The EDHEC-Risk Institute has issued a new paper on an old problem, how one can go about valuing infrastructure debt.
The opportunities offered by infrastructure debt, especially the credit risk diversification it allows, are tempting. Still, these opportunities require entering a scary space. In an earlier paper, Blanc-Brude, the lead author here, argued that the world’s investors need reliable benchmarks for performance, and that the development of such benchmarks should be “high on the international policy agenda.” It is in the interest of the whole world, after all, that this space become less scary.
This new paper, Unlisted Infrastructure Debt Valuation & Performance Measurement, is another in EDHEC’s continued research project. This paper focuses specifically on project finance (PF) loans, a “unique form of corporate governance that creates significant and extensive control rights for lenders through embedded options and debt covenants.”
PF loans are not collateralized. But they do have a tail, that is, there is a period after the loan has reached maturity while the life of the infrastructure project continues, and that tail creates a free cash flow that serves functionally as collateral. This is critical for valuation because, as Blanc-Brude et al. write, there are certain “states of the world” in which “lenders have control rights that allow them to restructure a loan and use its tail to maximize their recovery rate.”
Enough of preliminaries: what about the promised valuation process?
A Two-Step Modeling Process
In essence, the EDHEC authors propose a two-step modeling process. Step one is generic; it models the cash flows for the types of financing structures commonly found in infrastructure PFs. This modeling involves the debt service coverage ratio for the genuses. The DSCR on a project by project basis is typically monitored and recorded by infrastructure lenders. This observable data can then be employed to infer the cash flow available for debt service, and that cash flow’s volatility as well.
Step two takes the generic cash flow model as a given and builds a valuation model for a particular project presuming that the value of an asset “must lie within a range determined by the characteristics and preferences of individual investors.” The authors don’t propose to discount actual expected cash flows at a premium to a risk free rate. Rather, they incorporate both risk adjusted and risk-neutral probabilities in order to reflect the heterogeneity of potential investors.
The risk-neutral portion of this work depends upon the Black-Cox decomposition. That is to say, a security’s cash flow is understood as having four components: payout at maturity; payout in the event of reorganization at a lower boundary; payout in the event of reorganization at an upper boundary; payout before reaching any of these boundaries.
The authors tout their two-step approach as operationally implementable on the basis of the following characteristics:
- It uses observable inputs, such as the DSCR;
- It integrates the extent of market incompleteness while using market data when available;
- It takes into account the endogenous nature of loan cash flows and credit risk;
- It distinguishes between technical defaults and hard defaults, which is critical to valuing the lenders;’ step-in rights [more on this point below];
- It takes into account common PF debt covenants such as reserve accounts, cash sweeps, and clawback provisions; and
- It can take into account the unique circumstances of investors when valuing the loans.
A word more about “technical” defaults: Clearly the law of the excluded middle doesn’t apply to the question, “is such-and-such a project in default or is it not?”
In the case of PF loans, covenant breach or other default events can trigger step-in rights. The authors acknowledge that lenders will choose to “reschedule the outstanding debt if they can impose a new debt schedule such that the market value of the new debt, net of restructuring costs, is higher than the market value of the existing debt.” Their own approach includes a six-step explanation of how a new debt schedule may be developed in a situation of technical default.
All in all, I can recommend the full report for all those who are looking for alpha in the infrastructure space.
The paper is the work of Frédéric Blanc-Brude, the head of the institute’s thematic research program on infrastructure investing, with Majid Hasan (research assistant and PhD candidate) and Omneia R.H. Ismail, a former member of the model vetting group at the Ontario Teachers’ Pension Plan.