This paper explores the nonlinearities of the bivariate distribution of Bordeaux en primeur, or wine futures, prices and Parker “barrel ratings” for the period of 2004 through 2010. In partic- ular, copula-function methodology is introduced and employed to examine the nature of the bivariate distribution. Our results show a significant nonlinear relationship between Parker ratings and wine prices, characterized by significant positive tail dependence and higher correlation between high ratings and high prices. Marginal distributions for Parker ratings and wine prices are then identified and Monte Carlo simulation is employed to operationalize the relationship for risk-management purposes.