EDHEC: Investors Who Don’t Want to be Mushrooms Need Benchmarks

04-01-10 © DrPASMany investors understandably don’t want to make an investment at all if they’re going to end up in the position of a mushroom: kept in the dark and fed feces. Accordingly, in a new position paper, EDHEC-Risk maintains that the world’s investors need reliable data on the performance they can expect from their infrastructure investment, and that the development of the benchmarks that are necessary to do that is a challenging task, one that must be “high on the international policy agenda.”

The report, written by Frédéric Blanc-Brude, the head of the Institute’s 2012-vintage thematic research program on infrastructure financing and investment, draws on the research of that program and details what Blanc-Brude calls a “road map” to creating the benchmarks that in turn will support “the infrastructure investment narrative.”

They need this because the long-term illiquid nature of such investment increases information asymmetry between investors and their managers. The latter are those who will come under suspicion of maintaining the dark environment for the mushrooms.

Two Big Problems

There are two big challenges that this roadmap must direct interested parties around. First: there isn’t enough data available, especially about cash flow. “Little or no effort has been made to construct a data-base of these cash flows,” but even if that were to change overnight empirical observations would remain “truncated in time and limited in the cross-section.”

A related part of the database-creation challenge is that private equity funds report their results opportunistically. A study last year of the quarterly valuation history of 761 such funds in which CalPERS has invested found that managers tend to report conservative return-smoothing valuations, except when they’re audited or when they are creating a follow-on fund. In the latter case, “reported valuations soar for a few quarters before returning to their pre-fund raising levels.”

The second challenge: it isn’t at all clear how assets ought to be valued. In many situations in ongoing infrastructure projects, “the only observable price information is the initial equity investment and debt….” There may also be some realized cash flows and cash flow ratios, but even where they exist they leave an enormous task for anyone working on a benchmark, “to estimate the performance of an asset that is lumpy, held to maturity, for which most cash flows remain to be observed, with limited granularity in the cross-section, with (almost) no market prices.”

Those are the reasons benchmarking is tricky. How is it to be addressed nonetheless? In eight steps, according to Blanc-Brude:

1)      Definition of terms;

2)      Design of valuation and risk measurement methods;

3)      Determination of data collection requirements;

4)      Standardization of performance reporting;

5)      Creation of a data base of equity and debt cash flows;

6)      Identification of building blocks;

7)      Definition of relevant investment strategies;

8)      Creation of benchmarks.

The first five steps operate at the “financial asset” level, the final three at the “portfolio level.”

Looking to Basel

As to the first step, defining terms, Blanc-Brude believes that “long-term investment in infrastructure” is itself a vague conception. For example: is the energy sector part of the “infrastructure” or not? To tighten it up, he suggests that for the purpose of benchmarking, infrastructure be defined mot by the physical nature of certain assets (highways, water pipes, coal plants) which would inevitably be arbitrary. Rather, infrastructure investment should be identified with non-recourse project finance. If a coal plant is sponsored through such a structure, it is infrastructure in this sense. If not, not.

Further, this understanding is supported by the Basel-II Capital Accord, which defines project finance as “a method of funding in which investors look primarily to the revenues generated by a single project, both as the source of repayment and as security for the exposure.”

When we take this definition to step two, the development of valuation models, we may realize that we cannot simply transplant to the infrastructure context the use of established valuation methods for other illiquid investments such as PE or real estate. For example, self-reported NAVs have a lower level of reliability in the former situation than in the latter.

On a more positive note, Blanc-Brude suggests that the likelihood of being in default in a given period may be defined as a function of the default state in the period that preceded it, so that a “cash flow model can … be built as a dynamic Bayesian Markov Chain.”

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