Horizon Valuations for Mathematical Programming in Financial Planning

Abstract

Using a linear programming model for the financial planning of an organization requires the specification of a horizon date and a valuation of the firm at that date. Given perfect information about future opportunities, an exact valuation procedure should lead to the same optimal solution of the model regardless of the choice of horizon date. Even in the absence of perfect information, conventional valuations fall far shorter of this ideal than they need to. It is shown that for a modest increase in the size of the linear programme, better valuations can be achieved and, most importantly, valuations which consider the impact on the value of the firm of post horizon constraints and liabilities as well as post-horizon opportunities.