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COVID-19 and the Mortgage Market

Coronavirus   |   Risk, Performance, and Reporting

By Tom P. Davis, PhD, CFA  |  May 13, 2020

For many of us, the scale of the coronavirus crisis reminds us of 9/11 or the 2008 financial crisis—the events may reshape people’s behavior in a long-lasting way. As the event continues to unfold, we’ve found ourselves in uncharted territories. In this article, we will address some policy changes related to the U.S. mortgage market and our model changes as well as a few tuning parameters that can be used to adjust our U.S. mortgage prepayment model to reflect the potential impact of COVID-19.

Mortgage Market Update

The coronavirus pandemic has put tremendous pressure on the U.S. economy. To stop people from spreading the virus, social distancing was introduced in early March. Many states have also implemented shelter-in-place or stay-at-home orders. The lockdowns have led to the collapse of the U.S. economy. Over the last eight weeks, a total of 36.5 million Americans have filed for unemployment insurance [1]. According to the Congressional Budget Office[2], the unemployment rate is expected to exceed 10% during the second quarter, as high as the peak of the last recession. GDP is expected to decline by more than 7% for the second quarter. The stunning figures stated above may not even reflect the complete impact on the economy, as many people who lost jobs do not qualify for unemployment benefits. The long-term impact will take months to unfold and is still uncertain at this point. 

With a record increase in jobless claims, mortgage delinquencies and missing rental payments are likely to rise. The impact on the rental market may be more significant because hourly workers tend to be laid off first and are more likely to be renters than homeowners. The first hard data related to the rental market that we have seen comes from the rent payment tracker published by the National Multifamily Housing Council (NMHC)[3] on April 8. The tracker found that only 69% of renters had paid their rent through April 5, a 12% decrease compared to the previous month and the same time last year. In anticipation of financial hardship related to COVID-19, HUD[4] and FHFA[5] have rolled out several policies to help mortgage borrowers. Foreclosure and evictions are suspended for at least 60 days. Hardship forbearance for both single-family and multifamily borrowers is recommended for servicers and forbearance plans provide borrowers with payment relief for up to 12 months. Late charges and penalties are suspended as well. Forbearance is also eligible for a second home or an investment property. According to the Mortgage Bankers Association (MBA) Forbearance and Call Volume Survey released on April 7, the total number of loans in forbearance has jumped from 0.25% to 2.66% in the one month between March 2 and April 1[6]. Ginnie Mae loans have seen the biggest growth from 0.19% t to 4.25%. The surge in delayed payments will not have an immediate impact on investors because mortgage servicers must advance scheduled payments to investors even if end borrowers fail to make their payments. MBA estimated the surge in delayed mortgage payments will cost the mortgage servicing industry as much as $100 billion over the next nine months[7]. Stronger servicers will not need much assistance, while many smaller servicers will require some level of support from the government given the scale of this forbearance program at the duration required. The mortgage industry and housing associations have called on the federal government to establish a liquidity facility for servicers[8] as Ginnie Mae modified an existing program to provide short-term liquidity support for some of its servicers[9].

With an increased number of loans in forbearance, the growth of delinquent loans could be slower than the initial estimate. However, we still expect the early delinquency rate to rise given the magnitude of reported jobless claims in recent weeks. It will take a few months for early delinquent loans to transition into serious delinquent loans and many of them will be qualified for payment forbearance. Payment forbearance won’t trigger a buyout event and therefore, buyout-related prepayment speed won’t rise significantly in the near term. The delinquency trigger of the credit risk transfer (CRT) deals, usually based on the level of seriously delinquent loans, will not be hit right away either. The newer transactions, which have lower credit enhancements, will more likely fail the delinquency test earlier than the seasoned transactions. Some forbearance loans may lead to further loan modification or a higher default rate later. The losses will then be passed to CRT investors in reverse sequential order.

Housing market activities dropped significantly after social distancing measurements took effect. As of March 27, the purchase index decreased 24% versus the same week one year ago. Based on the data from ShowingTime website[10], the showing activities through mid-March were higher year-over-year. Since then, the showing is down roughly 60% versus the same time last year. The turnover rates are expected to drop to reflect a weak spring home-buying season.

Treasury rallied at beginning of March and so did mortgage rates. In the following two weeks, mortgage rates rose as the primary and secondary spread widened despite the treasury rate remaining low. The erratic mortgage rate movement in March was probably the result of liquidity concerns related to the MBS market since lenders usually securitize mortgage loans to hedge risk. In response, the Federal Reserve has rolled out unlimited quantitative easing to inject liquidity into the market. The mortgage rate may start to drift lower as liquidity concern is lifted. In addition, FHFA has granted flexibilities for appraisal and employment verifications as well as loan processing. However, lenders’ pipelines will remain clogged and processing time will be prolonged. The overall rate incentive for the borrowers will remain high, but the s-curve will flatten due to extended processing time.

LIBOR Market Model Update

In response to historically low rates in the fixed income space, option-adjusted analytics (e.g., OAS, Coupon Curve Duration, Coupon Curve Convexity, Spread Duration) calculated for securities in the U.S. securitized market that currently uses Monte Carlo model (MC Model)/LIBOR market model (LMM) will undergo the following changes.

  1. Switch caplet volatilities used in calibration for MC Model from using lognormal volatilities to normal volatilities. In low or negative interest rate environment, lognormal volatilities start to break down due to the assumption that the underlying rates are lognormally distributed (and therefore cannot be negative). On the other hand, rates in the normal model can be both infinitely positive and negative and therefore, we will use normal volatilities for caplets moving forward (swaptions are already using normal volatilities) for MC Model calibration.
  2. Increase lognormal shift in Shifted Lognormal LMM from 200 bps to 400 bps. The current form of instantaneous volatility used in LMM is shifted lognormal with a 200 bps shift. The current choice of shift makes the rate floor at -200 bps. Give the current low interest rate environment, we have determined that this rate floor is too high, especially when a minus 200 bps shock is applied in a scenario analysis. Thus, we decided to increase the shift to 400 bps.
  3. Add an alternative MC Model with a normal instantaneous volatility assumption. The normal form of instantaneous volatility used in LMM does not impose a rate floor at any level. Thus, it is free from any changes in interest rate levels. This model can be accessed via a change in Fixed Income Settings (@FS) and will be released later in May.

A good way to compare different LMM set-ups is to look at how good the calibration is compared with market data. The metric we use internally is the residual sum of squares (RSS) of calibrated instrument volatilities compared to market input volatilities. The figure below shows during March, normal LLM became the best set-up because of the lowest RSS. On the other hand, lognormal LMM with a 400 bps shift improved marginally over lognormal LMM with a 200bps shift.

RSS Calibration VS Market Data

FactSet U.S. Prepayment Model Knobs and Dials

Given the uniqueness of this event and the rapid changes of various policies, we are recommending clients use model dials to adjust our U.S. prepayment model to reflect the potential impact. Ramping or fading multipliers allow users to create a ramp of prepayment speed and adjust down for the coming months and let it ramp back to normal over a few months. For example, as illustrated in the next figure, a 30 percent multiplier can be applied to the prepayment speed and then a slow ramp back to 100 percent in six months.

prepayment_assumption-multipliers

Another available feature is the factor multipliers, which adjust individual components of the prepayment model. The refi twist multiplier is a new tuning knob, which allows the user to steepen or flatten the s-curve. The turnover multiplier can be used to lower the overall turnover rate to reflect the current market condition.

Prepayment-Assumption-refi-twist-multiplier

Conclusion

There remains much uncertainty in the mortgage market related to the impact of the coronavirus pandemic. The CARES Act and various policy changes will provide temporary relief for mortgage borrowers but borrowers’ financial hardships may last longer if the job market recovers slowly, which may lead to a higher default rate later. The prepayment speed of the U.S. mortgage pool may slow down due to the weaker housing market as a result of social distancing and clogged lenders’ pipeline. The payment forbearance plan at the current scale will put many smaller servicers under severe financial constraints without the support from the federal government; that presents a potential risk to the mortgage market.

In response to the low rates, we have updated our LIBOR Market Model with normal caplet volatility and increased the shift to 400. An alternative Monte Carlo Model with normal instantaneous volatility assumption will be released soon. For the U.S. agency prepayment model, we recommend several tuning options to adjust prepayment speed slower and will continue to introduce features that give users greater ability to tune the model.

 

[1] U.S. Department of Labor Unemployment Insurance Weekly Claims Report

[2] Congressional Budget Office: Updating CBO’s Economic Forecast to Account for the Pandemic

[3] National Multifamily Housing Council: NMHC Rent Payment Tracker Finds 12 Percentage Point Decrease in Share of Apartment Households that Paid Rent by April 5

[4] HUD COVID-19 Resources and Fact Sheets

[5] Coronavirus Assistance Information by FHFA

[6] Mortgage Bankers Association: MBA Survey Shows Spike in Loans in Forbearance, Servicer Call Volume

[7] Mortgage Bankers Association: March 20 letter to Mnuchin and Federal Reserve Chairman Jerome H. Powell

[8] Mortgage Bankers Association: Financial Services Industry and Affordable Housing Advocates Call on Financial Regulators to Establish a Liquidity Facility

[9] Ginnie Mae: Ginnie Mae approves private market servicer liquidity facility

[10] ShowingTime: Impact of COVID-19 on Real Estate Showings in North America

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Tom P. Davis, CFA

Vice President, Director Research, Fixed Income & Derivatives

Dr. Tom Davis is Vice President, Director Research, Fixed Income & Derivatives at FactSet. In this role, he is focused on ensuring FactSet is providing the highest quality derivative analytics and growing the coverage across all asset classes. His team also conducts cutting edge research in the models and methods of quantitative finance which will ultimately increase the speed and accuracy of FactSet analytics. Prior to FactSet, Mr. Davis spent four years at Numerix as Vice President of Product Management in charge of their flagship product and four years managing a team of quantitative analysts at FINCAD focused on arbitrage-free modeling of interest rates and foreign exchange rates to price exotic hybrid derivatives. Mr. Davis earned a Doctor of Philosophy in theoretical physics from the University of British Columbia in Vancouver, Canada.

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