U.S. Covered Bonds: Reassessing Credit Risk and Relative Valuations

Article Introduction

• We believe nominal spread analysis is insufficient, since investors must now consider recovery and default risk under various economic conditions.
• Our factor-based approach provides a means to quantify default probabilities across a range of outcomes instead of analyst-defined ad hoc assumptions.
• We also investigate historical CDS spreads as a means to quantify default risk relative to national home price appreciation.
• The potential for an emerging U.S. issuer market, combined with ongoing foreign issuance, leads us to believe the U.S. covered bond market has viability.

Article Main Body

In the absence of significant new non-agency mortgage-backed security (MBS) origination, banks — in particular, European financial institutions — have looked to covered bond (CB) issuance as a means to raise capital and improve liquidity. The practice has become more prevalent in recent years following the global financial crisis.

Covered bonds are securities backed by a collateral pool, or “cover pool,” typically consisting of mortgages. A covered bond has a dual recourse feature that provides the bondholder, in case of issuer default, a priority claim to the assets in the covered pool and senior claim to the issuer itself, ranking pari passu (i.e. on equal footing) with senior unsecured creditors.

The U.S. covered bond market has seen a revival since 2010 when foreign issuers opportunistically entered the market. Since then, approximately $74 billion has been issued as of January 2012, according to data compiled by Barclays, and more foreign issuers seek to tap the U.S. investor base. But the U.S. issuer covered bond market itself is almost non-existent, with just a few legacy covered bonds outstanding that were issued during the financial crisis.

In November 2011 the U.S. Covered Bond Act was introduced in the U.S. Senate by Senator Kay Hagen (D-NC) and Bob Corker (R-TN), co-sponsored by Chuck Schumer (D-NY). The bill expands on the bill introduced in the House in April 2011 but some of the outstanding issues remain unresolved, such as the FDIC’s concern about covered bondholders’ seniority over depositors, the eligible collateral appropriate for covered pools and extent of overcollateralization permitted (amassing more collateral than is necessary to obtain financing is sometimes used to improve credit ratings). If the bill finds bipartisan support in both the House and Senate, it may pass later this year. And if so, then under the current 4% bank liability limit introduced by the FDIC in 2008, the domestic covered bond market could reach $500 billion, according to a Deutsche Bank research report dated 10 January 2012. Combined with ongoing foreign issuance, we believe the U.S. covered bond market has viability.

Covered bonds versus non-agency MBS

To evaluate the risks of investing in covered bonds (CBs), we believe a bottom-up approach is required, since a covered bond risk premium consists of multiple components such as liquidity, cover pool assets cash flow valuation, seniority to unsecured holders, cross-currency basis and sovereign risk. We therefore advocate a methodology for relative valuation between covered bonds and non-agency MBS. Our proposed approach shows that increased transparency on pool collateralization can facilitate investment decisions by allowing for more informative relative value decisions across a broader set of asset classes that includes structured products and non-agency MBS in particular.

Traditional credit investors deciding whether to invest in CBs typically investigate movement in the CB’s historical basis versus nominal senior unsecured debt. Investors should also consider details on pool (over)collateralization and the possibility of recourse to the sponsor bank (issuer) in case of residual covered claims above and beyond the cover pool. In case of the latter, recourse could be junior or on a pari-passu basis with the senior unsecured debtholders. This means that investment decisions between CBs and senior unsecured debt can result from relative value views on the difference between corporate recovery rates and recovery on CB pool collateral. In practice, we have found that pool recovery estimates are based on historical performance of similar mortgage types without adjusting to forward-looking economic scenarios. Forward-looking scenario analysis is made more complicated, in part, by the revolving nature of the collateral pool, and the lack of transparency on the underlying loan characteristics.

When considering investment decisions between non-agency MBS and CBs, we believe nominal spread analysis becomes insufficient, since investors must now consider recovery and default risk under various economic conditions.

To calculate relative value or break-even analysis between CBs and MBS, we apply a factor-based approach. The attractiveness of this approach is that it provides a means to quantify default probabilities across a range of outcomes instead of analyst-defined ad hoc assumptions. For a one-factor model in non-agency MBS, arguably the single most important variable is home price appreciation (HPA). A borrower’s credit risk, as measured by a range of scores and levels of financial documentation, is an important underwriting criteria. However, as ample empirical evidence over the past decade has shown, the mortgagor’s default incentive remains directly tied to the amount of negative home equity. By extension, the CB issuer’s default probability is also impacted by home price depreciation via (i) direct primary impacts on bank portfolio retained loans and mortgage-backed securities, and through (ii) secondary effects as housing is strongly correlated to consumer and corporate credit held on banks’ balance sheets.

On the flip side to benefits, the fact remains that models are by definition simplified versions of complex financial mechanisms. As such, they are susceptible to biases on sensitivities that possibly could lead to an incorrect relative value view. Investment analysts should therefore be aware of the possibility of systematic deviation in statistical decisions and apply the appropriate adjustments.

PIMCO’s proprietary loan-level prepay and default models can be applied to non-agency MBS in conjunction with cash-flow structuring tools to model bond level valuations across a range of HPA scenarios.  Similarly, this model can be used to value collateral backing a covered bond. Without knowing the exact details on every single loan, however, general assumptions need to be imposed using the limited information that is available about vintage, product type and originated collateral performance. For issuer default, corporate default models may look to interest-coverage or capitalization ratios to estimate the amount of earnings a company generates to cover debt payments or the amount of total assets relative to total debt. Correlating these factors to home price appreciation would be challenging.

Instead, we investigate historical credit default swap (CDS) spreads as a means to quantify default risk relative to national home price appreciation. Using data from Bloomberg and Moody’s on the nation’s largest lenders since early 2000, we arrived at the statistical results with derived relationship displayed in Figure 1. Note that the shape of the surface implies larger near-term HPA shocks could have a bigger impact on cumulative default rates, which tend to be magnified over time due to the rapid deterioration of housing prices after the 2008-09 crisis and its subsequent macroeconomic impact. Through this analysis, we now have a robust set of factor-based models that allow for relative value analysis between CBs and non-agency MBS.