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Broker loans boost negative convexity in prime 2.0

| April 9, 2021

This document is intended for institutional investors and is not subject to all of the independence and disclosure standards applicable to debt research reports prepared for retail investors.

Large populations of prime jumbo loans coming through broker or warehouse channels are lifting prepayment speeds in new private-label deals and may show slower speeds out-of-the-money, increasing deal negative convexity. Deals heavy concentrated in these loans should trade at wider spreads to account for the greater option cost, although investors looking for carry may find opportunity in deals that have dropped out of the refi window.

Analyzing the effect of TPO loans in prime 2.0

An analysis of fixed rate loans backing post-crisis prime securitizations shows that given the same amount of refinancing incentive after adjusting for any risk based pricing or SATO on a given loan, those originated through broker or wholesale channels have historically prepaid faster than loans originated through retail channels when in-the-money and slower when further out-of-the-money.  (Exhibit 1)

Exhibit 1: Broker and wholesale loans exhibit steeper S-curves in prime 2.0

Source: CoreLogic, Intex, Amherst Pierpont

The difference in speeds between retail and broker or wholesale channels is most pronounced when loans are either at or slightly in-the-money or when loans are further out-of-the-money. Loans originated through broker or wholesale channels tend to prepay roughly 5 CRR faster than those originated through retail channels when either at-the-money or 25 bp in-the-money and 10 CRR slower when 50 bp out-of-the-money. While it’s difficult to say with certainty what may be driving these differences, it seems plausible that broker and wholesale channels may be more operationally efficient in refinancing loans with small amounts of refinancing incentive driving faster speeds on loans that are slightly in-the-money. Conversely, as loans fall out of the money and refinancing volumes decrease, broker and wholesale channels may be more focused on originating higher margin products like expended credit or non-QM loans against the backdrop of tighter primary secondary mortgage spreads, decreasing gain-on-sale margins and lower volumes in higher credit quality borrowers.

Loans originated through broker and wholesale channels with conforming jumbo balances that could potentially be refinanced in an agency execution may be the most negatively convex of those originated through these channels as they exhibit steeper S-curves than those of loans with both higher and lower balances. This is consistent with broader trends in prime 2.0 over the past year in that despite greater savings given the same amount of refinancing incentive, loans with non-conforming jumbo balances have prepaid slower than those with jumbo conforming balances. This is likely largely attributable to lower frictions to refinancing associated with loans that could have gone to agency execution over the past year as channels to refinance larger balance loans narrowed due to broader pandemic related market disruptions. However, this phenomenon may continue to hold up into the future across loans originated through broker and warehouse channels as broker networks may be more attune to private label to agency cross-refinancing options for borrowers (Exhibit 2).

Exhibit 2: Jumbo conforming TPO loans exhibit the steepest S-curves

Source: CoreLogic, Intex, Amherst Pierpont

Given this, scanning for deals with large amounts of TPO loans with conforming balances and GWACs that are roughly at or slightly in the money may provide a useful guidepost for deals that may exhibit worse convexity going forward while deals with lower concentrations of TPO loans may exhibit better convexity all else equal. (Exhibit 3)

Exhibit 3: Scanning the prime universe for TPO and conforming balance loans

Source: CoreLogic, Intex, Amherst Pierpont
Percentages are measured based on collateral composition at deal closing

Deals with larger concentrations of both TPO and conforming balance loans are largely seasoned Flagstar trusts and 2019 and 2020 vintage JPMMT deals backed by both conventional and high LTV collateral. The impact of higher concentrations of TPO loans may be more pronounced in trust backed by conventional collateral than in high LTV deals as high LTV loans, especially those with LTVs greater than 90, have generally exhibited flatter S-curves and slower prepayment rates. Conversely, certain WFMBS, Pearl Street and seasoned transactions issued by a number of sponsors have relatively small amounts of TPO and conforming balance loans and are substantially less exposed to this phenomenon.

Investment implications

While the market does not currently price in the presence of higher TPO, more negatively convex collateral it likely should, as investors should require more nominal spread to account for the greater option cost associated with the greater negative convexity. While growing amounts of negative convexity may drive broad based spread widening in higher TPO pools, it may create opportunity in certain cash flows. Given the recent amount of issuance backed by lower WAC, out-of-the-money collateral, investors may target higher coupon pass-throughs or derivatives in deals stocked with large amounts of loans originated through broker or wholesale channels. The combination of almost non-existent out-of-the-money speeds coupled with a steep forward curve predicting higher forward mortgage rates may have the combined effect of dampening prepayment rates and driving enhanced carry. The obvious caveat is that carry may decrease on inverse IO against the backdrop of higher forward rates.

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