📄 Extracted Text (486 words)
27 March 2015
US Fixed Income Weekly
Interpreting tradable implications and qualifications
Our model is based on a regression of high-LTV and loan balance pay-ups on a
small set of variables:
• Refinance incentive: measured as the gross WAC on the TBA deliverable
for a given period less the prevailing mortgage rate. This variable captures
the price premium in the corresponding TBA, increased prepay risk in the
TBA, and changes in the fair value of the dollar roll. As refi incentive
increases, so too should pay-up value
▪ Cumulative refinance incentive: Measures how long a given TBA cohort has
been exposed to refi incentive. This variable captures borrower burnout
and will interact with the impact of refi incentive. For higher levels of
cumulative refi incentive, increases in refi incentive will have less of an
impact on pay-up value as prepay sensitivity in the TBA is diminished
• Month-over month change in primary rate: Measures the momentum and
persistence of rate moves and can also change the impact of refi incentive.
Pay-up values should change with a lag to sudden rate moves, as the new
level will need to be sustained to translate into a real change in prepays.
In addition to the core set of variables used in the loan balance model, we also
found that a measure of national home price appreciation provided additional
explanatory power for CQ pools. For that measure we simply used the year-
over-year percentage change in the S&P Case-Shiller 20-city home price index.
Interestingly, that measure did not improve explanatory ability for CR pools,
and is not included in that model. That difference seems reasonable given the
minimum 105 UV on CQ pools versus the 125 LTV minimum on CR pools —
home price appreciation is much less likely to spring CR borrowers from
negative equity in the near term.
The high-LTV model is a strong fit, explaining nearly 97% of observed variance,
similar to the loan balance model. Using these models, loan balance 4.5%s
look undervalued, while CR pools look overvalued. For instance, in LLB 4.5%s
the difference between actual pay-up and model pay-up suggests that the
story is undervalued by $2-04+.
Of course, the model obviously does not fit perfectly —in fact, looking at the
historical model predicted value versus actual shows a standard deviation of
the error of $0-08. However, in the case of the LLB 4.5%s, the current
difference of $2-04+ is 8.4 times the error standard deviation. Similarly, the
actual pay-up on CR 4.5%s is $0-22 higher than the model value, which is 2.3
times the standard deviation of the error.
Constructing a model o€ high-LTV pay-ups
The most interesting aspect of this exercise is again that the relationship
between refi incentive and pay-up is not linear in high-LTV pools, but instead is
curved (Figure 8).
Page 38 Deutsche Sank Securities Inc.
CONFIDENTIAL - PURSUANT TO FED. R. CRIM. P. 6(e) DB-SDNY-0087419
CONFIDENTIAL SDNY_GM_00233603
EFTA01385951
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