most relevant to traders — the moments which exploit known information today. Using rigorous analysis and advanced statistical theory, our team worked to adapt a pricing methodology to a wide variety of issues facing this firm, including the pricing of complex structured physical supply contracts.

Prescio ultimately provided a solution to the problem, and detailed a combination of numerical and analytical procedures to solve for the conditional distribution of asset prices or returns, for any arbitrary date in the future, based on the original model.