Stochastic Optimization of Capital Structure in Privately
Funded Infrastructure Projects

Abstract

Capital structure optimization is a key aspect to ensure the success of infrastructure financing. Interest in capital structure optimization in infrastructure projects has been growing rapidly because of the prevalence of public-private partnerships in the U.S. and private finance initiative in the United Kingdom. Even though it is recognized that there are three types of financial sources (i.e., equity, mezzanine, and debt capital) in funding an infrastructure project, the traditional capital structure optimization method either did not consider the existence of mezzanine finance or treat it to be debt or equity instruments. This assumption is not valid in the new era when more and more inflows of capital into infrastructure development projects are from all kinds of institutional investors and multilateral development finance institutions through private equity-style funds. These new equity investors are willing to take advantage of mezzanine financial instruments and common shares as a vehicle to invest in infrastructure assets, which makes a huge difference with traditional equity providers. The frequent implementation of convertible security as one kind of mezzanine financial instrument makes the prediction of the evolution of capital structure impossible due to the dynamic stopping time of the contingent claim embedded in convertible security. Thus, the traditional method for capital structure optimization in the new era is not tenable any more. The principal objective of this article is to present a new model from the perspective of project promoters, which considers convertible security in infrastructure financing and identifies optimal mix of equity, debt, mezzanine capital by incorporating stochastic dynamic programming into the traditional approach.

TOPICS: Private equity, project finance, other real assets, statistical methods