Whichever part of the infrastructure market you operate in, something you probably can’t do without is quantitative skills. As in every field of investments, numbers are used to size a deal, assess expected returns and estimate assets under management. It’s thus pretty hard to make any sorts of decisions without them.
And yet there’s one thing asset managers don’t seem to be doing enough: comparing these numbers against each other in a meaningful away. Benchmarking infrastructure investments has become a vital condition to the development of the asset class, according to the EDHEC-Risk Institute. In a position paper published last month, the research body argues that the increasing popularity of infrastructure has the potential to help match the supply and demand of long-term capital, improve asset allocation outcomes for investors, forge better prudential regulation and support economic development.
Yet for allocations to grow in a sustainable fashion, investors need robust information on the performance they can expect from such investments over time and in various economic environments. Regulators, meanwhile, need to evaluate the risks investors are taking to adequately balance their prudential frameworks.
The institute adds that the nature of long-term investment in infrastructure meant that extensive data collection, while crucially needed, will not be sufficient and will have to be combined with sophisticated asset pricing and risk measurement tools. The institute thus suggests an eight-step roadmap to reach this desired outcome.
At the level of individual instruments, it argues for focusing on defining underlying financial assets, using adequate pricing models for thinly traded instruments, defining data collection needs and standardising performance reporting to create a global database of infrastructure cash flows. It also sees progress possible at the portfolio level.
“While a basket of long-term and illiquid infrastructure project debt or equity is not easily or instantly investable, it is possible to design and estimate the performance characteristics of constructs that have typical exposures to well-documented infrastructure risks such as greenfield or brownfield risks, merchant or contracted revenue risks,” the institute says.
These would help guide different investment strategies and create useful benchmarks for asset allocation, investment manager evaluation and more precise measures of the risk-weights required by prudential regulation.
Importantly, EDHEC underlines that a long-term infrastructure investment benchmark is not a representative basket of existing assets at a given point in time – as arguably is the case for indexes in the listed world – since illiquid assets would not be investable that time. Rather, it should be seen as “an efficient combination of homogeneous building blocks that are designed to capture the average characteristics of homogeneous groups of infrastructure equity and debts”.
That is a rather long definition – and one that leaves open the question of what part of the asset class is homogeneous and representative enough to count as a typical infrastructure investment scenario. But on this point too, EDHEC can provide clarification: project finance instruments are best placed to act as reference instruments to build such benchmarks, because “they embody the expected characteristics of the infrastructure investment narrative”.
The institute recognises the challenge associated with the task. “The development [of benchmarks] is particularly challenging in the context of infrastructure investments marked by the heterogeneous and lumpy nature of the underlying assets and the private, illiquid and thinly-traded nature of the markets in which financial claims to the revenues produced by these assets are originated and exchanged.”
But it reckons that the support and involvement of policy makers, regulators, banks and infrastructure investors, along with further research advances, will help garner the common knowledge needed to cement such measures and instruments. As will, probably, a good number of hours spent in the industry’s data rooms.