Abstract
We investigate the use of chance constraints in modeling the debt financing decision under conditions of debt heterogeneity and uncertainty. We develop a stochastic financial model that uses simulation optimization to select an optimal mix of fixed-rate debt instruments from different sources, with the objective of maximizing net present value (NPV) while limiting default risk. We then use simulation to evaluate the performance of the resulting debt policy. Numerical results from our model indicate that in a world of uncertainty, project promoters who wish to create bankable proposals for project financing, by limiting the probability of default, should spread debt across different maturities.
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