Second Lien Misrepresentation, RMBS Losses, and Pricing

VI. Second Lien Misrepresentation, RMBS Losses, and Pricing

So far we analyze asset misrepresentation at the loan level. We now turn our attention to the impact of second-lien misrepresentations on the RMBS market including the losses suffered by investors who invested in securities backed by such misrepresented collateral.

To perform our pool-level analysis, we restrict our sample to pools with at least 25% of loans for which we can compute whether the loan was misrep- resented. Moreover, we focus on pools for which both FICO and CLTV are nonmissing for at least 95% of included loans and reliable coupon data at is- suance are available in the ABSNet database, which yields a sample of 333 pools containing 669,462 loans. We note that on average 4.3% of loans in a pool have second-lien misrepresentation in this sample. We experiment with the thresholds above and find that our qualitative inferences below are similar. 18 For each of the mortgage securities associated with these pools, we collect data from Bloomberg (as of 2014Q1) on their initial subordination levels, cumula- tive losses, subsequent ratings downgrades, and price changes. This allows us to analyze the relation between misrepresentation, losses, and the price of mortgage securities.

A. Second-Lien Misrepresentation and RMBS Losses We start our analysis by verifying that, consistent with our loan-level re-

sults, pools with a larger share of misrepresented loans suffer larger losses. We estimate a series of pool-level regressions in Table V , Panel A of the following form:

(2) The dependent variable in the first two columns of the table is the pool’s

Y i =α+βX i + γ × Percent Misreported Second i +ε i .

cumulative loss in percentage terms. The pool cumulative loss data are from Bloomberg and reflect losses up to the first quarter of 2014. The coefficient of interest is on Percent Misreported Second, the percentage of loans in a pool with

18 Consistent with our loan-level analysis, misrepresentations of second-lien status are concen- trated among pools with a larger share of purchase loans and in pools with lower reported CLTVs.

These pools also have lower average credit scores (see the Internet Appendix).

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Table V

Impact on RMBS Market: Second-Lien Misrepresentation, Losses, and Pricing

Panel A presents OLS estimates from regressions in which the dependent variable is (i) the pool’s cumulative loss, defined as the initial balance weighted average cumulative loss of pool tranches (columns (1) and (2)); (ii) the pool’s issuance yield spread in percentage terms (columns (3) and (4)); and (iii) the pool’s AAA subordination level in percentage terms, defined as the lowest subordination level given to a tranche in the pool that received a credit rating of AAA (columns (5) and (6)). Panel B presents OLS estimates from regressions from the sample of 333 pools in which the dependent variable is (i) the pool cumulative loss on tranches with below-AAA initial rating by Standard & Poor’s; (ii) the pool cumulative loss on tranches with below-AAA initial rating by Standard & Poor’s; (ii) the pool cumulative loss on tranches with below-A initial rating by Standard & Poors; (iii) the pool cumulative loss on tranches with AAA initial rating by Standard & Poors; (iv) the ratings downgrades of AAA tranches in notches in the sample of 2,553 tranches (the more negative the number, the larger the downgrade), and (v) the change in the price of AAA tranches in percentage terms in the sample of 1,706 tranches for which Bloomberg reports these data. Percent Misreported Second is the percentage of loans in the pool identified as having a second-lien misrepresentation. Reported CLTV is the average reported CLTV of loans in the pool disclosed to investors. Other controls include the pool-level means of origination variables such as the credit score (FICO) of borrowers or the fraction of loans with low documentation, as well as the overcollateralization percentage of the pool. Data on RMBS losses, downgrades, and price changes come from Bloomberg (as of 2014Q1). The results are presented for specifications with and without underwriter fixed effects for the top six underwriters in our sample. Standard errors are in parentheses. *p < 0.10, **p < 0.05, and ***p < 0.01.

Panel A: Pool Level Analysis: Second-Lien Misrepresentation, Losses, and Pricing

Subordination level (1)

Losses

Yield spread

(5) (6) Percent misreported

(0.00471) (0.0222) (0.023) Reported CLTV

(0.0113) (0.0622) (0.0623) Underwriter FE

No Yes Other controls

Yes Yes Number of pools

Panel B: Second-Lien Misrepresentation and Losses for Junior and Senior RMBS Tranches

AAA ratings AAA price

downgrades change

(4) (5) Percent misreported

(0.0199) (0.1087) Reported CLTV

(0.0368) (0.2375) Underwriter FE

Yes Yes Other controls

Yes Yes Mean

Yes

Yes

Yes

57.33 91.20 3.99 −17.24 −22.73 R 2 0.292

2663 second-lien misrepresentation. To calculate this measure, we divide the number

Asset Quality Misrepresentation by Financial Intermediaries

of loans in the pool with the particular misrepresentation by the number of loans in the pool for which we can potentially identify such a misrepresentation. The vector of control variables X includes the pool-level means of common risk factors, such as the CLTV of loans in a pool reported to investors, the mean FICO credit score of borrowers, the fraction of loans in the pool with low documentation, and the fraction of loans in the pool that are purchase loans. To assess robustness of our findings, we also consider specifications that include underwriter fixed effects.

The estimates in the first two columns of Table V , Panel A indicate, as ex- pected, that pools with higher reported CLTV of the pool correspond to riskier pools that had more losses. More importantly for our purpose, pools with a larger share of misrepresented loans suffered significantly larger losses. Con- trolling for other observable characteristics of pools reported to investors, a 1% increase in the share of misrepresented loans in a pool is associated with a

0.25 percentage point increase in the pool cumulative losses. This estimate implies that a cumulative loss in a pool with an average level of misrepresen- tations in the data (4.3%) would be 1.08 percentage point larger compared to the loss in a similar pool on reported characteristics but with no second-lien misrepresentation. This effect implies a more than 12% increase in the pool cumulative loss relative to the mean in our sample (8.9%).

B. Second-Lien Misrepresentation and RMBS Prices We next investigate whether the pricing of mortgage securities at their is-

suance reflected the lower quality of pools that had a larger share of misrepre- sented loans, given that such pools suffered significantly higher losses. Specif- ically, we assess whether investors paid lower prices for the securities backed by loans with a higher misrepresentation level relative to similar securities on disclosed characteristics but with fewer misrepresentations.

Investigating this issue is challenging for several reasons. First, we do not have access to actual prices paid by investors for all securities at the time of pool issuance. This issue is common in existing literature that uses model- generated prices rather than actual prices (e.g., prices generated by Bloomberg or Intex) or indirect proxies such as subordination rates. Second, even if we were to observe the pool tranche prices, we would need a structural model to assess whether the variation in these prices is sufficient to compensate investors for the additional default risk. Constructing such a structural model is difficult, as it requires, among other things, modeling expectations of market participants while accounting for the complex structure of many pools with multiple tranches and rules governing the distribution of cash flows.

Nevertheless, to shed some light on this question we consider the statistical relationship between two proxies for pool prices employed by prior literature 19

19 See, among other, Faltin-Traeger, Johnson, and Mayer ( 2010 ), Demiroglu and James ( 2012 ), and He, Qian, and Strahan ( 2013 ), who employ similar pricing measures.

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and our measure of collateral misreporting. The first measure we use is the imputed yield spread of a pool. We calculate the yield from the tranche coupon rates and subtract from it the comparable maturity Treasury yields to obtain yield spreads, which takes into account the variation in the expected maturity of mortgage securities. The second measure, an important metric that emerges from rating agencies, is the AAA subordination level of the pool, that is, the fraction of a pool rated below AAA and hence protecting AAA-rated tranches. To the extent that prices of the pools reflect the riskiness of mortgage securities, we would expect pools with more misrepresented collateral, all else equal, to have higher yield spreads and/or higher subordination levels.

In Table V , Panel A we estimate a series of pool-level regressions like equa- tion (2) where the dependent variable is now the pool’s average yield spread (columns (3) and (4)) and AAA subordination level (columns (5) and (6)) at pool issuance. The table also displays the estimate for the reported CLTV of the pool to investors. This allows us to investigate whether the disclosed information regarding the pool CLTV is related to our pricing measures.

The results in the last four columns of Table V , Panel A show that the coefficients on the percentage of misrepresented second-lien loans in the pool are statistically insignificant for both imputed yields and subordination levels protecting AAA-rated tranches. These results are not likely to be an artifact of low statistical power as there is significant variation in the level of second-lien misrepresentation across the pools in our sample—on average, 4.3% of loans in a pool have a second-lien misrepresentation, with a standard deviation of 5.6%; the range is from 0.3% to 40% of loans in a pool being misrepresented.

In contrast, the results in Table V , Panel A indicate that the reported average CLTV in the pool is strongly and robustly related to the pool imputed yield and AAA subordination level. The estimates imply that a 10% absolute increase in the pool-reported CLTV is associated with a 33 bp absolute increase in the yield spread (about a 40% increase relative to the sample mean) and a 1.7% absolute increase in the AAA subordination level (about a 20% increase relative to the sample mean). We note that these estimates on the relation between reported CLTV and pricing measures are very similar both qualitatively and quantitatively to those reported in the literature (see Demiroglu and James ( 2012 )).

These results have two main implications. First, our pricing results indicate that at issuance investors were unable to distinguish mortgage pools with a large amount of misrepresented assets, which as a consequence suffered larger losses, from those that had very few misrepresentations. The evidence on pool subordination level also suggests that ratings agencies did not correct the misreported quality of the pools by demanding a higher subordination level to protect higher rated tranches in pools with a larger share of misrepresented loans. Second, the evidence that the reported CLTV is related to pool prices suggests that the securities backed by misrepresented collateral were sold for more than what their price would have been had their characteristics been truthfully reported to investors.

2665 We illustrate the economic magnitudes of this latter effect with an example

Asset Quality Misrepresentation by Financial Intermediaries

on a specific pool, Home Equity Trust Securities, which was underwritten by Lehman Brothers in 2006. Our data indicate that this pool had a reported av- erage CLTV of 80.6%, a 38 bp yield spread, and a 17.3% subordination level at issuance. We identify a significant number of loans in this pool that were mis- represented on the second-lien dimension, and consequently the actual average CLTV of this pool at issuance was considerably higher, reaching about 88.3%. Using specification (2) we can perform a simple counterfactual exercise and estimate what the yield spread and subordination level of this pool at issuance would be, if the true average CLTV level had been reported to investors. With the increase in CLTV from 80.6% to 88.3%, the yield spread would increase to 64 bps, which is a 26 bp absolute increase (68% relative increase), and the subordination level would increase to 18.8%, a 1.5% absolute increase (8.7% relative increase).

This example reveals the potentially large economic significance of second- lien misrepresentation on the profits of financial intermediaries. In the example above, the second-lien misrepresentation could increase the sale proceeds by more than 1% of the outstanding principal balance of mortgages in the pool. 20 This is a large amount, given that the net proceeds to intermediaries from buying and selling loans in the secondary mortgage market are at most a few percentage points (e.g., 1% to 2%) of the outstanding pool balance.

C. Which Investors Were Affected?

C.1. Losses across Rating Categories We now investigate which investors were adversely affected due to purchases

of RMBS backed by misrepresented collateral. Because of significant leverage embedded in the lower junior tranches, even a relatively modest reduction in the overall pool payments due to misrepresentations can imply a large decline in payments to the holders of junior tranches. Thus, given the findings of Sections VI.A and VI.B, it is apparent that investors of junior tranches would have suffered losses.

This point can be illustrated by a simple example. Consider a junior tranche representing 10% of collateral. Suppose that the baseline pool cumulative loss if loan characteristics are truthfully reported is 8%, which roughly corresponds to our data. Ignoring the impact of the timing of defaults on payments and dis- counting, in the baseline scenario the lowest tranche gets payments equivalent to roughly 2% (10–8%) of the outstanding pool principal at origination. Now,

in line with our estimates from Table V , Panel A, if about 4.3% of loans are misrepresented in a pool, the overall pool cumulative loss will be roughly equal to 9.08% (8% + 4.3 × 0.25%). This 1.08% increase in the pool cumulative loss implies that the lowest tranche would now obtain a payment of only 0.92% of

20 If the effective pool maturity (e.g., due to prepayment and so on) is on the order of five years or more, a 26 bps difference in annual yield can imply more than a 1% difference in the pool initial

price.

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the outstanding principal—a more than 50% reduction relative to the case in which the quality of loans corresponds to their disclosed characteristics.

We investigate this argument more formally in Table V , Panel B, which uses pool-level regressions of the form similar to the first two columns in Table V , Panel A. The dependent variable in the first column is the cumulative loss of below-AAA-rated tranches in a pool. As expected, relative to the relation be-

tween losses on the entire pool (column (2) of Table V , Panel A), we observe

a much stronger economic association between the percent misrepresentation in a pool and cumulative losses borne by junior tranches. The estimates imply that a 1% increase in the percentage of loans with second-lien misrepresenta- tion in a pool is associated with an absolute 1.4% increase in the cumulative losses of tranches with below-AAA ratings—almost six times as much as the corresponding effect of about 0.25% for the pool cumulative losses. Naturally, this association is even stronger for the most junior tranches that have the highest embedded leverage. We can observe this from results in column (2). A 1% increase in the percentage of loans with second-lien misrepresentation in

a pool is associated with an absolute 5.7% increase in cumulative losses of its tranches with below-A ratings. Interestingly, even the most senior and safest AAA tranches appear to suffer larger losses if the fraction of misrepresented loans in a pool is larger, despite being protected by the junior tranches. Column (3) of Table V , Panel B presents these results. We observe that a 1% increase in the fraction of misrepresented loans in a pool is associated with a 0.21% absolute increase in the cumulative losses for AAA-rated tranches. This point can also be demonstrated by ana- lyzing the association between subsequent downgrades of initially AAA-rated tranches as well as their subsequent price declines as reported by Bloomberg. Indeed, the last two columns of the table show that AAA-rated tranches from pools with a higher fraction of misrepresented loans suffered larger subsequent ratings downgrades and greater subsequent price declines.

Overall, this evidence indicates that every rating class of mortgage secu- rities exposed to misrepresentations suffered losses, with the largest losses concentrated among the junior tranches. We illustrate the potential economic magnitude of these effects by comparing the losses in a pool with second-lien misrepresentation at the sample mean (4.3%) to a pool with similar reported

characteristics and no misrepresentation. Our estimates from Table V , Panel

B imply that the cumulative losses in the mean misrepresented pool would be larger in absolute (relative) terms by 0.9% (30%) for AAA-, 6% (12%) for below- AAA-, and 24% (37%) for below-A-rated tranches. Note that this increase in losses of below-A-rated tranches implies a relative reduction in payments of about 74% on average compared to the below-A-rated tranches from similar pools on reported characteristics but with no second-lien misrepresentation.

C.2. Losses Borne by Insurance Companies Is it possible to determine the identities of investors who bought RMBS

backed by misrepresented collateral and suffered these losses? We are not

2667 able to investigate which particular investors were directly hurt by second-

Asset Quality Misrepresentation by Financial Intermediaries

lien misrepresentations since data on which investors held different mortgage securities are not available. However, as in Merrill et al. ( 2014 ), we are able to use information on holdings of one class of investors—insurance companies— from their disclosure filings to shed some light on this issue. Using informa- tion disclosed by insurance companies, we extract precise information on the tranches bought by these investors. We match these tranches to the pools in

the sample that we employ in Table V .

Table VI , Panel A displays the distribution of RMBS tranches in our sample that are bought by insurance companies, their initial credit ratings, and the losses suffered by these tranches. The majority of the acquisitions by these investors consist of AAA-rated RMBS securities, though more than 20% of tranches purchased by insurance companies had below-AAA initial ratings. As is also shown, tranches bought by insurance companies across rating categories suffered losses, with very large subsequent losses for lower rated tranches.

Column (1) of Table VI , Panel B investigates whether insurance companies shied away from securities backed by misrepresented collateral. We find no evidence that insurance companies avoided purchasing tranches from misrep- resented pools. If anything, it appears that these firms were more likely to buy securities backed by pools with a somewhat larger share of misrepresented loans. This evidence is consistent with our previous results on pool pricing, indicating that investors were unable to distinguish pools with a larger share of misrepresented loans from those that had few misrepresentations.

The estimates in the next two columns confirm our results on the positive and significant relation between investor losses and second-lien misrepresen- tation within the sample of securities bought by insurance companies. This relation holds at both the pool level (column (2)) and the tranche level (col- umn (3)). Finally, the last column shows that, consistent with our overall data, AAA tranches bought by insurance companies were also adversely affected by misrepresentation.

In sum, the evidence from insurance company holdings confirms the common view that large institutional investors acquired a wide range of mortgage secu- rities prior to the crisis. We show that investors such as insurance companies likely suffered significant losses due to misrepresentation, especially on their junior tranche holdings, since they were unable to distinguish misrepresented securities from those that accurately represented collateral quality.

Were the losses on RMBS backed by misrepresented loans borne entirely by large institutional investors, such as insurance companies, and by hedge funds who invested in junior tranches? Or were some losses also borne by sellers of these securities that may have kept some of the unsold tranches backed by misrepresented collateral on their balance sheet? This is a difficult question to answer, given the lack of available data on RMBS holdings. However, evidence from anecdotes and public testimonies indicates that, prior to the crisis, sellers of mortgage securities succeeded in selling most of the RMBS tranches, includ- ing the most junior tranches (see Board of Governors of the Federal Reserve

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Table VI

Impact on RMBS Market: Which Investors Were Affected? Evidence from Holdings of Insurance Companies

This table examines a sample of RMBS tranches in our RMBS data set that were bought by insurance companies. Panel A shows the distribution of these tranches sorted by their initial rating from Standard & Poor’s along with their cumulative average losses. Column (1) of Panel B presents OLS estimates in our main sample of 333 pools from a regression in which the dependent variable is a dummy that takes the value of one if a given pool has tranches that were bought by insurance companies, and zero otherwise. Column (2) of Panel B presents OLS estimates where the dependent variable is the pool’s cumulative loss. The sample is restricted to only those pools whose tranches were bought by insurance companies (139 pools). Column (3) of Panel B presents OLS estimates where the dependent variable is the cumulative loss of tranches bought by insurance companies in the sample of 556 tranches bought by insurance companies. Column (4) of Panel B presents OLS estimates where the dependent variable is the change in the price of AAA tranches bought by insurance companies (in percentage terms) in a sample of 293 AAA-rated tranches bought by insurance companies for which Bloomberg reports these data. Percent Misreported Second corresponds to the percentage of loans in the pool having a second-lien misrepresentation (for a pool corresponding to the given tranches). Reported CLTV is the average reported CLTV of loans in the pool to investors. Other controls include the pool-level means of origination variables, such as borrowers’ FICO scores or the fraction of loans with low documentation. Data on RMBS losses, ratings, and prices come from Bloomberg (as of 2014Q1), while data on insurance companies’ holdings come from Merrill et al. ( 2014 ). The estimates are in percentage terms; standard errors are in parentheses. *p < 0.10, **p < 0.05, and ***p < 0.01.

Panel A: Distribution of RMBS Tranches Bought by Insurance Companies and Their Cumulative

Losses

Original rating Number of tranches Percent of total Average loss Aaa

Panel B: Misrepresentations and RMBS Insurance Company Holdings

Whether bought by

Losses on Price change of insurance company

Losses on

pools bought

tranches bought bought AAA

(3) (4) Percent misreported

(0.2653) (0.2031) Origination CLTV

(0.6912) (0.4511) Other controls

Yes Yes Mean

Yes

Yes

R 2 0.245

2669 System ( 2010 )). Hence, investors and not sellers were likely bearing losses due

Asset Quality Misrepresentation by Financial Intermediaries

to misrepresentation of collateral that backed RMBS.