In a recent post[1], we discussed the various factors behind the elevated pace of prepayments in Ginnie Mae securitized pools relative to those in conventional pools. A key driver of the difference in speeds is the different incentives facing Ginnie Mae program servicers regarding loan buyouts on one hand and those facing the GSE’s on the other. In the first case, the economics of the transaction are often favorable for servicers with cash available to purchase loans out of pools while the GSE’s take a more balanced view of the interests of servicers and investors.

The key regulation driving GSE behavior in this regard is the September 30, 2020 statements by the Enterprises extending the timeframe for delinquent loan buyouts from four consecutive months to twenty four consecutive months[2]. While forbearance was not explicitly mentioned in these announcements, there is clearly a connection between this timeframe and that of the duration of the forbearance programs. For conventional loans that entered a plan prior to February 28 2021, borrowers have a maximum 18 months of forbearance available to them[3]. Since the biggest share of loans in forbearance took place in Q2 2020, that 18 month period is running out for many. As borrowers work with their servicers to consider their options, loan buyouts should start to pick up in coming months as distressed borrowers pursue loan modifications or enter into foreclosure proceedings. In addition, distressed borrowers with equity in their homes may choose to sell their properties, leading to a pickup in voluntary prepayments.

​Over the past six months, prepayment speeds of Ginnie Mae securities have notably widened against those of the GSEs.

As we mentioned in our previous blogs, Recursion’s proprietary tools Cohort Analyzer, and Pool Level Analyzer can analyze FED and CMO portfolios recursively down to the “simple pool” level. There are a wide range of applications of these powerful tools. We previously demonstrated how to calculate FED portfolio and CMO lockup rates at the macro level. Another important application is to study the collateral of mortgage bonds directly at the loan level in order to support investor’s trading decisions.
​
Before we delve into this particular CMO bond, we want to discuss the loan leverage coverage ratio for all agency pools. As we know, Fannie Mae discloses loan level information for all pools issued in and after 2013, and Freddie Mac does this for pools issued in and after 2006, while Ginnie Mae disclosures include loan level information for all pools that are not paid off. When Recursion was founded in 2015, due to its short disclosure history, Fannie Mae pools’ loan level coverage was fairly low. However, as of today, Fannie Mae’s loan level coverage has improved to close to 90%.  As time goes on and pools issued before 2013 gradually pay off, the loan level coverage of outstanding agencies pools will reach 100% as will the CMO loan level coverage.

​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.

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:

The Covid-19 pandemic has resulted in a great economic shock that has been met with a tremendous policy reaction in the form of interest rate cuts and MBS purchases by the central bank. Prepayments have picked up substantially during the year. The question arises as to whether the magnitude of the response is unusual compared to previous episodes of rate declines, and whether they can rise further should borrowing costs fall further.

The magnitude of the relationship between rates and refis is complex and depends crucially on a number of factors. First, the relationship is path-dependent. That is, it doesn’t just matter if rates fall 1.0%, but whether this decline takes rates to new lows so that the biggest possible set of borrowers can profitably refinance.
​
Great gobs of sophisticated statistics and modeling go into forecasting prepays on the part of lenders and investors. But a look at prepays over time shows three main waves of refis over the past 20 years. The first (A) is 2000-2003, (B) 2008-2013, and (C) 2019-2020. In all three instances, rates reached new lows. The dates correspond roughly to the times when the mortgage rate broke to a new low until a new trough was formed (or the present in the case of “C”)

​Here are the corresponding periods for prepays:

​Here are the corresponding periods for originations:

Here is a summary of the three periods:

Notably, the biggest jump in prepays occurred in the early 2000s, reaching a record high of 60 CPR. Rates had fallen substantially based on aggressive Fed ease in the wake of the bursting of the tech stock bubble. This passed right through to refis. There was also a substantial decline in rates with the Global Financial Crisis(GFC), but the refi response was more muted due to declining house price, but perhaps also more stretched out in time (off and on through 2013). The current episode with Covid-19 has resulted in record-low mortgage rates, and a substantial spike in refis, but still well below the experience of 2002-04.
​
What might explain the differences? A clear place to look is at credit conditions. If rates drop the same amounts in time periods X and Y, but credit conditions are tighter in Y than X, we can reasonably expect a bigger refi impact in X than Y. Below shows the Urban Institute’s Housing GSE Credit Availability Index, which is used to evaluate lender’s risk tolerance:

Note:  Urban Institute’s Housing Credit Availability Index for GSE Chanel. Adapted from Urban Institute Housing Finance at a Glance (August 2020). (https://www.urban.org/research/publication/housing-finance-glance-monthly-chartbook-august-2020)

As can be seen, credit was extremely loose before the GFC, very tight thereafter, followed by a period of modest loosening until 2019. This correlates well with the magnitude of the response of prepays to interest charges in the three regimes. Too hot, too cold and just right? Maybe.

All of this is important not just for investors but for the central bank as the Fed attempts to steer the economy through this uniquely uncertain period. Recently, credit conditions appear to have started tightening. It’s unclear whether this is a “normal” market reaction as volumes rise and capacity is constrained (good credits are easier to process) or whether lenders are becoming more cautious based on a more pessimistic view of the economic outlook. There is a big difference between the two in terms of choosing a successful investment strategy or an optimal monetary policy. The answer is unlikely to come from attempts to model borrower and lender behavior in a nuanced way and more likely to be discerned by careful observation of emerging trends in big data sets.

In a previous blog, we pointed out the importance of overseas investors to the mortgage market.[1] We looked at the share of holdings from this sector, as well as on the country breakdown within the sector. These shares tend to move somewhat smoothly over time as they represent very large portfolios of assets. There is, however, a second data set released in the TIC system every month, namely net capital flows. These data are purchases (or sales) and can be quite volatile in the short term. But they may provide a picture of emerging trends that will not show up in the holdings data for some time.

The same important caveat that applies to the holdings data applies as well to the flow data: the data on purchases and sales of assets reported for a country may be on behalf of agents domiciled in a different location, even the US.

As we have been in a declining rate environment since the start of 2019, it is not surprising that purchases of long-term agency securities have been generally strong from the point of view of asset replacement over that time. But Q2 2020 marked a break in the pattern with the onset of the Covid-19 crisis. Flows were smaller than in Q1, notably so for China, but markedly so for Hong Kong which engaged in outright sales of assets. Interestingly, Taiwan bucked the trend and added substantially to its holdings in Q2 compared to the prior quarter.
​
In the background, the economic and financial environment remains highly uncertain. Added to that is the increasing factor of rising geopolitical uncertainty as we head into the US election. Following these flows may provide useful insights into how different agents assess these considerations.

​The drop in the 30-yr mortgage rate to close to 3.0% has worked to keep purchase mortgage securitizations relatively steady while refinancing activities have soared to record highs. Refis in Q2 2020 for the GSE’s came in at more than twice the next highest quarterly figure reported over the past seven years:

Besides the sharp drop in rates, another factor in this sudden surge compared to previous years is the increasing use of Property Appraisal Waivers. With the transaction costs of refinancing going down as a result, it appears that refis accelerated compared to prior episodes of falling rates. To look at this a bit deeper, below find 1-month prepayment speeds of both PIW loans and PIW eligible purchase loans for the two agencies[1]:

​For both agencies, it appears that loans with appraisal waivers prepay faster than eligible loans without, but the impact diminishes over time in part because there are fewer such loans with a PIW left that haven’t prepaid. In fact, for non-cashout refis the impact is even more pronounced:

​In this case not only have prepayment speeds for this category of loans with appraisal waivers slowed relative to others, but in the last couple of months they have actually become slower compared to other eligible loans.
​
A combination of unprecedented policy moves and market developments have served to upend conventional mortgage market analysis, underscoring the need for new thinking, and new tools.