In this paper,the option pricing problem is formulated as a distributionally robust optimization problem,which seeks to minimize the worst case replication error for a given distri-butional uncertainty set(DUS)of the random underlying asset returns.The DUS is defined as a Wasserstein ball centred the empirical distribution of the underlying asset returns.It is proved that the proposed model can be reformulated as a computational tractable linear programming problem.Finally,the results of the empirical tests are presented to show the significance of the proposed approach.