Editor’s Letter

Welcome to the Summer 2022 issue of The Journal of Structured Finance. Issuance activity in the first half of the year was somewhat slower than in the first half of 2021. The slowdown is most pronounced in the areas of agency MBS and CLOs. The slowdown seems partly attributable to stresses associated with rising interest rates, the war in Ukraine, and related factors. However, heightened uncertainty about the future is an additional factor that amplifies the effects of other stressors. To be clear, I mean uncertainty as opposed to risk. Risk is when we know the chances of possible future outcomes (i.e., we can describe them with probability distributions). Uncertainty is when we do not even know the chances.

Markets have become reasonably comfortable in dealing with risk. We have an extensive toolkit—including probability theory and computers—for analyzing risk. By contrast, uncertainty is a problem. There are not reliable tools for analyzing it. Seeking to find comfort in inherently uncomfortable situations sometimes causes us to treat uncertainty as risk. Doing so can lead to disappointment.

Moneyball, by Michael Lewis, popularized the success of Sabermetrics, an approach to using quantitative analytics to maximize the performance of major league baseball players and teams. It is a great example of success in dealing with a risk-type situation. By contrast, the NFL draft is an example of a situation where extensive quantitative analysis has produced dismal results (Leonhardt 2022). NFL teams have an extremely poor track record of picking new players who will perform well at the professional level, despite having copious information about the players’ past performance. It calls to mind the old chestnut that “economists have predicted nine out of the last five recessions.”

David Leonhardt of The New York Times cites hubris as the reason why people try to predict the unpredictable. He writes:

Predicting performance is unavoidably hard, even in the country’s most popular form of mass entertainment, where executives can devote lavish resources to research. “There’s no crime in that,” Cade Massey, a University of Pennsylvania economist, said. “The crime is thinking you can predict it.”

What is the broader lesson here? The world is frequently messier and harder to understand than people acknowledge. We tell ourselves artificially tidy stories about why something happened and what will happen next.

The stock market rises or falls, and analysts proclaim a cause; in truth, they are often just guessing, as Paul Krugman, the economist and Times columnist, likes to point out. (Leonhardt 2022)

But Leonhardt was hardly the first to point to hubris. Peter Bernstein, the founding editor of The Journal of Portfolio Management wrote in 1996:

The English journalist G.K. Chesterton had the picture more clearly in mind when he wrote, “The real trouble with this world of ours is not that it is an unreasonable world, nor that it is a reasonable one. The commonest kind of trouble is that it is nearly reasonable, but not quite. Life is not an illogicality; yet it is a trap for logicians. It looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait.”

Even though many economic and financial variables have approximately normal distributions, the picture is never perfect. Resemblance to truth is not the same thing as truth. Those outliers and imperfections are where the wildness lurks.

It is hubris to believe that we can put reliable and stable numbers on the impact of a politician’s power, on the probability of a takeover boom like the one that occurred in the 1980s, on the return on the stock market over the next 2, 20, or 50 years, or on subjective factors like utility and risk aversion. It is equally silly to limit our deliberations only to those variables that do lend themselves to quantification, excluding all serious consideration of the unquantifiable. It is irrational to confuse probability with timing and to assume that an event with low probability is therefore not imminent. Such confusion, however, is by no means unusual. And it surely is naïve to define discontinuity as anomaly instead of as normality; only the shape and the timing of the disturbances are hidden from us, not their inevitability. (Bernstein 1996A)

A closely-related problem is that of entrenched beliefs and theories. When strong evidence contradicts our theories or beliefs, we should reexamine them. Scientists seem to be somewhat better at this than businesspeople. If strong empirical contradicts important scientific theories—like General Relativity or the Standard Model of particle physics—scientists are unlikely to practice denialism or avoidance. They are more likely to test the evidence and seek plausible modifications to their theories. Businesspeople would do well to follow that approach.

When we find that a given theory or approach is not effective, the purpose to which it is put should be reexamined and, possibly, modified or abandoned. In some cases, it may necessary to recognize that the state of the art is not sufficiently advanced to achieve a desired goal. For example, it does not (yet) seem possible to predict recessions and market declines reliably, despite an abundance of data about past events (Exhibit 1).

• Download figure
• Open in new tab
• Download powerpoint

EXHIBIT 1

S&P 500 Major Declines & Recoveries over the Past 50 Years

NOTE: Adapted from Quinn (2020).

Likewise, it may be fair to question whether the estimates of extremely small credit risk associated with triple-A-rated securities possess the high degree of reliability inherently implied by the estimated magnitude of the risk. Here, uncertainty seems to loom large compared to what can be reasonably analyzed as risk. Just food for thought in these uncertain times…

This issue has an eclectic selection of articles. It opens with an article by Jack W. Xu, an independent modeling consultant in Hong Kong. Xu introduces a methodology for incorporating fundamental credit analysis into a dynamic model of a company’s multidimensional balance sheet. He presents an application of the methodology to Chinese real estate companies. His results suggest that the market has a bias in favor of large companies, underpricing their credit risk while overpricing the credit risk of smaller firms.

The second article is by Robert K. Simmons of Marathon Capital. He writes about the role of natural gas in the transition to renewable energy sources. He explains that natural gas will remain an important source of energy for the near future and explores the effects of the conflict in Ukraine on natural gas supplies. The third article is by Prof. David Yu of NYU in Shanghai and Tasos Michael of Inception Aviation. They address the effects of the Ukraine conflict—including sanctions against Russia—on the aviation finance sector.

The fourth article is by Kadiri Karamon and Douglas McManus of Freddie Mac. They examine Freddie Mac’s automated collateral evaluation (ACE) program and find that loans originated using ACE display a 9.6% lower delinquency rate than similar loans originated with traditional appraisals. They note that ACE uses data not found in traditional appraisals. They add that their results may not apply broadly to other automated valuation models (AVMs).

The fifth article is by Nurkhodzha Akbulaev, Nigar Huseynli, and Tabriz Aliyev of the Azerbaijan State University of Economics (UNEC) in Baku, Azerbaijan. They explore the relationship between lending activity and economic growth in Azerbaijan. They find that increased lending by commercial banks boosts economic growth. To the extent that their results can be generalized to other countries, they support the notion that securitization can help promote economic growth by increasing the supply of available credit.

The sixth article is by Alankar Ranade of Acuity Knowledge Partners in Bengaluru, India. He explores how the demise of LIBOR affects the CLO market. He discusses various issues with the replacement indexes in different jurisdictions. The seventh article is by Shane Woodroffe of EnerCap Power Funds. He discusses the divergence of theory and practice in handling the technical insolvency of renewable power projects in Poland and Romania. He explains that the insolvency regimes of certain countries produce non-optimal results for handling situations, where economically viable projects generate cash flow more slowly than originally projected.

The next section is selected highlights from GlobalCapital for the second quarter of 2022. The selection was compiled and curated by GC deputy editor, Tom Lemmon. Five stories are featured, covering the following subjects:

• ▪ The state of the US securitization market in the face of a potential recession

• ▪ Solar ABS and the expiration of related tax credits

• ▪ The impact of the Ukraine conflict on the supply of warehouse lines for US CLOs

• ▪ Carlyle’s acquisition of CBAM, which makes Carlyle the world’s largest CLO manager

• ▪ The continuing strong demand for securitization professionals

Next comes a selection of industry news items from the Structured Finance Association, also from Q2 2022. The selection includes more than a dozen news snippets covering timely and important developments in the structured finance market.

• © 2022 Pageant Media Ltd