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It has been recently shown that numerical semiparametric bounds on theexpected payoff of fi- nancial or actuarial instruments can be computed usingsemidefinite programming. However, this approach has practical limitations.Here we use column generation, a classical optimization technique, to addressthese limitations. From column generation, it follows that practical univari-ate semiparametric bounds can be found by solving a series of linear programs.In addition to moment information, the column generation approach allows theinclusion of extra information about the random variable; for instance,unimodality and continuity, as well as the construction of correspondingworst/best-case distributions in a simple way.

Computing semiparametric bounds on the expected payments of insurance instruments via column generation