With the 30-year mortgage rate surging to a 13-year high near 5 ¼% and the FHFA purchase-only house price index at a record-high 19.42% in February (edging out the prior record of 19.39% in July 2021), we are in an unprecedented environment in the mortgage market. As such, it makes sense to update our analysis of the trend in issuance updated through April. Of particular interest in this regard are the FHA and VA programs.
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Let’s start by looking at FHA. By loan count, there were 107,500 FHA loans issued in GNM pools in April, with a decline of over 1/3 from the same month a year earlier. One special interest is the evolution of the share of issuance by loan purpose:

Recently, the GSE’s Fannie Mae and Freddie Mac released loan-level data associated with their “Special Eligibility Programs” that look to extend credit to low-income borrowers. As housing policy is increasingly focused on providing this market segment access to this market segment, this data will prove useful to housing analysts looking to assess the effectiveness of these programs as well as to traders looking to understand the impact on the performance of MBS containing these loans.

Briefly, each agency has three programs. There are many differences in details between the programs.

1. Low down-payment programs. Designed for low-income households with limited savings for a down payment, with flexibilities for down payment sources.
   1. FannieMae: Home Ready[1]
   2. Freddie Mac: Home Possible[2]
2. Loans underwritten by Housing Finance Agencies (HFAs)[3]
   1. FannieMae: HFA Preferred[4]
   2. Freddie Mac: HFA Advantage[5]
3. Refi programs for low-income borrowers
   1. FannieMae: Refi Now[6]
   2. Freddie Mac: Refi Possible[7]

​As the refi programs are relatively new and volumes are small, in this post we focus on the first two. For convenience, we refer to the first as the “Low-Income Programs” and the second the “HFA Programs”.
Below find the market share of Home Ready and Home Possible out of total volumes for their respective Agencies by loan count:

Credit provision is one of the great areas of concern addressed by the New Housing Policy. In a previous post[1], we mentioned that we have integrated HUD LMI Neighborhood information with our tools. We can view aggregate credit creation through Cohort Analyzer, and its composition through HMDA Analyzer.
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2020 marked an unprecedented year for mortgage production as the pandemic sparked aggressive moves by the Federal Reserve driving mortgage rates to record lows, coupled with a flight of households away from density towards more sparsely populated areas. Trends in the major programs by loan count can be seen here:

​We received the monthly GSE data download for the June book of business over the weekend and prepayment speeds dropped for the second consecutive month, with the 1-month CPR printed 22.4, the low posted since 17.1% was reached in February 2020 just before the onset of the pandemic.

Mortgage rates are of course the key driver here, but other issues matter as well, notably lending capacity. With the onset of the pandemic and the associated loosening of monetary policy and spike in demand for housing away from dense locations, the mortgage industry became overwhelmed. Originators were busy hiring and increased their capacity over the past 18 month to deal with the long period of refinancing activity.  However, as prepayment speeds slow down, it appears that the capacity building may be overshooting. In response, originators have started to lower their underwriting standards to create enough volume to fully utilize the capacity.

What we can see is that purchase demand remains strong, with the swing product being refinance mortgages. It is evident that lenders are trying to smooth out refinance production with countercyclical credit tightening and loosening. As credit scores are higher than was the case in the pre-pandemic period there is room to ease further, but the ultimate extent is highly uncertain.

Last August we reported that we had downloaded 2019 HMDA and detailed queries were accessible to our clients via HMDA Analyzer[1]. Recently, the CFPB provided a preliminary release of 2020 data, with information from smaller reporters coming a bit later in the year. Nevertheless, the new data is available on HMDA Analyzer and several insights can already be gained.
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​    1. Total Origination loan count grew to its highest level since the runup to the Global Financial Crisis,          driven by a surge in refinancings:

    2. Nonbanks Rule – Covid 19 accelerated the long-term trend increase in nonbank lending share:

    3. The held on book share collapsed, as banks preferred to hold mortgage risk in the form of MBS to            avoid the potential for credit losses:

​Much more can be found through with just a few clicks of the button.

The increase in the number of cashout refis has led to some concerns about the implications for the quality of household balance sheets, similar to what occurred in the run-up to the Global Financial Crisis[1]. At that time, many homeowners were tempted to use their houses as a “piggy bank” as the national savings rate hit all-time lows. In the runup to the Global Financial Crisis, the national savings rate hit a sixty-year low of 2.2% while over the 2016-2019 period the rate averaged a much healthier 7.6%[2].

It is useful to scale the magnitude of assets being cashed out and Freddie Mac releases a very useful file documenting this quarterly for their book of business back to 1994[3]. In the fourth quarter of 2020, the amount cashed out reached $48.4 billion, about 58% of the $84.0 billion peak attained in the second quarter of 2006. As a share of household net worth, the most recent data point is 3.7%, well below the peak of 12.7% reached in Q2 2006.

​It’s useful along these lines to ask about the credit profile of cashouts compared to other refinancings. Freddie Mac didn’t report cashout refi separately until 2008 Q3, but the following useful picture can be obtained.

In general, lenders tend to “lean against the wind” by loosening credit conditions when demand for credit declines, and vice versa. Interestingly, it appears that the share of noncashout loans follows a pattern in which the share rises when credit in general is tightened. At the present time, the average FICO score in March for noncashouts was a tight 764, vs 753 for cashouts. It is difficult to pin the rise in equity cashouts in the current cycle to loosening credit conditions.
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Of course, the proof is in performance, and now that we have loan-level DQs for the GSE’s beginning last month, we can look at this broken down by loan purpose for the Freddie Mac book:

​The performance of cashouts is mildly worse than that for noncashouts, but more in line with purchase mortgages. These statistics will bear watching in future months, particularly as forbearance programs begin to expire towards the end of the year.

In a recent post, we discussed our comment letter to FHFA regarding policies and procedures related to property inspection wavers (PIWs)[1]. In that note we commented that one of the best ways to assess the impact of the program is to look at the performance of loans with appraisal waivers vs those eligible to obtain waivers but did not. At the time the note was posted (late February 2021) the loan-level data needed to perform such a calculation was not available, so we used a sample obtained from the reference loans in the pools used by the Fannie Mae Connecticut Avenue Security (CAS) Credit Risk Transfer (CRT) program.

Earlier this month we obtained the loan level DQ data for the books of the GSEs as of the end of February 2021 so a more comprehensive analysis is now possible. As stated in the comment letter, the eligibility rules to obtain a PIW vary by product type and agency, so to obtain an apples-to-apples comparison we need to look at the performance of loans with waivers against those that are eligible to use them but did not, as opposed to all loans. Since waivers are generally a recent development, we look at performance for loans originated in 2019 and 2020.

For some time, we have been talking about the key driver of mortgage performance is policy rather than fundamentals. This theme is certainly evident with the release of agency prepayment data for November[1]. The chart below chart displays the gap between the 1M prepayment speeds between Ginnie Mae and GSE securities: