The Pipeline

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Welcome to the Pipeline, Andrew Davidson & Co., Inc.‘s newsletter, a “pipeline” of relevant and useful information, focused on recent trends, changes, and advances in the mortgage investor’s market.

Issue No. 178 | Sep 2022

A CHANGED LANDSCAPE
Eknath Belbase

With primary mortgage rates having risen from the 3-3.5% range to the neighborhood of 6% in six months, the mortgage landscape has changed dramatically, with turnover becoming a greater focus than it has been in a long time. An important consideration into how mortgage rates and spreads evolve is likely to be the newly ramped up QT limits.

THE CHANGING COMPOSITION OF POOL ISSUANCE DURING PANDEMIC TIMES
Dan Szakallas

Over the course of the last two-plus years, we have seen unprecedented behavior in the mortgage market. Interest rates on mortgages fell to historic lows for an extended period of time, and then rose extremely rapidly to high levels not seen in many years. In this article, we will look at how the interest rate movement affected the composition of pools issued by Freddie Mac by specifically focusing on loan purpose at origination.

PERSPECTIVES: FRB MBS BALANCE SHEET REDUCTION
Mickey Storms

On January 26, 2022, the Federal Reserve Board (FRB) released “principles” for reducing its balance sheet size, followed by the release of “plans” for the same on May 4, 2022.

PRIMARY-SECONDARY SPREAD (PSS) MODELING: 10 YEARS LATER
Matteo Caracciolo-King, Alex Levin, Vivian Li

We revisit the PSS model designed in 2012. We attribute much of historical PSS dependence on the level of rates to (a) the dynamics of guarantee fees (G-fees) and (b) the compounding difference between primary and secondary rates. Net of those factors, the new model is much less directional. In addition, we modified the concept of “trend factor” by making it asymmetrical thereby reflecting originators’ profit-protecting behavior. The new model has been tested for different historical intervals, including the recent COVID-19 pandemic.

NEURAL NETWORKS AND PREPAYMENT MODELING
Matteo Caracciolo-King

This article examines neural networks, which provide a general approach to evaluating a large data set with many potential input variables and complex non-linear interactions. Mortgage loan prepayments exhibit complex relationships to a wide range of variables and extensive data for tens of millions of mortgage loans. Therefore, mortgage modeling is a promising area for applying a variety of machine learning and artificial intelligence techniques.

© 2022 Andrew Davidson & Co., Inc. All rights reserved. You must receive permission from marketing@ad-co.com prior to copying, displaying, distributing, publishing, reproducing, or retransmitting any of the content contained in The Pipeline.
This publication is believed to be reliable, but its accuracy, completeness, timeliness, and suitability for any purpose are not guaranteed. All opinions are subject to change without notice. Nothing in this publication constitutes (1) investment, legal, accounting, tax, or other professional advice or (2) any recommendation or solicitation to purchase, hold, sell, or otherwise deal in any investment. This publication has been prepared for general informational purposes, without consideration of the circumstances or objectives of any particular investor. Any reliance on the contents of this publication is at the reader’s sole risk. All investment is subject to numerous risks, known and unknown. Past performance is no guarantee of future results. For investment advice, seek a qualified investment professional. Note: An affiliate of Andrew Davidson & Co., Inc. engages in trading activities in securities that may be the same or similar to those discussed in this publication.

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Date:
09-2022
Issue:
178
Author:
Eknath Belbase
Date:
09-2022
Issue:
178
Author:
Dan Szakallas
Date:
09-2022
Issue:
178
Author:
Mickey Storms
Date:
09-2022
Issue:
178
Author:
Matteo Caracciolo-King
Alex Levin
Vivian Li
Date:
09-2022
Issue:
178
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Matteo Caracciolo-King
Date:
07-2022
Issue:
177
Author:
Eknath Belbase
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07-2022
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177
Author:
Mickey Storms
Date:
07-2022
Issue:
177
Author:
Alex Levin
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07-2022
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177
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Connor Campbell
Date:
03-2022
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176
Author:
Eknath Belbase
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03-2022
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176
Author:
Sanjeeban Chatterjee
Daniel Swanson
Richard Cooperstein
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03-2022
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176
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Alex Levin
Daniel Swanson
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03-2021
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175
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Eknath Belbase
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03-2021
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175
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Daniel Swanson
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03-2021
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175
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John Gao
Alex Levin
Daniel Swanson
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03-2021
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175
Author:
Tom Parrent
Date:
12-2020
Issue:
174
Author:
Eknath Belbase
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12-2020
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174
Author:
Alex Levin
Date:
12-2020
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174
Author:
Eknath Belbase
Date:
10-2020
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173
Author:
Eknath Belbase
Date:
10-2020
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173
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Chris Widman
Date:
10-2020
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173
Author:
Alex Levin
Date:
08-2020
Issue:
172
Author:
Eknath Belbase
Date:
08-2020
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172
Author:
Daniel Swanson
Date:
08-2020
Issue:
172
Author:
Dan Szakallas
Date:
04-2020
Issue:
171
Author:
Eknath Belbase
Date:
04-2020
Issue:
171
Author:
Dan Szakallas
Kevin Atteson
Daniel Swanson
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04-2020
Issue:
171
Author:
Chris Widman
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04-2020
Issue:
171
Author:
Mickey Storms
Richard Cooperstein
Date:
04-2020
Issue:
171
Author:
Alex Levin
Date:
03-2020
Issue:
170
Author:
Eknath Belbase
Date:
03-2020
Issue:
170
Author:
Mickey Storms
Alex Levin
Date:
02-2020
Issue:
169
Author:
Eknath Belbase
Date:
02-2020
Issue:
169
Author:
Chris Widman
Date:
02-2020
Issue:
169
Author:
John Gao
Alex Levin
Daniel Swanson
Date:
12-2019
Issue:
168
Author:
Eknath Belbase
Date:
12-2019
Issue:
168
Author:
Chris Widman
Date:
12-2019
Issue:
168
Author:
Alex Levin
Nathan Salwen
Date:
09-2019
Issue:
167
Author:
Eknath Belbase
Date:
09-2019
Issue:
167
Author:
Andrew Davidson
Feiqi Jiang
Alex Levin
Date:
09-2019
Issue:
167
Author:
Chris Widman
Date:
06-2019
Issue:
166
Author:
Eknath Belbase
Date:
06-2019
Issue:
166
Author:
Dan Szakallas
Date:
06-2019
Issue:
166
Author:
Sanjeeban Chatterjee
Date:
04-2019
Issue:
165
Author:
Eknath Belbase
Date:
04-2019
Issue:
165
Author:
Alex Levin
Date:
04-2019
Issue:
165
Author:
Richard Cooperstein
Date:
02-2019
Issue:
164
Author:
Eknath Belbase
Date:
02-2019
Issue:
164
Author:
Eknath Belbase