Chart of the Month: Not Just the Economy — Asset Demand Drives Prices
Within weeks of the March 11th declaration of COVID-19 as a global pandemic by the World Health Organization, rating agencies were downgrading businesses across virtually every sector of the economy. Not surprisingly, these downgrades were felt most acutely by businesses that one would reasonably expect to be directly harmed by the ensuing shutdowns, including travel and hospitality firms and retail stores. But the downgrades also hit food companies and other areas of the economy that tend to be more recession resistant.
An accompanying spike in credit spreads was even quicker to materialize. Royal Caribbean’s and Marriott’s credit spreads tripled essentially overnight, while those of other large companies increased by twofold or more.
But then something interesting happened. Almost as quickly as they had risen, most of these spreads began retreating to more normal levels. By mid-June, most spreads were at or lower than where they were prior to the pandemic declaration.
What business reason could plausibly explain this? The pandemic is ongoing and aggregate demand for these companies’ products does not appear to have rebounded in any material way. People are not suddenly flocking back to Marriott’s hotels or Wynn’s resorts.
The story is indeed one of increased demand. But rather than demand for the companies’ products, we’re seeing an upswing in demand for these companies’ debt. What could be driving this demand?
Enter the Federal Reserve. On March 23rd, The Fed announced that its Secondary Market Corporate Credit Facility (SMCCF) would begin purchasing investment-grade corporate bonds in the secondary market, first through ETFs and directly in a later phase.
And poof! Instant demand. And instant price stabilization. All the Fed had to do was announce that it would begin buying bonds (it hasn’t actually started buying yet) for demand to rush back in, push prices up and drive credit spreads down.
To illustrate how quickly spreads reacted to the Fed’s announcement, we tracked seven of the top 20 companies listed by S&P across different industries from early March through mid-June. The chart below plots swap spreads for a single bond (with approximately five years to maturity) from each of the following companies:
- Royal Caribbean Cruises (RCL)
- BMW
- The TJX Companies (which includes discount retailers TJ Maxx, Marshalls, and HomeGoods, among others)
- Marriott
- Wynn Resorts
- Kraft Foods
- Ford Motor Company
We sourced the underlying data for these charts from two RiskSpan partners: S&P, which provided the timing of the downgrades, and Refinitiv, which provided time-series spread data.
The companies we selected don’t cover every industry, of course, but they cover a decent breadth. Incredibly, with the lone exception of Royal Caribbean, swap spreads for every one of these companies are either better than or at the same level as where they were pre-pandemic.
As alluded to above, this recovery cannot be attributed to some miraculous improvement in the underlying economic environment. Literally the only thing that changed was the Fed’s announcement that it would start buying bonds. The fact that Royal Caribbean’s spreads have not fully recovered seems to suggest that the perceived weakness in demand for cruises in the foreseeable future remains strong enough to overwhelm any buoying effect of the impending SMCCF investment. For all the remaining companies, the Fed’s announcement appears to be doing the trick.
We view this as clear and compelling evidence that the Federal Reserve in achieving its intended result of stabilizing asset prices, which in turn should help ease corporate credit.
Webinar: Data Analytics and Modeling in the Cloud – June 24th
On Wednesday, June 24th, at 1:00 PM EDT, join Suhrud Dagli, RiskSpan’s co-founder and chief innovator, and Gary Maier, managing principal of Fintova for a free RiskSpan webinar.
Suhrud and Gary will contrast the pros and cons of analytic solutions native to leading cloud platforms, as well as tips for ensuring data security and managing costs.
Click here to register for the webinar.
Changes to Loss Models…and How to Validate Them
So you’re updating all your modeling assumptions. Don’t forget about governance.
Modelers have now been grappling with how COVID-19 should affect assumptions and forecasts for nearly two months. This exercise is raising at least as many questions as it is answering.
No credit model (perhaps no model at all) is immune. Among the latest examples are mortgage servicers having to confront how to bring their forbearance and loss models into alignment with new realities.
These new realities are requiring servicers to model unprecedented macroeconomic conditions in a new and changing regulatory environment. The generous mortgage forbearance provisions ushered in by March’s CARES Act are not tantamount to loan forgiveness. But servicers probably shouldn’t count on reimbursement of their forbearance advances until loan liquidation (irrespective of what form the payoff takes).
The ramifications of these costs and how servicers should modeling them is a central topic to be addressed in a Mortgage Bankers Association webinar on Wednesday, May 13, “Modeling Forbearance Losses in the COVID-19 world” (free for MBA members). RiskSpan CEO Bernadette Kogler will lead a panel consisting of Faith Schwartz, Suhrud Dagli, and Morgan Snyder in a discussion of the forbearance’s regulatory implications, the limitations of existing models, and best practices for modeling forbearance-related advances, losses, and operational costs.
Models, of course, are only as good as their underlying data and assumptions. When it comes to forbearance modeling, those assumptions obviously have a lot to do with unemployment, but also with the forbearance take-up rate layered on top of more conventional assumptions around rates of delinquency, cures, modifications, and bankruptcies.
The unique nature of this crisis requires modelers to expand their horizons in search of applicable data. For example, GSE data showing how delinquencies trend in rising unemployment scenarios might need to be supplemented by data from Greek or other European crises to better simulate extraordinarily high unemployment rates. Expense and liquidation timing assumptions will likely require looking at GSE and private-label data from the 2008 crisis. Having reliable assumptions around these is critically important because liquidity issues associated with servicing advances are often more an issue of timing than of anything else.
Model adjustments of the magnitude necessary to align them with current conditions almost certainly qualify as “material changes” and present a unique set of challenges to model validators. In addition to confronting an expanded workload brought on by having to re-validate models that might have been validated as recently as a few months ago, validators must also effectively challenge the new assumptions themselves. This will likely prove challenging absent historical context.
RiskSpan’s David Andrukonis will address many of these challenges—particularly as they relate to CECL modeling—as he participates in a free webinar, “Model Risk Management and the Impacts of COVID-19,” sponsored by the Risk Management Association. Perhaps fittingly, this webinar will run concurrent with the MBA webinar discussed above.
As is always the case, the smoothness of these model-change validations will depend on the lengths to which modelers are willing to go to thoroughly document their justifications for the new assumptions. This becomes particularly important when introducing assumptions that significantly differ from those that have been used previously. While it will not be difficult to defend the need for changes, justifying the individual changes themselves will prove more challenging. To this end, meticulously documenting every step of feature selection during the modeling process is critical not only in getting to a reliable model but also in ensuring an efficient validation process.
Documenting what they’re doing and why they’re doing it is no modeler’s favorite part of the job—particularly when operating in crisis mode and just trying to stand up a workable solution as quickly as possible. But applying assumptions that have never been used before always attracts increased scrutiny. Modelers will need to get into the habit of memorializing not only the decisions made regarding data and assumptions, but also the other options considered, and why the other considered options were ultimately passed over.
Documenting this decision-making process is far easier at the time it happens, while the details are fresh in a modeler’s mind, than several months down the road when people inevitably start probing.
Invest in the “ounce of prevention” now. You’ll thank yourself when model validation comes knocking.
April Chart of the Month: COVID-19 Impact on Junior Bond Spreads
Our chart of the month presents data illustrating what has already been acutely felt by mezzanine and other subordinate bond investors – a sharp rise in spreads across all sectors coinciding with the imposition of pandemic-related lockdowns in the United States and around the world.
Spreads on aircraft leases had already begun widening by the start of March as travel was slowing dramatically well before widespread government-imposed shutdowns began hitting other parts of the economy. Spreads on aircraft bonds soared to 1,800 basis points at the end of March and 2,400 basis points on April 25th.
Aircraft differed from most other sectors in its spreads continued to widen throughout April. Spreads in most other sectors began reverting closer to normal in April after experiencing the March market shock. Another notable exception to this pattern were timeshare spreads, which also continued widening during April, reaching a level on April 25th four times where they were on March 2nd.
It is not surprising to see bonds associated with the travel sector of the economy react in this way. Other sectors that did not rebound during April included student, equipment, floor plan and commercial loans.
Widening spreads naturally correspond with price declines over the same period.
The spreads in this chart were computed using TRACE data enhanced by RiskSpan’s Market Color application.
Market dislocations like these are compelling an increasing number of portfolio managers to begin marking their portfolios to model rather than to market. Join us on Thursday at 1:00 p.m. for the webinar, “Valuing Hard-to-Value Bonds” for a lively discussion on some of the ramifications of this change.
RiskSpan VQI: Current Underwriting Standards – March 2020
The RiskSpan Vintage Quality Index (“VQI”) indicates that we are entering the current economic downturn with a cohort of mortgages that were far more conservatively originated than the mortgages in the years leading up to the 2008 crisis. The VQI dropped three points for mortgages originated during March to finish the first quarter of 2020 at 87.77. This reflects generally tight underwriting standards leading into the COVID-19 crisis, though not nearly as tight as what was witnessed in the years immediately following the housing finance crisis.
The VQI climbed slightly during the first two months of the year—evidencing a mild loosening in underwriting standards—peaking at just over 90 in February, before dropping to its current level in March. The following chart illustrates the historical trend of risk layering that contributes to the VQI and how that layering has evolved over time. Mortgages with one borrower—now accounting for more than 50 percent of originations—remain a consistent and important driver of the index and continued to climb during Q1. High-DTI loans, which edged higher in Q1, continue to drive the index today but not nearly to the degree they did in the years leading up to the 2008 crisis.
RiskSpan introduced the VQI in 2015 as a way of quantifying the underwriting environment of a particular vintage of mortgage originations. The idea is to provide credit modelers a way of controlling for a particular vintage’s underwriting standards, which tend to shift over time. The VQI is a function of the average number of risk layers associated with a loan originated during a given month. It is computed using:
- The loan-level historical data released by the GSEs in support of Credit Risk Transfer initiatives (CRT data) for months prior to December 2005, and
- Loan-level disclosure data supporting MBS issuances through today.
The value is then normalized to assign January 1, 2003 an index value of 100. The peak of the index, a value of 139 in December 2007, indicates that loans issued in that month had an average risk layer factor 39% greater (i.e., loans issued that month were 39% riskier) than loans originated during 2003. In other words, lower VQI values indicate tighter underwriting standards (and vice-versa).
Build-Up of VQI
The following chart illustrates how each of the following risk layers contributes to the overall VQI:
- Loans with low credit scores (FICO scores below 660)
- Loans with high loan-to-value ratios (over 80 percent)
- Loans with subordinate liens
- Loans with only one borrower
- Cash-out refinance loans
- Loans secured by multi-unit properties
- Loans secured by investment properties
- Loans with high debt-to-income ratios (over 45%)
- Loans underwritten based on reduced documentation
- Adjustable rate loans
Modeling Delinquency Deluge
RiskSpan’s CEO Bernadette Kogler recently spoke with Simon Boughey of Structured Credit Investor (SCI) to discuss COVIDー19’s impact on the mortgage market & securitizations of mortgage assets. Simon’s article has been republished here with their permission.
Wednesday 8 April 2020 17:45 London/ 12.45 New York/ 01.45 (+ 1 day) Tokyo
Mortgage market advisers and consultants are struggling to find any models that work for the current crisis, but they are telling clients that they should prepare for a worst case scenario in mortgage market and securitizations of mortgage assets.
“Our clients are modeling a range of scenarios but are preparing themselves for the worst case including sustained levels of unemployment. Hopefully it won’t be that bad, but they need to prepare themselves,” says Bernadette Kogler, Chief Executive Officer of RiskSpan, a Washington, DC-based analytics and modeling firm which has particular expertise in mortgage markets.
RiskSpan clients include firms prominent in the mortgage securitization industry, such as lenders and servicers like Wells Fargo and Flagstar, as well as Fannie Mae and Freddie Mac. It also has clients on the buy-side, such as Barings, Northern Trust and Fidelity.
Both buy-side and sell-side clients are struggling to assess what the economic devastation of the last two weeks, with more to come, will mean for the MBS markets.
The “worst case” could be very bleak indeed. Economists at the Federal Reserve Bank of St Louis have predicted that the dislocation elicited by COVID-19 could cause 47M job losses in the US. This translates to an unemployment rate of 32% – comfortably worse than the rate of 25% recorded in the Great Depression of 1930-33.
Other economists are not quite so pessimistic, but Kogler agrees and she is advising clients to prepare for an unemployment rate of 30% in the worst affected regions of the USA. Las Vegas, Nevada, for example, is particularly exposed to the collapse of the hospitality industry, while Texas has been hit with a double whammy of a Coronavirus lockdown and a precipitous decline of oil and gas prices.
Metropolitan Las Vegas has a population of over 2.5M while the state of Texas is home to over 12.5M people.
An unemployment rate of 30% could lead to a mortgage delinquency rate of around 30%. Data provided by the Bureau of Labor shows that the correlation between unemployment and mortgage delinquency is very high – virtually 1:1. So, for example, both unemployment and mortgage delinquency peaked at around 10% in the Great Recession.
At the moment, a delinquency rate of 10% looks a lot better than what might be seen in a few months from now. Of course, foreclosure rates will be substantially lower than delinquencies, but if delinquencies do hit 30% foreclosures might be as high as 30%. The effect on the MBS market, both agency and non-agency, of delinquency rates of this magnitude is hard to over-estimate.
Kogler suggests that around 1M Federal Housing Authority (FHA) loans could be affected by unemployment levels like that.
The GSEs, of course, offer largely guaranteed debt to capital markets investors in the TBA market, so their position could become particularly painful.
On January 23, when COVID-19 was still something to be not too bothered about, Federal Housing Finance Authority (FHFA) director Mark Calabria gave a speech to National Association of Homebuilders and reminded his audience that Fannie Mae and Freddie Mac had a leverage ratio of 300 to 1.
“Given their risks and financial position, even in a modest downturn, Fannie and Freddie will fail,” he said.
Part of the problem in modeling for a disaster of this proportion is that there are still many unknowns. Though the Federal Reserve has intervened with a stimulus package, but no-one knows how much it will continue to do, or can do, as the crisis persists.
Certain areas of the mortgage industry are still without any Federal aid. Mortgage originators and servicers hope to receive some backing, but nothing has been divulged as yet.
Models based on natural disasters provide no firm clue about this crisis will unfold. In disasters of that kind, insurance companies intervene at some juncture, distorting the appropriateness of disaster-based models for the COVID-19 world.
“No models are sufficient. Predictive models are based on historical data, and to the extent that we have not seen anything like this before they are not going to work,” says Kogler.
08/04/2020 17:45:18
Copyright © structuredcreditinvestor.com 2007-2019.
This article was published in Structured Credit Investor on 08 April 2020.
Impact of COVID-19 on Mortgage Originator Liquidity
Over the past few years, mortgage origination has shifted away from depository institutions and into the hands of independent mortgage banking entities. This transition has led to concerns over the ability of non-bank lenders to weather adverse market conditions.
Non-bank lenders employ large amounts of leverage. They rely heavily on warehouse lines of credit to finance their operations, while their balance sheet assets are mostly comprised of unclosed loan-locks in the pipeline, hedge instruments, funded whole–loan inventory available for sale, and mortgage servicing rights. Growing concern over the relative illiquidity of MSRs in particular, combined with the exposure of non-bank lenders to Government–backed servicing assets, prompted Ginnie Mae to announce plans to perform stress-testing on their non-bank issuers in 2019. The COVID-19 pandemic, however, appears poised to deliver a real-world scenario far worse than any stress test—one whose market disruption causes a disastrous liquidity crunch for a large sector of the mortgage origination market.
As the pandemic began to unfold and equity markets went into freefall, flight-to-quality trades pushed yields on Treasuries to record lows. Mortgage-backed securities significantly underperformed their treasury benchmarks, causing the Fed to re-ignite its MBS purchase program on March 19th and inject additional liquidity into the RMBS market.
This move by the Fed had an unintended consequence, however. As mortgage rates dropped, TBA passthroughs1 rallied significantly. Because TBAs are a widely used hedge instrument for mortgage originators, this rally triggered widespread margin calls on originators who sell TBAs short to the broker dealer community via lines of credit. Typically, this strategy is considered prudent for lenders and carries little risk, as originators are simply offsetting their interest rate exposure on their locked pipeline by selling a deliverable hedge instrument. However, the sudden spike in unemployment created by the pandemic has generated considerable uncertainty around whether pipeline loans will actually be able to close. Traditional pull–through models are rendered useless, as they do not contemplate huge numbers of mortgage applicants losing their jobs within a short period of locking their loans.
The sharp uptick in expected pipeline fallout coupled with heavy hedge losses and increased volatility in the TBA market has created the perfect storm for a liquidity crisis. Within ten days of the Fed’s announcement, the Mortgage Bankers Association was sounding the alarm to regulators about the extreme pressure that mortgage originators, particularly non-bank institutions, faced in the wake of excessive TBA margin calls, and the risk of widespread defaults that would likely result unless swift action were taken.
Even with loans that make it past the closing table and into an originator’s available-for-sale warehouse, it’s not exactly business as usual in this environment. Broker-dealer balance sheets are “heavier” than usual because their network of end-account customers who typically invest in mortgage–related securities are looking to reduce their exposure to the sector. This is causing bid-ask spreads in the TBA market to widen and specified pool pay-ups to collapse, both of which cut into profit margins for originators and further strain liquidity.
Lenders that sell their originated mortgages via the agency cash window programs are not immune, either. Cash executions are rumored to be softening relative to MBS executions. Agency capital requirements related to the actual/actual remittance requirements for servicers who use the cash window are leading to higher model–implied guarantee fees. This is creating a disconnect between TBA hedges and cash window prices for closed whole loans, which also adds pressure to expected profit margins. Originators who sell to correspondent buyers face similar challenges as correspondent buyers price in additional margin to help offset extreme market volatility and the anticipation of increased future borrower credit risk.
Adding to the immediate concern about non-bank mortgage originator liquidity is the current dysfunction in the mortgage servicing rights market. Mortgage servicers in scheduled/scheduled remittance programs are on the hook to advance principal and interest payments on the mortgage, as well as tax and insurance payments when a borrower misses a payment. These advances can quickly become capital intensive, a particular concern for non-bank servicers.
As the pandemic unfolded, MSR buyers quickly evaporated as government agencies have scrambled to provide relief to borrowers facing hardship. Similar relief, however, has not been offered to mortgage servicers. With co-issue counterparties and correspondent lenders softening bids or pausing MSR purchases altogether, originators that typically sell loans servicing–released are now forced to either 1) sell at heavily discounted prices to the relatively small handful of remaining buyers, or 2) retain the asset. Both options adversely impact profit margins and exacerbate existing liquidity concerns. For originators that choose to retain servicing, the prospect of servicer advance requirements and borrower forbearance pose additional long-term capital and liquidity issues.
Not coincidentally, MSR valuations are falling. Non-bank lenders holding these assets will be at risk of breaching net-worth, leverage, and liquidity covenants for warehouse lines, MSR financing facilities, and TBA lines of credit. Breaching these covenants would have a devastating effect on the lenders’ ability to do business.
Every crisis is unique, but things are beginning to feel eerily reminiscent of 2008. During that crisis, RiskSpan leveraged its deep familiarity with mortgage credit to help capital markets participants navigate unprecedented market conditions. Today, we are assisting our mortgage originator clients with modeling the impact of COVID-19 across several areas, including:
- Balance Sheet and Liquidity Stress Testing
- Servicing Advance Scenario Modeling and Analysis
- Alternative Pipeline Hedge Coverage Models
- MSR and Whole Loan Valuations
Contact us for a free consultation.
