  It has been recently shown that numerical semiparametric bounds on the
expected payoff of fi- nancial or actuarial instruments can be computed using
semidefinite programming. However, this approach has practical limitations.
Here we use column generation, a classical optimization technique, to address
these 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 the
inclusion of extra information about the random variable; for instance,
unimodality and continuity, as well as the construction of corresponding
worst/best-case distributions in a simple way.
