Hedge fund operations can be complicated, with numerous investments at any given time spread across myriad industry sectors and geographic locales. While some of these investments will be in liquid securities with easily ascertained market values, alternative assets increasingly are in the mix. Assets such as rarely traded securities or whole businesses are hard to value, but hedge funds and other money managers must do just that, on at least a quarterly basis. It's a challenging task.
Given that most hedge fund managers are sophisticated financial experts able to create complex mathematical models, they sometimes develop extraordinarily complex ways to value such illiquid assets. But does a complex valuation model provide a more accurate valuation? Inevitably, based on our experience, the answer is no.
Hedge funds and other institutional managers need to realize complexity often obscures clarity. Indeed, the ideal valuation model should capture the complexities of an investment without being more complicated than necessary. It should also be one you can use and maintain with a reasonable amount of effort. Ultimately, such clarity will better serve hedge fund managers and their investors alike. Together, on a quarterly basis, all parties gain a clearer understanding of a particular fund's returns.
Why is there such a reliance on overly complex financial models in the valuation of illiquid assets? We believe one reason managers operate in this way is because it can be tough to admit that all investments entail risk. They don't want to focus on uncertainties, such as the fact that an asset could default a few years down the line. Asset buyers often will take a prospectus or other legal document related to the investment, and try to input into the model every line, every wrinkle and every contingency. In reality, an asset's true value is determined by very few contingencies. It's important to stay focused on the elements that most influence the asset's value and risk.
An investment will have several types of risk: Treasury risk, country risk, industry risk. In valuing the asset, complex models could use multiple contingencies for each type of risk. We've seen models with up to eight components used to account for the interest-rate risk. For example, frequently an asset's value is not going to change much just because the Treasury rate increases by 50 basis points. That small of a change is just not crucial to the asset's economics. (Going from 100 basis points to 500 basis points is another story, of course.)
To use another example, let's assume you are valuing an enterprise. You might simply look at last year's earnings and decide what multiple to use based on these numbers, or perhaps look at the values of similar companies that are publicly traded. Complicated approaches are often taken, however, such as trying to project the next five or seven years of income before going back to determine present value. It's very difficult to forecast revenues so far into the future — there are just too many assumptions. Moreover, people don't bother to adjust these projections as time goes on, leading to further problems. A more accurate model can help to avoid such complexity altogether.
Or consider the example of an investment vehicle that buys a company's subsidiary, using a fairly simple model to determine value. What if it later buys the parent company? It will probably try to take that existing model and adapt it for the larger entity. The result can be an extremely complicated spreadsheet — at times, far more complicated than the investment itself. The focus becomes maintaining the spreadsheet, rather than accurately valuing the company.
Complex models can also become brittle, in the sense that they will include outdated information — perhaps even broken links to sources such as databases and websites that have moved or no longer exist. Given normal personnel turnover, in other cases no one even remembers why a source is there in the first place. Once that ever-more-complicated model is established, institutionally it's hard to put it aside and build a new, cleaner one. But over the long term, the benefits of updated and improving valuation models with a keen eye on simplicity can pay enormous returns.
Ultimately, everyone involved in the process of valuing illiquid assets must realize that complexity often breeds confusion, and that — in an overwhelming number of cases — clarity can better be found in sophisticated-but-simple valuation models that separate signal from noise.
Murray C. Grenville is CEO of Sterling Valuation Group Inc., New York. Richard J. Buttimer Jr. is professor of real estate and finance at the Belk College of Business at the University of North Carolina at Charlotte, and a member of Sterling's board of advisers. This article represents the views of the authors. It was submitted and edited under Pensions & Investments guidelines, but is not a product of P&I's editorial team.