In this paper, we present a new budget allocation framework for the problem of selecting the best simulated design from a finite set of alternatives. The new framework is developed on the basis of general underlying distributions and a finite simulation budget. It adopts the expected opportunity cost (EOC) quality measure, which, compared to the traditional probability of correct selection (PCS) measure, penalizes a particularly bad choice more than a slightly incorrect selection, and is thus preferred by risk-neutral practitioners and decision makers. To this end, we establish a closed-form approximation of EOC to formulate the budget allocation problem and derive the corresponding optimality conditions. A sequential budget allocation algorithm is then developed for implementation. The efficiency of the proposed method is illustrated via numerical experiments. We also link the EOC and PCS-based budget allocation problems by showing that the two are asymptotically equivalent. This result explains, to some extent, the similarity in performance between the EOC and PCS allocation procedures observed in the literature.