Changing commodity prices create opportunities for traders to profit or experience substantial losses if risk is not managed. Extensive research has been presented regarding optimal hedging strategies using futures markets to mitigate price risk of holding a physical commodity, but the literature has not introduced a method for optimizing basis or rail coverage ratios. This study introduces coverage ratios to manage basis and transportation risk. Coverage ratios are optimized for a portfolio of basis and rail positions consistent with expected utility theory using Monte Carlo simulation at various risk aversion levels. The results indicated that as risk aversion increased, optimal coverage levels increased while profit and standard deviations of profits decreased. Sensitivity analysis is used to demonstrate the effects of changing intermarket correlations, standard deviations of individual markets, and time to liquidation. This study provides insight into managing basis and rail portfolios and presents implications for traders and risk managers.