Intro to HEQ Market

See Disclosure Appendix A1 for the Analyst Certification and Other Disclosures.

U N I T E D S T A T E S OCTOBER 20, 2005

F I X E D I N C O M E

R E S E A R C H

Asset-Backeds and Mortgage Credit UNITED STATES

Ivan M. Gjaja (212) 816-8320 [email protected] New York

Mary E. Kane (212) 816-8409 [email protected]

New York

Marc Carnahan (212) 816-8633 [email protected] New York

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Introduction to the Home Equity Loan Market

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https://fidirect.citigroup.com/

See Disclosure Appendix A1 for the AnalystCertification and Other Disclosures.Research

U N I T E D S T A T E S OCTOBER 20, 2005

F I X E D I N C O M E

R E S E A R C H

Asset-Backeds and Mortgage Credit UNITED STATES

Ivan M. Gjaja (212) 816-8320 [email protected] New York

Mary E. Kane (212) 816-8409 [email protected]

New York

Marc Carnahan (212) 816-8633 [email protected]

New York

This report can be accessed electronically via

➤ FI Direct

➤ E-Mail

Please contact your salesperson to receive fixed-income research electronically.

Introduction to the Home Equity Loan Market




https://fidirect.citigroup.com/

October 20, 2005 Introduction to the Home Equity Loan Market

Citigroup Global Markets 4

Contents

Executive Summary ......................................................................................................................... 3

HELs in the US RMBS Market 7 The Mortgage Market in the United States ........................................................................................ 7 Securitization of Mortgage Loans ..................................................................................................... 8 HEL Market Overview ..................................................................................................................... 11

Collateral Characteristics 19 Subprime Borrower Profile — Classic Middle America .................................................................... 19 Loan Characteristics ......................................................................................................................... 19 Collateral Trends — Mainstreaming of the Subprime Borrower ........................................................ 24 Interest-Only Loans.......................................................................................................................... 26

Collateral Performance 29 Credit Performance........................................................................................................................... 29 Timing of Losses — Default Curves ................................................................................................. 31 Delinquency Roll Rates .................................................................................................................... 34 Prepayments..................................................................................................................................... 37 Main Determinants of Prepayments .................................................................................................. 41

HEL Deal Structures 46 The Senior/Subordinate Structure ..................................................................................................... 46 Cash Flows in the Senior/Subordinate Structure ................................................................................ 52 Net Interest Margin Securities (NIMS).............................................................................................. 66 Lender-Paid Mortgage Insurance — A Variation on the Senior/Subordinate Structure ....................... 68 Bond Insurance ................................................................................................................................ 72

Rating Agencies’ Methodology 73

Valuation of HEL Securities 79 Credit Risk....................................................................................................................................... 79 Prepayment Risk .............................................................................................................................. 87 Valuation of NIMS........................................................................................................................... 90

APPENDIX A — Does Conversion to REIT Status Matter to ABS Investors 94 Does Conversion to REIT Status Matter to ABS Investors?............................................................... 94

Appendix B — The Available Funds Cap 98 Cost of the Available Funds Cap — Effect of Interest Rates, Volatilities, Speeds, and Seasoning....... 98



Nonagency mortgages have been the growth engine of mortgage

securitizations during the past two years. The home equity loan

(HEL) market is the biggest portion of the nonagency market, and

by far the largest source of subordinate bonds. We provide a

comprehensive introduction to the HEL market.

HEL issuance was $412 billion in 2004, up 80% over 2003 and up 170% over 2002.

The rapid growth of the HEL market was spurred by low mortgage rates, strong home price appreciation (HPA), the shift toward higher-credit borrowers, and product innovation. A large majority of HELs are first-lien subprime mortgages (B/C mortgages), which are the focus of this report. The term “home equity loan” endures for a good reason: most HELs are taken out as cash-out refinancings.

The majority of HEL servicers today are large, well-capitalized companies.

Of the top ten servicers, eight have an investment-grade unsecured rating and market capitalizations between $8 billion and $227 billion. An increasing fraction of HEL securitizations is now being done by broker-dealers on their own shelves. Broker-dealers purchase loans in the whole loan market.

Since 2000, FICO scores have increased, while the growth of loan balances has exceeded HPA.

The subprime borrower today has a monthly income above the national median and a long tenure in his job and profession. His home is a three-bedroom, two-bathroom typical American home, valued at the national median home price. Past credit problems are the main reason why the subprime borrower is ineligible for a prime mortgage loan.

Lifetime cumulative losses on subprime deals typically reach 3% to 5%.

Many factors influence HEL losses, including the servicer performance, collateral characteristics, and the economic environment. A slowdown of home price growth, resets on hybrids, and the increasing popularity of interest-only loans heighten the credit risk going forward.

HEL prepayments are more stable than prepayments on prime mortgages, adding appeal to HEL securities.

The range of historical speeds on fixed-rate HELs is 23% CPR, versus 51% CPR for Fannie Mae loans. On the floating-rate side, the range of HEL speeds is 25% CPR, versus 38% CPR for Fannie Maes.

Today, most HEL deals have the senior/subordinate/OC structure.

Credit enhancement is provided by a combination of subordination, overcollateralization (OC), and excess spread. Currently, the initial levels of subordination and OC to the triple-A level are 23% for floating-rate loans and



20% for fixed-rate loans. Initial excess spread is about 300bp. Investors can buy securities rated triple-A through double-B, as well as net interest margin (NIM) certificates.

The standard structure includes time-tranching of cash flows and prepayment protection in the form of non-accelerated senior (NAS) bonds.

The rating agencies use detailed quantitative models to assess the credit risk in HEL transactions.

The agencies consider the level and timing of losses, prepayment curves, interest rate scenarios, and servicer quality.

Valuation of HEL securities depends on loss and prepayment expectations as well as structural details.

We highlight the key issues for fixed- and floating-rate triple-As and for subordinates.

The authors thank Elizabeth Escobar, Norma Lana, Chris Saunders, and Adela Carrazana for their able and conscientious assistance in preparing this report. Anand Omprakash contributed to many of the analyses contained in the report.



HELs in the US RMBS Market

The Mortgage Market in the United States A home is the single largest purchase most people make in their lifetimes. United States public policy has long promoted home ownership, with the initial policy enactments dating to the Great Depression. Beginning in 1938, the US Congress created government agency lenders to provide secondary markets for residential mortgages. In addition, the Federal Housing Administration (FHA) and Veteran’s Administration (VA) were created as exceptional lenders, charged with the task of facilitating home purchases by people with moderate incomes and veterans.

The government has also long endorsed home ownership through tax benefits. These include a tax deduction for mortgage interest payments and a deduction of property taxes from federal and many states’ income tax. In addition, the capital gains realized from the sale of a home are exempt from taxation under certain conditions.

Collectively, these programs have fostered a robust housing market in the United States. Residential mortgages outstanding total almost $10 trillion, more than two-and-a-half times the amount of Treasuries outstanding. (Numbers are as of the end of 2004.) The home ownership rate is currently 69%, high relative to most other industrialized countries. Spurred in part by record low interest rates, mortgage product innovations (such as hybrid mortgages, interest-only mortgages, and option adjustable-rate mortgages), and favorable government policies (the preferential tax treatment of real estate capital gains was introduced in 1997), mortgage originations have continued to grow in the past several years. They reached a record of $3.8 trillion in 2003. The second highest year on record was 2004, with $2.8 trillion of new originations (see Figure 1).

Figure 1. Residential Mortgage Originations in the US Mortgage Market, 1997–1H 05

$859

$1,450$1,310

$1,048

$2,058

$2,680

$3,760

$2,810

$1,420

0

500

1,000

1,500

2,000

2,500

3,000

3,500

$4,000

1997 1998 1999 2000 2001 2002 2003 2004 1H 05

Dolla

rs in

Bill

ions

Source: Inside Mortgage Finance.

The United States public policy has long

promoted home ownership.

Residential mortgages outstanding total almost

$10 trillion, more than two-and-a-half times the

amount of outstanding Treasuries.



Congress’ aim in creating the housing agencies was to ensure that lenders had adequate access to capital, making it possible to continue the mortgage origination process in periods of economic distress. It is believed that the creation of government agencies has lowered the cost of mortgages for most homeowners. Standardization of mortgage contracts and of credit underwriting procedures is an additional benefit of the government agencies.

The government restructured the housing finance market in 1968. It privatized the Federal National Mortgage Association (Fannie Mae), which was originally a wholly owned government corporation, and spun off the Government National Mortgage Association (Ginnie Mae) as a separate government agency that would undertake some of Fannie Mae’s previous activities. One of Ginnie Mae’s charges was to finance home loans not typically underwritten in the conventional mortgage market, such as low-income loans. Congress established the Federal Home Loan Mortgage Corporation (Freddie Mac) in 1970, through the Federal Home Loan Mortgage Corporation Act. The act’s statement of purpose describes the goals of all the agencies:

1 To provide stability in the market for residential mortgage obligations;

2 To respond appropriately to the private capital market;

3 To provide ongoing assistance to the secondary market for residential mortgages (including activities relating to low- and moderate-income families) by increasing the liquidity of mortgage investments and improving the distribution of investment capital available for residential mortgage financing, and;

4 To promote access to mortgage credit throughout the nation (including central cities, rural areas, and underserved areas).

Today, only Ginnie Mae is a true government agency whose obligations carry the full faith and credit of the US government. Fannie Mae and Freddie Mac are shareholder-owned companies. Nevertheless, Fannie Mae and Freddie Mac have explicit ties to the government, and most investors assume that their securities carry an implicit government guarantee. The president of the United States appoints members to Fannie and Freddie’s governing boards, the companies have a line of credit with the US Treasury, and they are subject to extensive political and regulatory scrutiny. Fannie Mae and Freddie Mac are overseen by the Office of the Federal Housing Enterprise Oversight (OFHEO). All mortgage-backed securities (MBS) issued by Ginnie Mae, Fannie Mae, and Freddie Mac are rated triple-A. Fannie Mae and Freddie Mac are often referred to as government-sponsored enterprises (GSEs).

Securitization of Mortgage Loans The majority of mortgages in the United States are securitized. The agencies account for the majority of securitizations, although their share of the securitizations market dropped to just 54% in 2004.

Conforming Mortgage Loans — Agency-Mortgages

Private lenders can sell mortgages that comply with the GSEs’ underwriting guidelines and loan limits to the GSEs. The underwriting guidelines are strict, ensuring that only mortgages issued to top-credit-quality borrowers are eligible for

Congress’ aim in creating the housing

agencies was to ensure that lenders had

adequate access to capital.

The housing finance market was restructured

in 1968.

The majority of mortgages in the United

States are securitized.

The agencies target the middle-income

borrower with an excellent credit history.



purchase. The loan limits are adjusted annually to keep up with changes in home prices. The current limits are about 70% higher than the national median home price, implying that the target borrower is typically the middle-income borrower. We show the current agency limits in Figure 2.

Figure 2. Agency Single-Family Mortgage Loan Limits for 2005 First Mortgage Loans One-family $359,650Two-family $460,400Three-family $556,500Four-family $691,600

Second Mortgages $179,825In Alaska, Hawaii, Guam, and the US Virgin Islands $269,725

Note: One- to four-family first mortgages in Alaska, Hawaii, Guam, and the US Virgin Islands are 50 percent higher than the limits for the rest of the country. Source: Citigroup.

Nonconforming Mortgage Loans — Nonagency Mortgages

Mortgages that are not insured by the FHA or partially guaranteed by the VA or that do not qualify for sale to Fannie Mae or Freddie Mac are nonconforming mortgages. The underwriting criteria used to originate nonconforming mortgages are less standardized than the agency criteria.

The majority of nonconforming mortgages are also securitized, but they are securitized on private label shelves. (Private-label shelves are trusts that issue MBS and are set up by mortgage originators. We discuss the structure of these vehicles in the section on HEL deal structures.) Credit enhancement of securities issued on private label shelves comes either from the structure of the deal (senior/subordinate structure), from third-party bond or mortgage insurers, or from some combination of the two. Recently, the senior/subordinate structure has been the most popular form of credit enhancement.

There are three types of nonconforming mortgages: prime jumbo loans, alternative-A (alt-A) loans, and home equity loans (HELs).

Jumbo Loans

Jumbo loans are mortgages whose balance exceeds the agency limit. They are typically issued to prime borrowers and have very low losses and correspondingly very low credit enhancements. The current enhancement level to triple-A rating is about 3% on 30-year fixed-rate jumbos and 5% on jumbo adjustable-rate mortgages (ARMs). However, the enhancement level can vary significantly between issuers.

Pools of jumbo loans have a high geographical concentration in high-cost areas, particularly in California. The California concentration often exceeds 50% in jumbo pools. Recently, jumbo ARMS have also included high concentrations of mortgage affordability products, such as interest-only and option ARMs. Borrowers holding jumbo loans refinance readily when a refinancing opportunity arises, leading to very high prepayment speeds during refinancing waves. Jumbo issuance in 2004 was $233 billion.

The majority of nonconforming

mortgages are also securitized.

Jumbo loans exceed agency limits.

Jumbos have low losses and low credit

enhancements.



Alt-A Loans

If a borrower is unable or unwilling to provide the full documentation required by the agencies, but his credit history is strong, he will qualify for an alternative-A (alt-A) loan. Such a borrower typically pays a rate premium of about 50bp over a comparable agency rate.

Although the level of documentation is a convenient starting point in the definition of alt-A loans, in reality the distinction between agency and alt-A loans is fuzzier. Various additional loan characteristics apart from documentation help distinguish agency and alt-A loans. Compared to agency pools, the alt-A pools have the following characteristics:

1 A higher proportion of investor properties;

2 A lower proportion of single-family properties;

3 Higher average loan balances;

4 Higher debt-to-income ratios; and

5 More heterogeneous pools, including a greater dispersion of loan balances and FICO scores.

Often, an alt-A loan may be eligible for purchase by the agencies, but the lender decides that a securitization on a private-label shelf gives a better all-in execution than the sale to an agency.

Alt-A loans have higher losses than jumbo loans, and correspondingly higher credit enhancements. The average credit enhancement to triple-A currently runs 5%–6% for 30-year fixed-rate mortgages and 7%–8% for ARMs. As with jumbos, there is significant variation of enhancement levels between issuers and collateral pools. Although the onset of refinancing activity is slower in alt-As than in jumbos, the peak refinancing speeds for the collateral types are similar. In addition, prepayments on alt-A loans tend to have high speeds in the absence of refinancing incentive, as borrowers correct the deficiencies that led them to take an alt-A loan and refinance it into a lower-cost loan. Alt-A issuance in 2004 was $159 billion.

HELs

The market collectively refers to the remaining nonagency loans as home equity loans (HELs). The majority of HELs are first-lien subprime mortgages, which are mortgages issued to borrowers with impaired credit histories. Other components of the HEL market include second-lien loans, reperforming loans, program exception loans, high-LTV loans, and other smaller categories. We discuss the HEL market in more detail in the next section. The 2004 issuance of HELs was $412 billion, making HELs the largest segment of the nonagency market. (Some rating agencies use the term “home equity loan” to refer only to second liens, rather than to the sector of the market we describe here. However, that definition is not consistently applied.)

Figure 3 shows the breakdown of mortgage securitizations for the past ten years.

Alt-As have higher losses than jumbos, and correspondingly higher

credit enhancements.

HELs comprise the rest of the mortgage market, with first-lien subprime mortgages claiming the

largest share.



Figure 3. Breakdown of Mortgage Securitizations 1995–1H 05

0%

20%

40%

60%

80%

100%

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005H1

0

500

1,000

1,500

2,000

2,500

$3,000

HEL Alt-A Jumbo GNMA FNMA FHLMC Issuance

Source: Inside MBS & ABS.

Reasons for the GSE Pullback

For the past ten years, agency issuance has typically accounted for more than 75% of all mortgage securitizations. However, in 2004, agency securitizations dropped to only 54% of the total securitized volume of $1.9 trillion. Several reasons account for the relative decline of agency issuance:

1 The GSEs have traditionally been less competitive in hybrid products, which have been the growth engine of the nonagency market.

2 The GSEs have also taken a very cautious approach in interest-only (IO) and negative amortization (NegAm) loans, which now account for the majority of prime nonagency hybrid issuance.

3 Execution of senior/sub deals in the secondary market has been excellent throughout 2004, offering an alternative to selling loans to the agencies.

4 Lenders have become very sophisticated about pricing credit risk, segmenting the market, and drawing borrowers away from government-subsidized loans offered by Ginnie Mae.

5 Accounting issues have forced Fannie Mae to shrink its retained portfolio. In addition, Congress is currently discussing legislation to cap the portfolios of both GSEs, limiting the appeal of aggressive growth at Freddie Mac.

6 A slowdown of refinancings in 2004 has hit agency issuance harder than some of the nonagency sectors, such as subprime mortgages. Prepayments on subprime mortgages are less sensitive to interest rate shifts than prepayments on prime mortgages.

HEL Market Overview The HEL sector has evolved over time. It started out as a small secondary market for second liens and first-lien deeply subprime mortgages. In the early 1990s the loan balances were often less than $40,000 and interest rates often topped 13%. The sector has changed dramatically since that time. Today HELs are the largest nonagency MBS sector. Most of the securitized HELs are first-lien mortgages issued

The market share of nonagencies has grown

sharply.

The majority of HELs are first-lien mortgages

taken out by economically able

borrowers.



to borrowers who have had credit problems in the past, but whose economic standing closely mirrors that of the average American homeowner. The term home equity loan endures for a good reason: the majority of securitized HELs are taken out as cash-out refinancings.

HEL Sectors

The HEL market consists of the following subsectors:

First-Lien Subprime Loans

The lender takes a perfected first mortgage security interest on the property. HEL obligors have a 20%–25% equity in the property and select repayment terms of up to 30 years. The interest on the mortgage can be fixed or floating. The interest rate exceeds the interest rate available under agency programs, because the borrower’s credit is impaired. First-liens now comprise more than 80% of HEL securitizations. This segment of the HEL market is sometimes referred to as the residential B/C market. In this primer, we only review first-lien HELs.

Second Liens

Second-lien mortgages include amortizing closed-end loans and home equity lines of credit (HELOC). The second lien has a perfected security interest in the property, but it is junior to the first mortgage lien. The credit profile of securitized second liens is stronger than the credit profile of first liens and includes fully prime borrowers. Second liens can be taken out at the same time as the first lien, for the purpose of purchasing a home with little down payment, or they can be taken out separately, to refinance credit card debt, student loans, finance home improvements, etc. Second liens are about 10% of HEL securitizations.

High Loan-to-Value Mortgages

Some lenders make loans that exceed the value of the property (called high-loan-to-value, or HLTV loans). These loans, which can be either first lien or second lien, generally do not exceed 125% of the property’s appraised value. The interest on the amount of the mortgage that exceeds the property value is not tax deductible. In addition, these assets are generally treated as unsecured investments by regulators for capital purposes.

First-lien HLTVs have a typical LTV of 102%–103%, while second-lien HLTVs have a typical combined LTV of 110%–115%. First-lien HLTVs are issued for home purchase with no down payment. The amount in excess of 100% finances the closing costs. Second-lien HLTVs are primarily consumer loans. The borrowers taking out first- and second-lien HLTVs have much stronger credit profiles than the borrowers taking out low-LTV first-lien subprime loans. HLTVs have declined in popularity, and today they are a small percentage of HEL securitizations.

Scratch and Dent

The “scratch and dent” term encompasses a variety of loans. Most of them are loans that do not fall into the underwriting categories of lenders, but have some additional features that make them reasonable credit risks. For example, the borrower’s debt-to-income ratio may be too high, but the combination of disposable income and LTV make the loan attractive. These loans are also called “program exceptions.”



Other, less common reasons for loans to be classified as scratch-and-dent include the following: (1) the loans have been declined or removed from sale to a third-party purchaser; (2) they are delinquent loans (not in bankruptcy or forbearance) up to three-months past due; (3) the loans are in bankruptcy; (4) the loans had prior multiple delinquencies that are now cured; and (5) the loans are subject to certain appraisal, property, credit documentation, underwriting compliance, and/or other deficiencies.

Reperforming Loans

Reperforming mortgages include the following categories: (1) rewritten loans where the prior loan may have been in default and the new loan was originated in a workout situation; (2) loans where the original loan terms have been modified pursuant to the Servicemembers Relief Act of 1940 (Relief Act loans); and (3) modified loans where the original loan terms have been subject to a material modification pursuant to a written agreement.

Summary of HEL Servicers/Issuers

The issuer and servicer landscape in the HEL market has changed dramatically since the liquidity crisis of 1998. Large mortgage lenders or units of diversified financial services companies have replaced the small specialty finance companies of the 1990s. This should add staying power to the market in case of an economic downturn, as well as rigor to the underwriting process. The key issuer-related developments of the past five years include the following:

➤ A move away from small specialty finance companies to large mortgage lenders and diversified financial service companies. In addition to being better capitalized, the current securitizers rely less, if at all, on gain-on-sale accounting as a core of their earnings.

➤ The ability of issuers to efficiently monetize a portion of the residuals through net interest margin certificates (NIMS). Sales of NIMS are now an important component of HEL transactions.

➤ A vast increase in whole loan (WL) purchases by broker dealers who generally securitize the loans on their own shelves and retain the back-end residuals (first loss pieces).

➤ An increase in the sophistication of all market participants — from lenders to the underwriters to the rating agencies to investors. All of these participants now have access to quantitative models that analyze extensive historical data to estimate credit and prepayment risks.

➤ Opportunities to tap a growing investor base that includes new participants among traditional investor groups, such as insurance companies and money managers, and new classes of investors, such as CDO managers, hedge funds, and offshore investors.

➤ The increasing popularity of the Real Estate Investment Trust (REIT) tax structure among frequent issuers. The ranks of REITS now include New Century, Saxon, NovaStar, Aames, Origen, and Bimini/Opteum (pending). The REIT structure does not have a direct legal impact on HEL investors, but it raises some other questions, which we discuss in detail in Appendix A.

Today’s HEL issuers are large mortgage lenders or diversified financial

service companies.



Figure 4 shows the ten largest HEL issuers in 2004 and the first nine months of 2005, while Figure 5 shows the 25 largest HEL servicers.

Figure 4. Ten Largest HEL Issuers — 2004 and First Nine Months of 2005 (Dollars in Billions)

2004 2005

Volume Market Share Volume Market ShareIssuer ($) (%) Issuer ($) (%)

Ameriquest Mortgage 55.1 14 Ameriquest Mortgage 32.0 10Countrywide Financial 40.6 10 Lehman Brothers 28.2 9Lehman Brothers 27.3 7 Countrywide Financial 23.8 7GMAC-RFC 26.0 7 Morgan Stanley 20.0 6New Century 22.3 6 GMAC-RFC 16.3 5First Franklin 19.5 5 CS First Boston 15.5 5CS First Boston 18.2 5 Citigroup 13.8 4Option One 17.5 4 New Century 13.6 4Fremont Investment 15.3 4 Washington Mutual/Long Beach 11.4 4Washington Mutual/Long Beach 13.9 4 Deutsche Bank 11.1 3

Source: Inside MBS & ABS.



Figure 5. Portfolio and Corporate Fundamentals of the Largest Subprime Servicers (Dollars in Billions)

Subprime Primary Moody’s/S& P/Fitch Ratings

Servicing Yrs in Market Long-Term Special Master TK Portf. ($B) Business Capitalization Parent Company Auditor Debt Servicers Servicers Servicers Countrywide Financial

CFC 108.8 35 19 Countrywide Home Loans

KPMG LLP A3/A/A SQ1/Strong/ RPS1

SQ1/Strong /RSS1

RMS2+

Ameriquest Private 76.6 24 NA NA Ernst & Young NA SQ2/Strong/ RPS2

RSS2- NA

Option One HRB 70.8 12 8 H&R Block KPMG LLP BBB+ SQ1/Strong/ RPS1

SQ2/Avg/ RSS1

NA

CitiFinancial C 54.1 92 227 Citigroup KPMG LLP Aa1/AA-/AA+ Avg/RPS2 NA NA Chase JPM 53.0 127 119 JP Morgan

Chase Price Waterhouse

Aa3/A+/A+ SQ1/Strong/ RPS1

RSS1 RMS1-

Home Equity WB 50.7 13 75 Wachovia KPMG LLP Aa3/A/A+ SQ1/Strong/ RPS1

Strong/ RSS1

NA

Homecomings GM 49.0 22 17 GMAC Deloitte & Touche

Baa1/BBB-/ BBB

SQ2/Strong/ RPS1

SQ2/RSS1 NA

Wells Fargo WFC 39.0 152 100 Wells Fargo & Company

KPMG LLP Aa1/AA-/AA SQ1/Strong/ RPS1

NA Strong/ RMS1

Ocwen OCN 37.8 16 0.4 Ocwen Financial Corp.

Price Waterhouse

B1/B SQ2/Strong/ RPS2

SQ2/Strong /RSS2

NA

Household HBC 36.9 126 177 HSBC KPMG LLP A1/A/A+ n/a NA NA EMC BSC 36.0 15 15 Bear Stearns Deloitte &

Touche WR/BBB SQ1/Abv

Avg/RPS1 SQ2+/Abv Avg/RSS1

NA

Litton RDN/PMI 33.4 16 4/4 Radian/PMI Deloitte & Touche/Ernst & Young

A2/A/A1/A+ SQ1/Strong/ RPS1

SQ1/Strong/ RSS1

NA

Washington Mutual

WM 33.4 115 38 Washington Mutual Inc.

Deloitte & Touche

A3/A-/A RPS2 NA RMS2+

New Century (R) NEW 31.2 9 2 New Century Financial

KPMG LLP B1/BB Avg/RPS3 NA NA

First Franklin NCC 27.9 23 21 Nat’l City Bank of Cleveland

Ernst & Young A1/A/AA- RPS2- RSS3+ NA

Saxon Mortgage (R) SAX 24.7 16 0.5 Saxon Capital Inc.

Deloitte & Touche

NA SQ2/RPS2+ SQ3/RSS2- NA

Fremont General FMT 21.0 33 2 Fremont General Corp

Ernst & Young B3/CCC+/ CCC+

RPS3- NA NA

American General Finance

AIG 18.0 84 164 American Intl. Group

Price Waterhouse

Aaa/AAA/AAA NA NA NA

Select Portfolio Servicing

CSR 17.0 149 53 Credit Suisse KMPG LLP NA SQ3/Average/ RPS3-

SQ3/Average /RSS3

NA

NovaStar (R) NFI 13.6 8 0.9 NovaStar Financial Inc.

Tohmatsu NA SQ2/Strong/ RPS3+

Average NA

Wilshire MER 10.5 10 57 Merrill Lynch Deloitte & Touche

Aa3/A+/AA- SQ2/Abv Avg/RPS2+

SQ2/Abv Avg/RSS2+

NA

Centex CTX 10.0 54 8 Centex Corporation

Ernst & Young Baa2/BBB/ BBB+

Abv Avg/ RPS2+

NA NA

Equity one BPOP 8.7 112 6 Popular Inc. Price Waterhouse

A3/BBB+/A SQ2-/Above Avg/RPS3-

NA NA

Acc. Home Lenders LEND 8.3 15 0.7 Acc. Home Lenders Corp.

Grant Thornton NA SQ2/RPS3- NA NA

Aames (R) AIC 4.5 14 0.4 Aames Inv. Corp

Ernst & Young NA SQ3/RPS3- NA NA

As of October 17, 2005. (R) REIT NA Not Available. Sources: Inside B&C Lending, Bloomberg, Moody’s, Standards & Poor’s, and Fitch.

One of the most striking features of Figure 5 is the corporate strength of the top subprime servicers. Of the top ten servicers, eight have an investment-grade rating on unsecured debt, only one is rated below investment grade, and one is privately held and has no unsecured rating. (We show the rating of the servicer’s parent company.) The market capitalization of the investment-grade servicers ranges from $8 billion to $227 billion.

Of the top ten servicers, eight are rated

investment grade. Their market caps range from $8 billion to $227 billion.



Even if we extend the list of subprime servicers to the top 25 portfolios, the picture of solid fundamentals remains. Sixteen servicers hold an investment-grade unsecured rating, six do not carry a credit rating, and only three are rated below investment grade. Sixteen of the servicers on the list have a market capitalization of $6 billion or more. The strength of the corporate parent’s balance sheet is not by itself a guarantee of the quality of servicing or the staying power in the subprime market, as the experiences of Bank of America, First Union, and GE have shown. However, a strong balance sheet implies that a company will be less likely to impair its servicing operation to conserve cash in a downturn of the mortgage market.

The rating agencies’ servicer ratings are not available for all large subprime servicers. In some cases the servicing has not been rated, while in others the servicer has requested that the rating not be made public. Nevertheless, the ratings shown in Figure 5 are generally strong. With the exception of Aames and Select Portfolio Servicing, which have suffered several rating actions as a result of regulatory issues, the lowest Moody’s rating for a primary servicer is SQ2, on a scale of SQ1 (highest) to SQ5 (lowest). The lowest S&P rating is Average (Strong/Above Average/Average/Below Average/Weak). One servicer (Wilshire) has a primary servicer Fitch rating of RPS2+; for the others, the lowest Fitch rating is RPS3- (RPS1 is the highest, RPS5 the lowest). The available servicer ratings for special servicing are also high, supporting the view that the large subprime servicers are experienced in the handling of all delinquency stages of the subprime loan.

Definition of Primary, Special, and Master Servicing

In most cases, the primary, special, and master servicers are part of the same corporate entity. However, the splitting off of special servicing is becoming more widespread.

➤ Primary loan servicing refers to the management of loan cash flows, including communication with the borrower, loan reporting, and the management of initial delinquencies.

➤ Special servicing refers to the servicing of severely delinquent loans, including foreclosure, and the subsequent management and sale of repossessed properties.

➤ The Master servicer oversees the performance of primary and special servicers, manages the servicing portfolio, and advances interest and principal on nonperforming loans. If either servicer is unable to meet its obligations, the master servicer takes over the servicing of the loan portfolio and therefore serves as the ultimate guarantor of the servicing operation.

Business Models of HEL Originators

HEL originators have several options to fund the loans.

1 They can retain the loans on their balance sheet and fund them through corporate borrowing or funds from the parent company;

2 They can securitize them; and

3 They can sell them as whole loans.

The funding mechanisms are summarized in Figure 6. Many originators combine several funding strategies. For example, New Century sells mortgage loans to broker dealers and also securitizes them on its own NCHET shelf. For the past several

All but two of the servicers with a Moody’s primary servicing rating

are rated SQ1 or SQ2.

HEL originators can fund the loans on the balance

sheet, through securitizations, or through WL sales.



quarters the securitization rate on subprime first liens has been between 60% and 65%, implying that most of the loans are securitized. However, many of the largest lenders, especially the money center banks, prefer to hold the loans on their balance sheets.

Figure 6. Business Models of HEL Originators Off-Balance Sheet Financing

On-Balance Sheet Financing Par Proceeds NIMS Proceeds Whole Loan Sale

Financing Process Issue commercial paper or MTNs. Repurchase/warehouse lines. Syndicated bank lines Obtain funding from parent.

Structure deal and issue LIBOR floaters or fixed rate notes. Book residual non-investment grade bonds on balance sheet. Book gain on sale.

Structure deal and issue either fixed or floating rate certificates or notes. Structure and sell front-end residual as NIMS.

Sell assets to obtain above par execution. Depending on issuer, sale is either servicing retained or servicing released.

Servicing Retained Servicing Released

Sample Issuer Wells Fargo Financial Centex Ameriquest Option One New Century

Source: Citigroup.

If the originator sells WLs, he can either retain the servicing rights or sell them. Servicers generally charge 50bp per loan per year, which makes servicing a profitable business. Servicing operations add stability of earnings to WL sales and securitizations.

HEL Production Channels

HEL lenders originate the product in three ways: retail, correspondent, and broker network. Most lenders employ a combination of the methods. For the investor, the origination channel is relevant because it affects the performance of the loan. Loans from brokers and correspondents tend to prepay faster. In addition, investors typically scrutinize the re-underwriting practices of HEL issuers to ensure that bulk purchases do not result in lower credit quality of the loans.

Retail originators work directly with the borrower, either through retail branches or calling centers. Many customers are referred to the lender through affiliates, such as credit card companies, insurers, or related mortgage lenders. Retail originations are more expensive than the other origination channels, but they provide the lender with points and loan origination fees, which are significant sources of income. (We discuss points and fees in the next section.) In addition, retail originations provide an opportunity for best loan selection and pricing.

Correspondent lenders (correspondents) are banks and finance companies that are typically too small or regionalized to warrant retaining and servicing the loans. Correspondents sell their originations to larger lenders in packages. Most final lenders re-underwrite the correspondent loans to make sure they meet the lender’s credit criteria.

Mortgage brokers match borrowers with mortgage lenders. They act as an intermediary, trying to get the best match between the borrower and the lender. Brokers typically offer a loan to several lenders and act on the most competitive offer. The lenders, in turn, underwrite each loan before offering the loan terms. Broker channels have consistently dominated subprime loan production, as shown in Figure 7. In 2004 they accounted for more than 50% of subprime originations.

HEL servicing is profitable.

HEL lenders originate the product through

retail branches, correspondents, and

brokers.



Figure 7. 2004 HEL Mortgage Origination Sources Production Channel Description 2000 2001 2002 2003 2004Retail (%) Direct to consumer 36 39 34 34 28Broker (%) Intermediate between borrower and lender 34 41 45 48 52Correspondent (%) Sells to lender/servicer 30 20 21 18 20

Source: Citigroup.



Collateral Characteristics

Subprime Borrower Profile — Classic Middle America The typical borrower has a stable employment history, with a long tenure in his job and profession. The home is generally a single-family dwelling typical of an average American home — 1,713 square feet, 3.3 bedrooms, and 1.8 bathrooms. The average home price is $215,000, which is nearly identical to the national median of $219,000.1 HEL borrowers’ incomes are above the median US household income, which was $4,600 per month in the fourth quarter of 2004.2

These collective borrower traits offer a picture of economically stable consumers with a home that has benefited from the strong housing market in the United States, but is probably not located in one of the highest growth areas. (Regions with the strongest home price appreciation (HPA) tend to have prices above the national median.) Figure 8 summarizes the HEL borrower profile, based on the blended reports for several large lenders.

Figure 8. Subprime Borrower Profile Characteristics DetailAge 43 yearsMonthly Income $5,780Time in Property 7 yearsTime in Job 8 yearsTime in Profession 11 yearsProperty Type 84% single-familyYear Built 1960Size 1,713 sq. ft.No. of bedrooms 3.3No. of bathrooms 1.8Property value $215,000

Source: Citigroup.

Loan Characteristics

Fixed-Rate Versus Floating-Rate Originations

First-lien subprime mortgages are issued either as fixed-rate or adjustable-rate mortgages (ARMs). The loan terms on fixed-rate mortgages can be either 15 years or 30 years, while the loan terms on ARMs are almost always 30 years. The historical range of floating-rate versus fixed-rate loans is 55% to 80%. Currently, 80% of the securitized loans are ARMs, which is at the high end.

Several factors contribute to the prevalence of ARMs in subprime pools, including the following:

1 Secondary market execution is currently better for floating-rate securities, which are mostly backed by ARMs;

1 As of August 2005. Source: National Association of Realtors.

2 Source: US Bureau of Census.

The typical borrower has a stable employment

history, and the home is an average American

home.

Currently, 80% of first-lien subprime loans

are ARMs.



2 ARMs that reset after two or three years are a natural product for subprime borrowers, because many of them refinance after that time. They refinance because their credit profile has improved and they have become eligible for better loan terms or because they want to monetize the equity that has accumulated in their home.

3 A loan that resets after two or three years offers a lower interest rate than a fixed-rate loan. Borrowers in high-cost areas have been seeking ARMs as a means of lowering their monthly payments;

4 Interest-only (IO) loans, which are a growth area of the subprime mortgage market, are available only as ARMs. This choice makes sense because borrowers typically take IOs to lower their monthly payments and ARMs already offer lower monthly payments than fixed-rate loans.

Almost all ARMs are hybrids. The interest rate is fixed for either two years or three years. (These loans are called 2/28s and 3/27s, respectively). After the fixed-rate period, the loans reset every six months, indexed to six-month LIBOR. The typical margin over six-month LIBOR is 550bp–650bp. Both the first reset and the subsequent resets are subject to a maximum increase in interest rates. These are called the initial cap and the periodic cap. The most common initial cap is 300bp. The most common periodic cap is 100bp.

Fees, Points, and Predatory Lending Laws

The borrower pays various administrative, legal, and lender-imposed fees to close the loan. In addition, he may pay points. A point is an upfront fee of 1% of the loan amount, paid in exchange for a reduction of the interest rate. Points are typically financed. The exact points and fees on each loan are generally not disclosed to the participants in the securitization market, including WL buyers, trustees, underwriters, and investors. Based on partial information, points and fees typically run 3%–3.5% of the loan balance and are effectively capped at 5%.

Almost all lenders avoid charging points and fees that would classify the loan as a high-cost loan. High-cost loans carry many restrictions on refinancings and require additional disclosures. In addition, high-cost loans may be subject to predatory lending laws in many states. Some states have predatory lending laws that affect all loans, not only high-cost loans. However, the brunt of the legal scrutiny is borne by high-cost loans.

The predatory lending laws of a few states include liability that can be carried over to the trust issuing MBS (assignee liability). Generally, the cases of assignee liability are narrow and well defined; the rating agencies are vigilant about taking them into account when assigning credit ratings to the securities.

Under the Federal Home Owners Equity Protection Act (HOEPA), a loan is designated as a high-cost loan if the sum of points and fees exceeds 8% of the loan amount or the coupon on the loan exceeds the rate for a comparable Treasury security by 8% or more. Some states have stricter laws, which cap the points and fees at 5% of the loan amount. GSEs also cap the points and fees of the loans they purchase at 5%. For the majority of first-lien subprime loans, the fees and points are effectively capped at 5%.

Almost all ARMs are hybrids.

Fees and points are a few percent of loan

balance and are effectively capped at 5%.

Lenders avoid charging points and fees that

would classify the loan as a high-cost loan.

Some state laws include assignee liability.

Under HEOPA, a loan is a high-cost loan if the

points and fees exceed 8% or the coupon

exceeds Treasuries by 8%.



Loans Summarized

First-lien subprime loans are mostly taken as cash-out refinancings (56% of floating-rate loans and 72% of fixed-rate loans). The cash-out refinancing means that the borrower refinanced an existing loan with a loan that has a larger principal balance. The extra cash is used for home improvements, paying off consumer debt (including credit card debt, automobile loans, and student loans), medical expenses, and other general consumer purposes.

Other salient features of subprime loans include the following:

➤ Virtually all floating-rate subprime loans are hybrids. The fixed-rate term is either two years (80%) or three years (20%), after which the loans reset every six months, indexed to six-month LIBOR. Initial resets of 12 months or less were common in 1998 and 1999 (24% and 7% of originations, respectively), but have disappeared since that time.

➤ Over 92% of the loans are taken out on borrower-occupied properties. There are very few investor properties in subprime pools.

➤ More than three quarters of the loans are backed by single-family properties.

➤ For the majority of subprime loans (60% of floating-rate and 72% of fixed-rate) the borrower has submitted full documentation, which typically includes two years of income tax returns, pay stubs with verification of employment, and a full documentation of assets.

➤ The majority of loans carry prepayment penalties. Prepayment penalties add to the stability of prepayments and contribute important cash flows to the NIMS, as we discuss later in this report. The amount of penalty varies, though the most common penalty is six months’ interest on 80% of the unpaid principal balance. About half of hybrids have two-year penalties, 20% have three-year penalties, and 30% have no penalties.

Therefore, the typical subprime loan is clearly differentiated from the other nonprime nonagency category, the alt-A loan. Alt-A loans have higher credit scores and higher loan balances, but also include significantly higher concentrations of investor borrowers and loans with limited documentation. Figure 9 shows the cross section of first-lien subprime loans securitized in the past 12 months. (We show the largest loan groups within each collateral characteristic. The percentages may not add up to 100%.)

Most first-lien subprime loans are cash-out

refinancings.



Figure 9. Collateral Cross Section of Floating- and Fixed-Rate HELs Securitized in the Last 12 Months Floating (%) Fixed (%)Percent of Originations 80 20Average Loan Balance $183,000 $155,000 WAC 7.12 7.05Margin over Six-Month LIBOR 5.97 NAInitial Cap 2.30 NAPeriodic Cap 1.20 NALifetime Interest Rate Cap 13.55 NALifetime Interest Rate Floor 6.71 NAFirst Reset NA Two Years 77 Three Years 20 Penalty Term No Penalty 29 26 Two Years 47 3 Three Years 20 55California Concentration a 32 28Loan Purpose Purchase 40 19 Equity Takeout 54 71 Rate/Term Refi 6 10Owner Occupancy 94 92Documentation Full 60 72 Limited 40 28 None 0 0FICO 619 642LTV 82 77Known Seconds 19 6Combined LTV when 2nd lien present 97 95Debt-to-Income 41 39a No other state exceeds 10%. Sources: LoanPerformance and Citigroup.

Fixed- Versus Floating-Rate Loans, Piggyback Seconds, and Alt-Bs

Figure 9 shows that fixed-rate loans have lower balances, higher FICO scores, and lower LTVs than ARMs. They are less likely to be purchase loans and are less likely to be taken in conjunction with second liens (piggyback seconds). The debt-to-income ratio is lower, even though ARMs are now underwritten to the initial monthly payment and the ARM interest rate is lower. Overall, the comparison implies that ARMs carry slightly more credit risk than the fixed-rate mortgages. This is reflected in the credit enhancement levels, as we will discuss.

Piggyback seconds are second liens taken out at the same time as the first lien, for the purpose of buying a home. The borrower puts down a very small down payment on the property. Instead of obtaining one loan with an LTV in excess of 95%, which may be costly and require mortgage insurance, the borrower takes out a first lien for about 80% LTV and a second lien for the remainder of the cost. The presence of the second lien does not affect the legal priority of the first lien in case of borrower default.

The loan balances and FICO scores we show in Figure 9 have a wide distribution of values. Floating-rate loan balances range from about $80,000 to $280,000 and fixed-rate loan balances range from about $65,000 to $250,000. Although there is no firm cutoff on FICO scores, the proportion of pools with FICOs less than 550 is now typically less than 10%. On the upper end, however, the FICO band has expanded, especially on the fixed-rate side. Fully one quarter of the securitized fixed-rate loans

Fixed-rate loans have lower balances, higher

FICO scores, lower LTVs, and fewer piggyback seconds than ARMs.

Piggyback seconds are taken out at the same

time as the first lien to facilitate home purchase.

Loan balances and FICO scores have wide

distributions.



now have FICOs at or above 685. These loans, which typically carry LTVs in excess of 85%, are often referred to as alt-B collateral.

Teaser Rates

At the beginning of 2005, subprime hybrids were being originated with a WAC of 7.12% and a margin of about 600bp over six-month LIBOR. As six-month LIBOR was 3.16% in February 2005, this means that the fully indexed rate on the loans was more than 200bp over the initial coupon. The low initial rate that is in effect until the first reset is called the teaser rate.

In addition to being the reference rate for loan coupons, six-month LIBOR is a proxy for the cost of funding for HEL issuers that securitize. All floating-rate HEL bonds are indexed to one-month LIBOR, whose movements are very closely correlated with the movements of six-month LIBOR. Changes of spread on HEL securities are an important adjustment to this calculation of the cost of funding. We take this into account in the calculation of excess spread later in this paper (Figure 36).

In the past one-and-a-half years, the spread between the fully indexed rate and the teaser rate has increased steeply. Based on average industry numbers, teasing increased from -70bp to about 260bp. Figure 10 shows the pattern. Even as six-month LIBOR rose between April 2004 and July 2005 by about 270bp, the initial WACs on 2/28 hybrids dropped by about 80bp. The aggressive pricing of new loans relative to the cost of funding is a sign of competition in the subprime industry. It translates into thinner profit margins per loan for the lenders and excellent funding opportunities for the borrowers. In the past two months, many lenders have begun to raise rates, slowing or reversing the increase in the teasing spread.

Figure 10. Initial WAC on 2/28s, Six-Month LIBOR, and the Teasing Spread, Jan 04–Jul 05

0

1

2

3

4

5

6

7

8

9

Jan 04 Mar 04 Jun 04 Sep 04 Dec 04 Mar 05 Jun 05

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

WAC 6M LIBOR Teaser (Right Axis)

Source: Citigroup.

The increase in rate teasing with a flattening of the swap curve is not new. In past flattening and steepening cycles, the initial WACs on the loans lagged the changes in the short rate, leading to a ballooning and compression of the teasing spread. However, the magnitude of the recent increase in teasing spread is unprecedented. Between June 2001 and January 2003, the spread has ranged between +100bp and -100bp.

The initial WACs on HEL hybrids are often lower

than the fully indexed rate.

In the past one-and-a-half years the teasing spread has increased

steeply.

The teasing spread typically increases when

the curve flattens.



Collateral Trends — Mainstreaming of the Subprime Borrower The abundance of HEL ABS supply in the past three years has made the market anxious about possible erosion of HEL credit quality. In fact, collateral credit quality has been improving since 2000. FICO scores and loan balances increased significantly, implying a mainstreaming of the subprime borrower. The deeply subprime borrower of the late-1990s has been replaced by the average American homeowner who has had credit problems in his past, such as late payments on his mortgage, credit card, or automobile loans.

FICO and LTV

Collateral varies according to the issuer and loan product, but in general, the borrower credit has been on an upswing since 2000. Between the first quarter of 2000 and the first quarter of 2005, the average FICO score of subprime fixed-rate loans increased from 603 to 635, while the average FICO score of subprime ARMs increased from 601 to 624. The left graph of Figure 11 shows the average FICO scores of S&P-rated HEL deals from the first quarter of 2000 through the first quarter of 2005.

FICO scores increased, but the LTVs on subprime loans increased as well. The right graph in Figure 11 shows the average LTVs of HEL deals rated by S&P between the first quarter of 2000 and the first quarter of 2005. The average LTV increased 3% on fixed-rate loans and 2% on floating-rate loans. Although noticeable, this increase in LTV does not offset the improvement in credit performance brought about by higher FICO scores.3

Figure 11. Average FICOs and LTVs of S&P Rated Transactions LTV 1Q 00–1Q 05

580

600

620

640

Mar 00 Mar 01 Mar 02 Mar 03 Mar 04 Mar 05

FICO

Fixed Floating

10

20

30


LTV

(%)

Fixed Floating

Sources: S&P and Citigroup.

3 See Delinquency Transitions in Subprime Loans, Citigroup, March 17, 2004, The RAMP-RS Program Explained, Citigroup

December 16, 2003, and Fixed-Rate Loans in RASC-KS Deals, Citigroup September 20, 2002, for estimates of the relative importance for defaults of various collateral characteristics.

Collateral quality has improved from early

2000. FICO gains outweigh minor LTV

increases.



Loan Balance and Debt-to-Income

HEL loan balances have increased sharply since 2000, exceeding HPA. The average loan balance of fixed-rate HELs increased by 84% through the fourth quarter of 2004, while the average balance of HEL ARMs increased by 57%. By comparison, HPA amounted to 46% over this period, indicating a shift of the subprime lenders toward wealthier and more credit-worthy borrowers. Debt-to-income ratios have also increased since 2000, though modestly. Much of the pickup in debt-to-income ratios came in 2004, amid increasing competition among lenders, the decision by borrowers to stretch further and purchase increasingly expensive homes, and the introduction of IO loans. IOs carry higher debt-to-income ratios, as we discuss in the next section. Figure 12 shows the trends in HEL loan balances and debt-to-income ratios.

Figure 12. Average Loan Balance and Debt-to-Income Ratios of Subprime Loans, 1Q 00–1Q 05

60,000

80,000

100,000

120,000

140,000

160,000

180,000

$200,000


Aver

age

Loan

Bal

ance

Fixed Floating

34

36

38

40

42


DTI (

%)

Fixed Floating

Sources: LoanPerformance and Citigroup.

Prepayment Penalties and Documentation

The percentage of HELs with prepayment penalties has remained between 65% and 80% since 1998. However, the distribution of penalty terms has shifted away from five-year penalties. Few fixed-rate loans and virtually no floating-rate loans today carry the five-year penalty. Among ARMs, the shortening of the penalty term was driven by concerns that the penalty term that exceeds the fixed-rate term of the loan could be viewed as predatory. Today, for the majority of ARMs the penalty term coincides with the time to first reset. The disappearance of the five-year penalty on fixed-rate loans follows the pattern of making the loans more borrower-friendly. In part, this is a consequence of the shift toward a higher borrower credit. Predatory lending issues are also a consideration.

Today, the most common penalty term on AMRs is two years (47% of originations). The most common penalty terms on fixed-rates is three years (49% of loans). Figure 13 shows the penetration of prepayment penalties on fixed- and floating-rate HELs.

HEL loan balances have increased sharply since

2000, exceeding HPA.

For the majority of floating-rate loans

today the penalty term coincides with the

fixed-rate term.



Figure 13. Prepayment Penalties in HEL Deals, 2000–2004 Floating Fixed

0%

20%

40%

60%

80%

100%

2000 2001 2002 2003 2004

Perc

ent o

f Loa

ns (%

)

No penalty 1 2 3 5

0%

20%

40%

60%

80%

100%

2000 2001 2002 2003 2004

Perc

ent o

f Loa

ns (%

)

No penalty 1 2 3 5

Source: Citigroup.

Full documentation loans dropped from about 70% of ARM originations in 2000 to about 60% today. Apart from competition, this shift suggests that subprime lenders are starting to target higher-credit, reduced documentation loans, which are common in the alt-A market. The percentage of fixed-rate loans with full documentation decreased from about 80% in 2000 to about 70% today.

Interest-Only Loans The growth of IO loans in the HEL market in the past two years has received a lot of attention. For the past 12 months, IOs accounted for 21% of HEL ARMs, up from virtually zero in 2002. Almost all HEL IOs are floating-rate loans. The IO period typically lasts between two and five years, after which the loan starts amortizing according to the 28-, 27-, or 25-year schedule. Figure 14 shows the penetration of IOs in subprime hybrid pools. We also show piggyback seconds, which occur more frequently with IOs than with amortizing loans.

Figure 14. Growth of IOs and Piggyback Seconds in Securitized Subprime Pools, 1Q 01–1Q 05

0%

10%

20%

30%

Mar 00 Sep 00 Mar 01 Sep 01 Mar 02 Sep 02 Mar 03 Sep 03 Mar 04 Sep 04 Mar 05

Perc

ent o

f Orig

inat

ions

(%)

Piggyback Seconds IOs

Source: Citigroup.

Full documentation ARMs have decreased

from 70% of originations in 2000 to 60% today.

For the past 12 months IOs accounted for 21% of

HEL ARMs.



Apart from the amortization schedule, the IOs are notably different from amortizing loans. Some of their characteristics increase the credit risk, while others mitigate it. Additional credit risks include the following:

➤ A higher payment shock as a result of resets or the beginning of amortization. Although the largest bucket of IO terms is five years (45% of originations), almost a third of the IOs begin amortizing after two years. For the majority of these loans, the increase in payments due to amortization coincides with the increase in payments due to coupon resets. The current origination trend is toward the extension of IO terms to five years.

➤ A higher debt-to-income ratio on IOs (42% versus 40% for amortizing loans). This difference increases after the IOs start resetting or amortizing.

➤ A significantly higher proportion of known second liens (38% versus 14%). The true risk of second liens becomes apparent when viewed against the combined LTV. With an average combined LTV of 98%, the borrower has very little equity in the property.

➤ A higher California concentration (56% versus 26%). In general, any regional concentration increases credit risk. The realistic possibility that the California housing market may underperform the rest of the country over the next several years increases the risk.

We do not view the absence of equity buildup during a two- to five-year period as a significant credit risk in itself. In fact, an amortizing 30-year loan builds up only about 1% of equity per year. This equity buildup is easily overshadowed by home price growth or decline.

IO credit risks are offset by the following loan and deal features:

➤ The average FICO score on IOs is 43 points higher than on amortizing loans. This is a very significant difference.4

➤ Average loan balances on IOs are $66,000 higher than the balances on amortizing loans. Higher loan balances reduce default frequency (most likely because they are correlated with higher disposable incomes and wealthier borrowers) and reduce loss severity on defaulted loans.

➤ The rating agencies require about 20% of additional credit enhancement for a subprime IO compared to a subprime amortizing loan.

Figure 15 compares the collateral characteristics of amortizing subprime hybrids and subprime IOs securitized in the second half of 2004 and the first half of 2005.

4 See previous references for an estimate of the importance of FICO score for credit performance.

IOs carry additional credit risks.

Absence of equity buildup is not a

major risk.

Credit risks are offset by better borrower credit

and higher enhancement.



Figure 15. Comparison of Amortizing and IO Subprime Loans Securitized Q3 04–Q2 05 Amortizing (%) IO (%)Percent of Originations 79 21Average Loan Balance $173,000 $239,000 WAC 7.28 6.44Index Six-Month LIBOR 99 93Margin 6.10 5.49Initial Cap 2.27 2.37Periodic Cap 1.19 1.25Rate Reset Period 6mos 99 96First Reset Two Years 80 66 Three Years 19 25

Penalty Term No Penalty 30 21 Two Years 46 51 Three Years 19 21

IO Term Two Years 32 Three Years 20 Five Years 45

California Concentration a 26 56

Loan Purpose Purchase 36 58 Equity Takeout 58 36 Rate/Term Refi 6 6

Owner Occupancy 93 96Documentation Full 59 64 Limited 41 36 None 0 0

FICO 610 653LTV 82 83Known Seconds 14 38Combined LTV (when 2nd lien present) 97 98Debt-to-Income 40 42a No other state exceeds 10%. Sources: LoanPerformance and Citigroup.



Collateral Performance

A large majority of current HEL deals do not carry credit protection provided by outside parties. In addition, all HEL bonds are amortizers. Therefore, HEL investors face credit and prepayment risk. In this section we review the performance of HEL collateral. In the last section of the paper we relate the collateral performance to the valuation of HEL securities.

Credit Performance Lifetime cumulative losses on HEL pools typically range from 3% to 5%. Various factors, including servicing performance, collateral properties, and the economic environment affect losses. Because collateral characteristics change from one origination year to another, the collateral performance also changes from one origination year to another. Figure 16 shows the cumulative losses by origination year for fixed- and floating-rate HELs deals originated by 13 large issuers between 1997 and 2004.5

Figure 16. Average Industry HEL Cumulative Losses, 1997–2004 Floating Fixed

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 5 10 15 20 25 30 35 40 45 50

Months Since Issuance

Perc

ent o

f Orig

inal

Bal

ance

(%)

1997 1998 1999 20002001 2002 2003 2004

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 5 10 15 20 25 30 35 40 45 50

Months Since Issuance

Perc

ent o

f Orig

inal

Bal

ance

(%)

1997 1998 1999 20002001 2002 2003 2004

Source: Citigroup.

Credit performance has been improving steadily since the 2000 vintage. Most of the improvement can be accounted for by the increase in the average FICO scores and loan balances shown in Figures 11 and 12. The post-2000 vintages have also benefited from accelerating HPA.

Loss on a HEL is a combination of two effects:

1 Borrower default, which means that the borrower has stopped making mortgage payments and the property is repossessed and sold by the lender or the mortgage debt is resolved through some other means. One alternative resolution is a sale of the property, where the lender agrees to accept a partial payoff on the loan to avoid the lengthy and costly repossession process.

5 Citigroup’s Home Equity Loan Lifecycle Overview (HELLO) report tracks the prepayment and credit performance of 13 large HEL

issuers from 1997 to the present. The report is issued bimonthly. See HELLO, Citigroup, September 21, 2005.

HEL investors face credit and prepayment risk.

Lifetime cumulative losses on HEL pools

range from 2% to 6%.

Credit performance has been improving steadily

since the 2000 vintage.



2 Loss severity, which means that the net proceeds from the resolution of a defaulted loan are insufficient to cover the loan amount. In spite of initial LTVs that are below 100%, most defaults result in a loss. The average loss severity for first-lien subprime pools is about 40%.

Several collateral characteristics have a direct impact on losses. Some of them, such as the FICO score, level of documentation, occupancy status, and borrower’s debt-to-income ratio, affect only the probability of default. Others, such as the LTV and loan balance, affect both the default probability and loss severity. Next, we briefly review the key drivers of losses.

Borrower’s Credit Score

The credit score, as captured by FICO or some other, issuer-specific credit scoring formula, is the most important determinant of HEL defaults. FICO is a general credit score, not specifically tailored to mortgage products. Nevertheless, it is useful for predicting defaults and is widely used. It is reported for all mortgages, making it easy to compare the credit risks across deals. The score is computed by the credit reporting bureaus, using a proprietary formula developed by Fair Isaac. It includes the borrower’s credit characteristics, such as the number of credit lines available, their utilization, past payment history, and the number of inquiries to the credit bureau in the recent past.

Figure 17 shows the effect of FICO score on cumulative losses at 48 months of seasoning. The clear separation of losses between different FICO buckets demonstrates the usefulness of FICO score. In this calculation we only use initial LTVs between 75% and 85%.

Figure 17. Effect of FICO Score on Cumulative Losses at 48 Months of Seasoning

FICO Ranges

Collateral Type 0-580 581-610 611-650 651-690 691+Floating 4.7 2.8 2.2 1.6 1.2Fixed 4.0 2.3 1.8 1.4 1.0


Initial LTV

Borrowers who have more initial equity in the property are less likely to default. Higher equity generally implies financially stronger borrowers. In addition, if the borrower is unable to make monthly payments because of job loss, divorce, illness, or death, higher equity makes it more likely that the borrower (or estate) will sell the property and avoid default. In addition, in case of default, higher equity implies lower loss severity. Figure 18 shows the effect of initial LTV on cumulative losses. The highest-LTV bucket has more than three times the losses of the lowest-LTV bucket, confirming the importance of LTV in predicting losses. In this calculation, we only use FICOs between 590 and 640.

The credit score is the most important

determinant of default.

Higher equity implies lower risk of default. In

case of default, it implies lower loss severity.



Figure 18. Effect of Initial LTV on Cumulative Losses at 48 Months of Seasoning

LTV Ranges

Collateral Type 0-60 60-70 70-80 80-90 90+Floating 0.9 1.2 2.1 2.8 3.3Fixed 0.6 1.1 1.9 2.2 2.6


Level of Documentation and Owner Occupancy

Borrowers who do not or cannot provide the full documentation of employment and assets are higher credit risks. This also holds true for borrowers who are financing a rental property rather than their residence. Figure 19 illustrates the effect of documentation and occupancy on cumulative losses. In the figure, we control for FICO scores and LTVs, but do not take into account the effect of other variables.

Figure 19. Effect of Documentation and Occupancy on Cumulative Losses at 48 Months of Seasoning

Documentation Occupancy

Collateral Type Full Partial None Owner Occ Inv. Property Second Home

Floating 2.5 4.7 5.7 1.9 5.8 1.9Fixed 2.1 3.4 NA 2.2 7.1 2.0

Source: Citigroup.

Loan Balance

Higher balance loans generate lower losses. On the one hand, borrowers who take out higher balance loans are more financially sophisticated and have higher disposable income than borrowers who take out lower-balance loans. These characteristics imply lower default probabilities. On the other hand, if a loan defaults, a higher loan balance implies higher recovery rates. The effect of loan balance is most prominent for a loan below $140,000. It is a much weaker distinguishing factor between medium- and high-balance loans. Figure 20 illustrates the effect of loan balance on cumulative losses.

Figure 20. Effect of Loan Balance on Cumulative Losses at 48 Months of Seasoning

Loan balance Ranges ($ Thousands)

Collateral Type 0-140 140-250 250-500Floating 3.1 1.2 1.3Fixed 3.4 1.3 1.0

Source: Citigroup.

Other collateral characteristics that affect losses include loan term, lien, and debt-to-income ratio.

Timing of Losses — Default Curves Cumulative losses have a straightforward interpretation — they are the percentage of the original deal balance that is written off. However, this description of losses mixes the effect of three different factors: prepayments, default rate (or default probability), and loss severity. Collateral characteristics and the economic variables affect each one of these factors differently, making it difficult to project cumulative losses directly. In addition, the valuation of HEL securities depends on the timing of losses,

Low-documentation loans and investor

properties are higher credit risks.

Higher balance loans generate lower losses.

Cumulative losses combine the effects

of prepayments, default probability, and loss

severity.



so that a prediction of a lifetime cumulative loss is not sufficient to fully gauge the credit risk of a bond.

Definition of CDR and Net Loss Rate

The default rate is measured by constant default rate (CDR). The CDR is the dollar amount of defaults in a given month divided by the outstanding balance at the beginning of the month and annualized. Because loans that default are removed from the deal, defaults are also prepayments. The CDR is simply a default contribution to the CPR (constant prepayment rate). The two units are the same.

The net loss rate is the CDR multiplied by loss severity. Therefore, the net loss rate is the dollar amount of loss in a given month divided by the outstanding balance at the beginning of the month and annualized.

The conversion from the net loss rate to cumulative losses is straightforward:

1 Multiply the monthly net loss rate by the outstanding balance to get the dollar amount of loss;

2 Sum up the dollar losses for each month to get the dollar cumulative loss through month N. N can include all months in the life of the pool — lifetime cumulative loss;

3 Divide the dollar amount of loss through month N by the initial pool balance to get the cumulative loss through month N.

The outstanding balance at the beginning of each month depends on prepayments. Therefore, step one depends on prepayments and the relationship between cumulative losses and net losses depends on prepayments.

The CDR Seasoning Curve

The default rate is highest between loan ages of 3.5 and 4.5 years. At that time, the risk of negative equity in the property owing to adverse home price movements is highest.6 At the same time, the positive selection of borrowers created by the loan origination process has partly worn off, while the risk of adverse life events, such as loss of job, divorce, and health crises, has increased among the borrower population. As the loan seasons further, amortization and HPA become the dominant factors, diminishing the risk of default. The CDR seasoning curves for fixed- and floating-rate HELs are shown in Figure 21.

6 A mathematical model of defaults that explains the shape of the default curve is described in Prepayments on Green Tree MH

Loans, I.Gjaja, L.Hayre, P.Jablansky, and A.Rajan, Citigroup, August 1999.

CDR is the annualized monthly default rate.

The net loss rate is the CDR multiplied by loss

severity.

The default rate is highest between loan

ages of 3.5 and 4.5 years.



Figure 21. Default Seasoning Curves

0

2

4

6

8

10

12

14

0 20 40 60 80 100

Loan Age (Months)

CDR

(%)

Floating Fixed

Source: Citigroup.

Defaults are higher for floating-rate loans than for fixed-rate loans. The peak of the floating-rate default curve is about 12.5% CPR and the peak of the fixed-rate default curve is about 8% CPR. Two factors contribute to higher defaults on ARMs:

1 The slightly weaker credit profile of ARM loans, as shown in Figure 9; and

2 The adverse selection of ARM borrowers following the reset. Higher credit borrowers and higher loan balances refinance faster after the reset, leading to a drop in the average credit profile of the remaining pool.

In spite of higher defaults, ARMs have lower cumulative losses than fixed-rate loans (see Figure 16). Because prepayments on floating-rate loans are faster, the outstanding pool factor at each month is lower, resulting in a lower dollar amount of loss.

Loss Severity

Defaults of HELs result in loss severities of 35%–45%. Several factors lead to loss severities greater than zero, including the following:

1 Servicer advances during delinquency and foreclosure (discussed in the section entitled “HEL Deal Structures”);

2 Legal and realtor fees incurred in the repossession of the property and its subsequent sale;

3 Real estate taxes paid over the same period;

4 Need for maintenance, upkeep, and repair of the property prior to sale; and

5 Initial overestimates of the value of the property, which are common in refinancings.

Higher loan balances imply lower loss severities, as do lower LTVs. Because LTVs decrease with rising home prices, HPA has a beneficial effect on loss severity. Generally, loss severities begin to decrease markedly only after the LTV has reached about 60%. Initial appraisal inflation is partly responsible for the low sensitivity of loss severity to the LTV when the LTV is between 60% and 100%.

Defaults are higher for floating-rate loans than

for fixed-rate loans.

ARMs have lower cumulative losses than

fixed-rates.

Higher HPA implies lower loss severity.



Payment Resets and Defaults

Loan coupons on hybrids may reset up at the first and subsequent reset dates, implying higher monthly payments. If the payment increase is large, the borrower may be exposed to payment shock, leading to higher delinquencies and higher defaults. Under the current market terms, for example, a typical 2/28 amortizing hybrid will see its loan coupon increase by 260bp at the first reset (see Figure 10). This implies an increase in monthly payments by about 35%.

The effect of resets on defaults is asymmetrical: Payment increases imply higher delinquencies, but payment decreases have little effect on credit performance. Figure 22 shows the probability of default as a function of the reset amount. Resets have recently gained in importance for the following reasons:

➤ Short rates are rising, which implies higher resets.

➤ Coupon teasing has increased in the last 18 months, as shown in Figure 10. Lower teaser rates imply higher resets.

➤ In contrast to the underwriting practices of several years ago, loans are now underwritten to the initial payment rather than to the fully indexed payment. This leaves the borrower more vulnerable to the reset.

➤ IOs include the payment adjustment of a reset and the payment adjustment of amortization. When the IO term coincides with the fixed-rate term, the two adjustments occur simultaneously.

Figure 22. Effect of Payment Reset on Defaults 12 Months After Reset

8

9

10

11

12

13

14

-3,000 -2,000 -1,000 0 1,000 2,000 3,000

Payment Reset ($)

CDR

(%)

Source: Citigroup.

Delinquency Roll Rates Default Timeline

If a borrower misses one monthly payment, the loan becomes 30 days delinquent. If he misses two monthly payments, the loan becomes 60 days delinquent, and so on. Between two and three months of delinquency the servicer generally sends a letter to the borrower stating its intention to foreclose. The foreclosure proceeding is a lengthy legal process that ends with the eviction of the borrower from the property and its repossession by the servicer. The servicer’s (or lender’s) ownership of the

Coupon resets on hybrids may lead to

payment shock.

Upward resets imply higher defaults, but

downward resets have little effect.



property is called real estate owned (REO). After sale of the property, the proceeds are distributed to the trust and the loan is removed from the deal. Therefore, the prepayment and loss resulting from default are realized only when the delinquent loan is resolved.

The time between initial delinquency and sale of the property varies from state to state. Some states allow administrative foreclosures, while others require judicial foreclosures (which means that the court has to approve the servicer’s repossession of the property). The national average of the time from the 30-day delinquency to the disposition of the loan through REO is about 20 months.

The credit performance of a securitized deal does not depend directly on the delinquency status of the loan, because the servicer normally advances principal and interest until the delinquency is resolved. Nevertheless, an understanding of delinquencies is key to gauging the credit performance of an HEL for the following reasons:

1 Current delinquencies are the best predictor of future defaults and losses for seasoned deals.

2 If a loan defaults, the amount of realized loss is directly related to the time the loan has spent in delinquency.

3 Delinquencies represent an interruption of cash flows for the residual holders.

We show the historical monthly transition rates (or roll rates) between different delinquency states of a subprime loan for a representative issuer in Figure 23. The roll rates indicate the probability that a loan will roll from one delinquency state to another in one month.

Some issuers report borrower’s bankruptcy status as a separate delinquency state; others simply report the status of the monthly payments. A bankruptcy filing has fewer implications for mortgages than for unsecured debt. On the one hand, the borrower’s bankruptcy filing does not prevent repossession of the property if the borrower fails to make the mortgage payments. On the other hand, if the borrower continues to make the monthly payments, he may be able to keep his primary residence in bankruptcy. (Under the current bankruptcy law, the real estate equity that the borrower can retain in bankruptcy is capped at $125,000.)

The average time to default through REO is

about 20 months.

Delinquencies are key to predicting losses.

Delinquency transition rates are the

probabilities of transition from one delinquency

state to another.

Bankruptcies have a smaller effect on

mortgages than on unsecured debt.



Figure 23. Monthly Delinquency Roll Rates for Fixed- and Floating-Rate HELs Fixed-Rate Loans To

From Current 30 60 90+ Foreclosure REO PayoffCurrent 94.9 2.3 0.1 0.0 0.0 0.0 2.730 Days 37.8 33.5 22.0 0.5 2.4 0.0 3.860 Days 13.1 11.1 19.1 37.9 15.9 0.0 3.090+ Days 2.7 0.9 2.4 79.6 11.7 0.2 2.4Foreclosure 2.5 0.2 0.1 1.4 87.6 4.9 3.4REO 0.0 0.0 0.0 0.1 0.3 83.3 16.3

Floating-Rate Loans To

Current 94.4 2.4 0.1 0.0 0.0 0.0 3.030 Days 35.5 33.3 23.7 0.5 3.5 0.0 3.560 Days 11.5 9.7 18.4 36.5 21.0 0.0 2.990+ Days 2.4 0.8 2.4 79.0 13.1 0.2 2.0Foreclosure 2.6 0.1 0.1 1.5 87.6 4.6 3.4REO 0.0 0.0 0.0 0.0 0.2 82.4 17.3

Source: Citigroup.

Several features of delinquency roll rates are evident in Figure 23, including the following:

➤ Transition rates of fixed- and floating-rate loans are similar across a variety of initial and destination states. One difference is that floaters consistently pay off faster. Another difference is that floaters proceed to foreclosure from various delinquency states at a slightly higher rate.

➤ In each month, the probability that a current loan will become 30 days delinquent is high, at over 2% for both fixed- and floating-rate loans. However, the most common resolution of a 30-day delinquency is a return to current status. Therefore, the 30-day delinquency is a relatively common state for a subprime borrower.

➤ Foreclosure proceedings or 90-plus-day delinquency is by far the most common resolution of 60-day delinquency.

➤ REOs and payoffs are the most common resolutions of foreclosure proceedings. A large majority of these payoffs likely result from a loss mitigation strategy and result in some loss to the lender. The loss is smaller, however, than the loss incurred from the REO status.

➤ About 20% of loans return from foreclosure to current status. (We calculate this fraction by considering all transitions away from foreclosure.)

➤ Once the loan is in REO, payoff is the only possibility.

Citigroup has developed a detailed model of delinquency transitions that relates the major transitions to collateral characteristics and economic variables, such as unemployment, HPA, and interest rates.7

7 Delinquency Transitions in Subprime Loans — Analysis, Model, Implications, I.Gjaja and J.Wang, Citigroup, March 8, 2004.



Delinquencies Imply Defaults

Delinquency roll rates make it possible to estimate the fraction of delinquent loans that will default, as well as the time they will take to default. We provide the estimates in Figure 24. For the purposes of this calculation, we define a default as any payoff from 90-plus-day delinquency, foreclosure, or REO. To estimate overall payoff rates, we use the average historical prepayment speeds.

Figure 24. Lifetime Default Probability of Loans in Different Delinquency States Initial State ARMs (%) Fixed-Rates (%)60 Day Delinquency 56 5390+ Day Delinquency 68 67Foreclosure 77 78REO 99 99

Source: Citigroup.

More than half of 60-day delinquent loans eventually default and about two thirds of 90-plus-day delinquent loans eventually default. Foreclosure implies a further deterioration of the loan’s prospects. Because only 10%–15% of the initial pool balance defaults, Figure 24 demonstrates the importance of serious delinquency as a predictor of defaults.

Prepayments

Stability of HEL Prepayments

One of the great appeals of HELs over prime mortgages is the stability of prepayments, as subprime borrowers are less sensitive to interest rate shifts than prime borrowers. The majority of subprime prepayments occur because the borrower has improved his credit standing and has become eligible for a lower interest rate or higher-LTV loan (credit curing), or because the borrower’s home has appreciated in value and he has decided to monetize the additional equity. Loan purpose (shown in Figure 9) supports this view.

The comparison of prime and subprime speeds can be summarized as follows:

➤ Subprime loans have higher speeds in the absence of interest rate incentives (baseline speeds), because most of the refinancings are driven by credit and HPA. In addition, defaults are a much bigger component of prepayments. Defaults have only a modest dependence on interest rates.

➤ In the presence of an interest rate incentive, the refinancing response of subprime borrowers is lower.

Figure 25 compares the HEL industry average speeds with the speeds on all Fannie Mae mortgages from December 1998 to the present. On the fixed-rate side, HEL speeds spanned 23% CPR, ranging from 18% to 41% CPR. Fannie Mae speeds spanned 51% CPR, ranging from 7% to 58% CPR. The comparison is similar for hybrid speeds. HEL speeds spanned 25% CPR (between 29% and 54% CPR), compared to 38% CPR for Fannie Mae (ranging from 15% to 53% CPR). A similar

Delinquency roll rates make it possible to

estimate the fraction of delinquent loans that

will default.

More than half of 60-day delinquent loans

eventually default.

HEL speeds are more stable than prime mortgage speeds.

Since December 1998, HEL fixed-rate speeds have ranged over 23%

CPR, and HEL ARM speeds have spanned

25% CPR.



comparison holds between HEL and jumbo and alt-A speeds.8 The span of prime nonagency hybrid speeds is even wider than that of Fannie Mae 3X1s.

Figure 25. Comparison of Floating- and Fixed-Rate HEL and Fannie Mae Speeds, Dec 98–Jul 05 Floating Fixed

Dec 98 Dec 99 Dec 00 Dec 01 Dec 02 Dec 03 Dec 04 Dec 05

1 M

o CP

R (%

)

0

10

20

30

40

50

60HEL Fannie Mae 3x1

0

10

20

30

40

50

60

Dec 98 Dec 99 Dec 00 Dec 01 Dec 02 Dec 03 Dec 04 Dec 05

1 M

o CP

R (%

)

HEL Fannie Mae

Source: Citigroup.

Components of Prepayments

Prepayments that are reported for HEL deals are the sum of several different components. They can be broken down into voluntary prepayments and involuntary prepayments (defaults). The basic reasons why borrowers prepay their mortgages are as follows:9

Home Sales

The sale of a home leads to the prepayment of a mortgage. HELs are not assumable, meaning that the purchaser of a home cannot take over the existing mortgage.

Refinancings

Refinancings refer to mortgagors prepaying an existing loan and taking a new one. Refinancings can be cash-out refinancings, where the new mortgage is larger than the refinanced mortgage, or they can be interest rate/term refinancings. In the interest rate/term refinancing the borrower takes advantage of lower interest rates or generally more favorable loan terms to lower his monthly payment or to accelerate equity buildup in the property.

Defaults

We discussed defaults in the previous section. Sometimes defaults are difficult to distinguish from other forms of prepayments, as in the case where the borrower loses his job and sells his home in order to pay off the mortgage and avoid foreclosure.

Curtailments and Full Payoffs

Some mortgagees are in the habit of sending in more than the scheduled payment each month, as a form of forced savings and to build equity in their homes faster.

8 Citigroup’s Summary of Nanaegncy Performance (SNAP) I.Gjaja et al., Citigroup, September 9, 2005, tracks prepayments and

credit performance of six large alt-A issuers between 1997 and the present. The SNAP report is released bimonthly.

9 Anatomy of Prepayments, L.Hayre et al., Citigroup, March 23, 2004.



The extra payments are referred to as curtailments and show up as partial prepayments of principal. Full payoffs refer to mortgages that have been prepaid completely, usually when the mortgages are very seasoned and the remaining loan balances are small. Full payoffs can also occur because of the destruction of the home from natural disasters such as hurricanes and earthquakes.

Prepayment Seasoning Curve

HEL prepayments show a distinctive seasoning pattern. Because of the stability of speeds over time, as shown in Figure 25, the seasoning curve is clearly visible for each vintage, regardless of the interest rate or HPA environment. We show the industry-average prepayment seasoning curves for fixed- and floating-rate HELs in Figure 26. To limit the effect of interest rates, we only include prepayments when the refinancing incentive was between -100bp and +100bp. We also show the typical deal pricing speeds.

Figure 26. Prepayment Seasoning Curves for Floating- and Fixed-Rate HELs and Typical Deal Pricing Speeds Floating Fixed

0

10

20

30

40

50

60

70

0 20 40 60 80

Loan Age (Months)

CPR

(%)

Actual 100PPV

0

5

10

15

20

25

30

35

0 20 40 60 80

Loan Age (Months)

CPR

(%)

Actual 23 HEP

Source: Citigroup.

The first spike in prepayments on both fixed- and floating-rate loans occurs at 13 months. After 12 timely mortgage payments, many borrowers become eligible for a loan with a lower interest rate or a higher LTV, prompting a wave of refinancings. An additional reason for the increase in speeds after 12 months is that brokers are often prohibited from resoliciting customers within 12 months or loan origination. After month 12, borrowers start receiving solicitations from the broker who originated their loan, boosting the refinancing activity.

The second prepayment spike occurs after 24 months. It is very sharp for ARMs, with average speeds exceeding 66% CPR. The spike combines the effect of penalty expiration and first reset on 2/28 hybrids. (Two-year penalties and two-year resets are the most common — see Figure 9). Expiration of the prepayment penalty releases a pent-up refinancing demand, as the economics of refinancing improves dramatically. In addition, because the first reset on the loan often implies a rate increase, and because the prevailing WAC offered in the primary market may be lower (see Figure 10), the first reset also causes a sharp rise in prepayments. The increase on fixed-rate HELs is much smaller. It corresponds to the expiration of two-year penalties, which are not very common in fixed-rate loans.

The prepayment seasoning curve is identifiable in each

vintage.

The prepayment spike at 13 months is the result

of credit curing.

The prepayment spike after 24 months is

caused by the expiration of the two-year penalty, and for hybrids, by the

first reset of the loan coupon.



With the prepayment vector shown in Figure 26, the pool factor of a floating-rate pool is 0.27 after 30 months of seasoning, meaning that 73% of the collateral has paid off by that time. The pool factor reaches 0.10 after 48 months of seasoning. The WAL of a floating-rate pool is about 2.5 years. The rapid decrease of the pool factor implies that prepayments for loans seasoned by more than five years are of limited importance. However, a slowdown of speeds could extend the WAL of the collateral, raising the significance of seasoned collateral.

The pool factor does not drop as rapidly for fixed-rate HELs. After 30 months of seasoning, the factor is 0.55. It reaches 0.10 only after 109 months. The WAL of a fixed-rate pool is about three years.

The prepayment spikes for loan ages of 36 months and greater correspond to the expiration of the three- and five-year penalties, and to the first reset on 3/27 hybrids. As we showed in Figures 9 and 13, more than 80% of HELs carry a prepayment penalty. For fixed-rate HELs, three years is the most common penalty term.

More detailed analyses of fixed- and floating-rate HEL prepayments require the calculation of the seasoning curves for each penalty term and each initial reset. For a description of these curves we direct the reader to our relevant publications.10

Actual Speeds Versus New-Deal Pricing Speeds

The new-deal pricing speed varies from deal to deal. The most common pricing speed ramps are shown in Figure 26. The 100PPV used for ARMs stands for 100% of the prepayment pricing vector. The vector includes a spurt of prepayments after the 24-month reset. The 23 HEP curve (home equity prepayment) used for fixed-rate collateral is defined as follows: 2.3% CPR in month one, increasing by 2.3% CPR each month until month ten, and remaining constant at 23% CPR thereafter. Other values of HEP are defined analogously — for example, 20 HEP. If a deal has both fixed- and floating-rate loans, a separate pricing curve is used for each collateral group.

The 100PPV curve is well below the actual seasoning ramp. This is advantageous to the investor, because it implies that new-issue securities are priced at longer than actual weighted average life (WAL), and longer WALs imply higher spreads. Pricing speeds for seasoned deals in the secondary market match the actual speeds much more closely than the 100PPV curve. The new-issue pricing curve for fixed-rate loans is only slightly lower than the actual speeds, as shown in Figure 26. Pricing of fixed-rate securities, which are backed by fixed-rate collateral, is more sensitive to the prepayment assumption, because the investor is long interest rate duration. (We discuss this in more detail in the section entitled Valuation of HEL Securities.)

10

See Fixed-Rate Loans in RASC-KS Deals, I.Gjaja and A.Kari, Citgroup, September 20, 2002, and New Model of Subprime Hybrid Prepayments, I Gjaja and O. Beelders, Citigroup, June 17, 2005.

At 30 months of seasoning the pool

factor for floating-rate HELs is 0.27.

The pool factor drops more slowly for fixed-

rate HELs.

The prepayment spikes after 36 months

correspond to penalty expirations and to the

first reset on 3/27s.

The new-issue pricing speed is slow for ARMs

and is close to the actual seasoning ramp for

fixed-rates.



Main Determinants of Prepayments

The Refinancing Curves

The refinancing curves of fixed- and floating-rate HELs are much less steep than the refinancing curves of prime mortgages. Nevertheless, the refinancing response is a key adjustment of the seasoning curves shown in Figure 26. We show the refinancing curves in Figure 27. For floating-rate loans we use loan ages of six to 24 months, and we define the refinancing incentive as the difference between the actual loan coupon and the prevailing market coupon for that type of loan. (After reset, the actual coupon is adjusted.) For fixed-rate loans we use loan ages of 13 to 60 months. The refinancing incentive is calculated as the difference in the Freddie Mac 30-year survey rate between loan origination and loan prepayment (with lags).

Figure 27. Refinancing Curves for Floating- and Fixed-Rate HELs Floating Fixed

20

25

30

35

40

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Refinancing Incentive (%)

CPR

(%)

15

20

25

30

35

40

-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0

Refinancing Incentive (%)

CPR

(%)

Source: Citigroup.

The slope of the fixed-rate refinancing curve near zero curve is 6%–7% CPR per 100bp interest rate shift. It is nearly symmetric about zero, implying that a selloff of interest rates slows down prepayments by about as much as an interest rate rally speeds them up. This refinancing curve stands in contrast to the refinancing curve for prime collateral. Prime loans exhibit only a weak response to interest rates until they are at least 50bp in-the-money. Further interest rate rallies then lead to very sharp speed increases.

The refinancing curve for floating-rate HELs is also symmetric about zero, but it is much flatter, with a slope of about 3% CPR per 100bp of interest rate incentive. This flatter refinancing curve helps explain the greater stability (lower percentage variation) of floating-rate HEL prepayments in Figure 25 compared to the fixed-rate prepayments. The relative standard deviation of floating-rate HEL speeds is 15% compared to 21% for fixed-rate speeds. Note that industry-average floating-rate speeds are more stable, even though the floating-rate seasoning curve exhibits a great deal more variability than the fixed-rate seasoning curve (see Figure 26).

The refinancing response is a key adjustment of the

seasoning curves.

Fixed-rate speeds increase by 6%–7% CPR

per 100bp interest rate rally.

The refinancing curve for HEL ARMs is flatter, with

a slope of 3% CPR per 100bp interest rate shift.



The Prime-Subprime Spread

Historically, the spread between prime and subprime rates has been about 350bp for ARMs and 150bp–200bp for fixed-rates. Until July 2005, the spread between the subprime ARM rate and the corresponding prime mortgage rates has been compressing, providing an additional refinancing incentive to HEL borrowers. (Most subprime mortgages refinance into a subprime mortgage rate.) On the fixed-rate side, the prime-subprime spread has been very tight until April 2005, when it started widening. Figure 28 compares the rates on 2/28 subprime hybrids and 1x1 agency ARMs and fixed-rate subprime and agency loans. We limit the HELs to a 10% range of LTVs and a 50-point range of FICOs. The spread compression is the result of several factors, including the following:

1 Lower elasticity of subprime mortgage rates;

2 Competition in the subprime lending industry; and

3 Excellent secondary market execution of HEL transactions.

Early indications point to a reversal of spread compression on HEL ARMs over the past two months.

Figure 28. History of Prime and Subprime Mortgage Rates, Jan 98–Jul 05 Floating Fixed

2

4

6

8

10

12

Jan 98 Apr 99 Jul 00 Oct 01 Jan 03 Apr 04 Jul 05

Rate

(%)

2.0

3.0

4.0

5.0

Diff

(%)

Subprime Rate Freddie Mac 1x1 Diff (Right Axis)

4

5

6

7

8

9

10

11

12

Jan 98 Apr 99 Jul 00 Oct 01 Jan 03 Apr 04 Jul 05

Rate

(%)

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Diff

(%)

Subprime RateFreddie Mac 30-Year FixedDiff (Right Axis)

Source: Citigroup.

Home Price Appreciation and Spread Momentum

The majority of subprime loans are taken out as cash-out refinancings. Such a refinancing is possible only when the borrower is able to tap additional equity in the property, either because of HPA or because his credit has improved and he now qualifies for a higher LTV.

HPA is especially important for hybrids, where the dollar amount of equity buildup since loan origination is the most important determinant of prepayments. The importance of this variable clearly demonstrates the subprime borrower’s interest in extracting the available equity in his home. The far-left graph in Figure 29 shows the effect of equity buildup on hybrid speeds between the loan ages of six and 24 months. (We compute the equity buildup curve for each loan age, then average the curves.) As with all economic variables, equity buildup has a more pronounced effect on no-penalty loans.

The prime-subprime spread historically has

been about 350bp for ARMs and 150bp–200bp

for fixed-rates.

HPA facilitates cash-out refinancings.

The dollar amount of equity buildup is the

most important driver of hybrid speeds.



Equity buildup is a direct result of accumulated HPA and loan balance. Therefore, faster HPA and higher original loan balances imply higher prepayments. Both of these have been rising steadily since 2000, explaining in part the rise in hybrid prepayments since 2000 shown in Figure 25.

Figure 29. Effect of Equity Buildup, Home Price Momentum, and Spread Momentum on Floating-Rate Prepayments Equity Buildup Home Price Momentum Spread Momentum

0

10

20

30

40

50

60

4 8 12 16 20Equity Buildup ($000's)

CPR

(%)

No Penalty Penalty

0

10

20

30

40

50

60

70

80

10 12 14 16 18 20

Home Price Momentum (%)

CPR

(%)

No Penalty Penalty

0

10

20

30

40

50

60

70

80

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Spread Momentum (%)

CPR

(%)

No Penalty Penalty

Source: Citigroup.

Home price momentum and spread momentum are two other important external determinants of ARM speeds. Home price momentum is the two-year change of the national HPA index provided by Freddie Mac. It is a general measure of the strength of the housing market. A strong housing market enhances both cash-out refinancings and home sales (turnover). The spread momentum is a two-year change of spread between the 2/28 hybrid current coupon and one-month LIBOR. We use one-month LIBOR as a proxy for the cost of funding of subprime lenders. A compression of this spread indicates active borrower solicitation.

Figure 29 shows the effect on prepayments of the two momentum variables. In both cases, the no-penalty loans are much more responsive to the change in the momentum variable. The figure indicates that the spread momentum plays a role only for negative values. Therefore, a widening of the spread between one-month LIBOR and the 2/28 rate does not appear to affect speeds.

Collateral Factors

Various collateral characteristics affect prepayments. The most important ones are loan balance, FICO score, initial LTV, owner occupancy, and loan purpose. The effect of these collateral features typically depends on the refinancing incentive. For example, loan balance is more important for positive refinancing incentives than for negative ones.

Loan Balance

A higher loan balance implies a larger dollar amount of savings that can be realized by refinancing. In addition, higher loan balances typically imply wealthier and more sophisticated borrowers who react more readily to refinancing opportunities. Figure 30 illustrates the effect of loan balance on fixed-rate HEL refinancing curves.

Equity buildup is a direct result of HPA and loan

balance.

Home price momentum and spread momentum

are the other external determinants of

prepayments.

The most important collateral determinants

of speeds are loan balance, FICO, LTV,

owner occupancy, and loan purpose.



Figure 30. Effect of Loan Balance on HEL Refinancings

Loan Size (Dollars in Thousands)

Refinancing Incentive Less Than 75 76-110 111-180 181-350 Greater than 351-100bp 8% CPR 10% CPR 10% CPR 8% CPR 8% CPR0 12 14 23 28 22 100 16 22 32 42 39 200 20 27 36 47 49 250 21 28 38 48 49

Source: Citigroup.

At positive incentives, the loan balance is an excellent predictor of prepayments. For example, at the refinancing incentive of 200bp, the difference in speeds between low-balance loans and high-balance loans (balances less than $75,000 and greater than $350,000) is 29% CPR. Moreover, each increase in loan balance leads to systematically higher speeds. The effect of loan balance persists even for zero refinancing incentive, implying that the refinancing enhanced by loan balances includes credit curing and cash-out refinancings, in addition to interest rate refinancings.

The slope of the refinancing curve continues to be a function of loan balance even for negative refinancing incentives. For example, the slowdown of prepayments in a 100bp selloff is only 3% CPR for low-balance loans, but as much 14% CPR in subprime loans greater than $350,000. The effect of loan balance on ARM speeds follows the same pattern, but is less pronounced.

FICO

FICO has a similar but weaker effect on prepayments than the loan balance. Higher FICOs prepay faster in interest rate rallies, and higher FICOs imply steeper refinancing curves. Figure 31 shows the results for fixed-rate HELs, while controlling for loan balance.

Figure 31. Effect of FICO Score on HEL Refinancings

FICO Score

Refinancing Incentive Less Than 580 581-610 611-650 651-690 Greater than 690-100bp 11% CPR 9% CPR 10% CPR 9% CPR 10% CPR0 14 16 19 18 17 100 22 24 26 25 26 200 29 29 30 32 33 250 30 30 31 34 36 Source: Citigroup.

Owner Occupancy

Given the refinancing opportunity, HELs on owner-occupied properties are slower to refinance than HELs on investment properties. Figure 32 shows the refinancing curves for the two occupancy types for fixed-rate HELs. This is the opposite of the pattern seen in prime loans, where owner-occupied properties are faster to refinance.

At the refi incentive of 200bp, high-balance loans outpay low-balance loans

by almost 30% CPR.

Higher FICOs imply steeper refinancing

curves.

HELs on investment properties refinance faster than HELs on

owner-occupied properties.



Figure 32. Refinancing Curves by Owner Occupancy

0

5

10

15

20

25

30

35

40

45

50

-2 -1 0 1 2

Incentive (%)

CPR

(%)

Owner-Occupied Investment

Source: Citigroup.

Financial sophistication is the main reason for the difference in refinancing curves shown in Figure 32. Ownership of an investment property by a subprime borrower indicates a greater financial savvy and awareness of refinancing opportunities than that of a subprime borrower who does not own an investment property. Financial savvy is much less of an issue with prime borrowers. Investor properties carry a coupon that is about 50bp higher than the coupon for an owner-occupied property. If a prime borrower has moved from his residence and turned it into an investment property, the difference in coupon is a disincentive to refinance.

Media Effect

When interest rates reach their multiyear lows, the media attention to the mortgage market spurs refinancings. Although consumers may be better educated today about their choices than they were in the past, and the Internet has made refinancing more efficient, the media effect is real and it drives refinancings. It also makes prepayments dependent on the history of interest rates. Citigroup’s fixed-rate and floating-rate HEL prepayment models incorporate the media effect by comparing the current mortgage rates to their long-term historical average.

Multiyear interest rate lows spur refinancing

activity.



HEL Deal Structures

All HEL deals in the ABS market today are structured, meaning that the borrower payments are distributed to investors according to a set of rules. Structured deals stand in contrast to pass-throughs. In a pass-through, all the borrower payments are passed directly to the bondholders after the subtraction of servicing and insurance fees. Therefore, the payment window and prepayment risk of the loan pool are mirrored directly by the bonds.

The structure distributes the cash flows from the loans into different classes in a HEL deal in order to achieve the following purposes:

➤ Produce a variety of principal payment windows and WALs.

➤ Distribute credit risk among various classes, creating bonds with the full spectrum of credit ratings, from the super-senior triple-As to the unrated bonds.

➤ Distribute prepayment risk among various classes. This distribution of prepayment risk is primarily of interest for fixed-rate bonds, which carry interest rate durations from one to seven years.

The structuring of classes with narrowly defined payment and credit characteristics broadens the pool of investors and leads to the best execution of the deal for the issuer.

Credit Enhancement

Securitized HEL deals in general do not carry government guarantees, such as that provided by the GSEs. Therefore, investors are subject to the full credit risk of the underlying mortgages. To address this risk, early HEL securitizations relied on bond insurance policies underwritten by highly rated insurers. (These policies are referred to as monoline wraps.) Over time, these “external” mechanisms of credit protection were largely replaced by “internal” mechanisms, whereby the credit risk in a deal is allocated between securitized bonds and residual cash flows. The internal mechanisms take the form of a senior/subordinate structure of the cash flows (senior/sub for short).

Hybrid forms of credit enhancement have also been used. The most common of these is a combination of a senior/sub structure and lender-paid mortgage insurance. In this approach the lender pays an insurer to cover a subset of loans in the deal up to a specified loss level. This partial insurance coverage, in turn, reduces the required amount of subordination, excess spread, or overcollateralization. In another hybrid approach, a bond insurer steps in to insure only some classes in a deal that already has a senior/sub structure. This approach makes it possible to carve out classes with only corporate credit exposure.

The Senior/Subordinate Structure Owing to strong investor appetite for subordinate debt, the senior/sub structure is currently the most common from of credit enhancement of HEL deals. It accounts for more than 95% of current issuance. The senior/sub structure provides credit enhancement through three mechanisms:

All HEL deals in the ABS market are structured.

HEL investors are subject to the credit risk

of the underlying mortgages; the

senior/sub structure allocates this risk.

Hybrid credit enhancement combines the senior/sub structure

and lender-paid mortgage insurance.

More than 95% of recent deals have the

senior/sub structure.



1 Subordination;

2 Overcollateralization (OC); and

3 Excess spread.

All three mechanisms coexist in a deal, and the size of each one changes from month to month.

Definition of Subordination

Subordination means that payments of interest and principal on the classes in the deal are ordered according to some priority. If in a given month the amount of available cash is insufficient to cover the full interest and principal payments on all the classes, the classes with a higher priority get paid in full, while some of the classes with a lower priority experience an interest or principal shortfall. Bonds that have a higher priority of payments carry a higher credit rating.

Definition of Overcollateralization

OC is the excess of collateral balance in a deal over the face amount of the bonds. Deals can either be issued with an initial OC, or the OC can be built up to some target level by using excess spread to accelerate the paydown of bonds.

Definition of Excess Spread

Excess spread is the difference between the gross coupon on the loans, adjusted for servicing and other fees, and the average coupon on the bonds. A typical servicing fee is 50bp per year and the trustee and other administrative fees are generally less than 2bp. Excess spread is the first line of credit protection in any HEL deal. In older deals there were sometimes triple-A rated interest-only (IO) bonds (called NAS IOs) that were carved out of the excess spread, effectively reducing the excess spread for all of the other bonds. This structure has largely disappeared in recent originations because of the compression of excess spread and better execution of net interest margin securities.

Deal Structure

Figure 33 shows the structure of a typical recent HEL deal. There are five senior classes rated triple-A (A-I-1, A-I-2, A-I-3, A-II-1, and A-II-2), six mezzanine classes with different credit ratings (M1-M6), and the subordinate class B, which is rated double-B. The senior classes have the highest priority of payment, followed by mezzanine classes in the order of increasing numerical designation, followed by the subordinate class. Below the subordinate class is the OC, and below the OC is the excess spread. In the ABS market, the triple-A rated classes are often referred to as the seniors, while the mezzanine and subordinate classes are collectively referred to as the subordinates.

A typical deal has classes rated triple-A

through double-B.



Figure 33. Typical HEL Deal Structure

A-I-1 AAA 18.8%

A-I-2 AAA 19.5%

A-I-3 AAA 1.2%

A-II-1AAA

35.6%

A-II-2AAA3.9%

Group I(non-conforming

balance)

M-1 AA 8.8% M-2 A 5.0%

M-3 A- 1.5%

M-4 BBB+ 1.4%

OC unrated 1.5%to NIM

M-5 BBB 1.1%

Excess Spread

Loss Position

Credit RiskGroup II

(conforming balance)

LastLoss

LowerRisk

FirstLoss

HigherRisk

Class A:

M-6 BBB- 0.7%

B BB+ 1.0%

Class M:

Class B:

Mortgage Loans: $550 MM

A-I-1 AAA 18.8%

A-I-2 AAA 19.5%

A-I-3 AAA 1.2%

A-II-1AAA

35.6%

A-II-2AAA3.9%

Group I(non-conforming

balance)

M-1 AA 8.8% M-2 A 5.0%

M-3 A- 1.5%

M-4 BBB+ 1.4%

OC unrated 1.5%to NIM

M-5 BBB 1.1%

Excess Spread

Loss Position

Credit RiskGroup II

(conforming balance)

LastLoss

LowerRisk

FirstLoss

HigherRisk

Class A:

M-6 BBB- 0.7%

B BB+ 1.0%

Class M:

Class B:

Mortgage Loans: $550 MM

Source: Citigroup.

Allocation of Losses

Losses in a given month are first allocated (taken out of) excess spread. If excess spread is not sufficient to cover losses, then the losses are taken out of the OC, by allowing principal payments from the excess collateral to cover interest payments on the bonds. If the OC is also not sufficient to cover losses, then the bonds get written down, starting from the bottom of the capital structure. (The amount of writedown is often called the Realized Loss Amount in a prospectus.) The credit risk of a bond is directly related to its position in the structure. For example, the principal on the class M1 does not get written down until the principal on classes B and M2-M6 has been written down to zero.

A bond that is written down may be written back up in a subsequent payment period, if excess spread becomes available. For example, suppose that the class B, which has a face amount of $5,500,000, is written down by $1,000,000 in month 20. If excess spread becomes available in the deal in month 21, then the bond will be written back up by the amount that is available in month 21. Reasons for the increase

Losses are first allocated to excess spread, then to

OC, and then to subordinate bonds.

A bond that is written down may be written

back up in a subsequent payment period.



of excess spread from month to month include an improvement in credit performance, and an increase in the interest payments by the borrowers (for example after a reset), or a combination of these factors.

Senior certificates do no get written down. They get paid whatever cash is available in a payment period after the payment of interest on all the certificates. This absence of a writedown has ramifications for the accrual of interest.

Interest on Writedowns, Certificates, and Notes

The majority of HEL bonds are issued in the legal form of certificates. For certificates on the mezzanine and subordinate classes, the current interest is not due on writedowns, and writedowns do not accrue interest. In the example above, the $1,000,000 writedown on class B does not accrue interest in month 20. The amount that is written back up in month 21 starts to earn interest from that point on.

Because there is no writedown of principal on senior certificates, they accrue interest on the full amount of principal outstanding. If the required interest payment is not available in a given month, the interest shortfall is made up in the subsequent payment period. This interest shortfall is paid very high in the priority of distributions, right after the current interest due on the seniors.

Many HEL issuers converted to REIT status in the last two years, as we discuss in Appendix A. The deals issued by REITs are identical in structure to the deals issued by REMICS,11 except that the legal form of the HEL bonds is a note, rather than a certificate. The key distinction between notes and certificates is that the writedown on a certificate is replaced by the concept of principal deficiency on a note. Principal deficiencies work in the same way as writedowns, except that they continue to earn interest.

Level of Credit Enhancement

The amount of credit enhancement for each bond is determined by the rating agencies. It depends on the following factors:

1 Credit quality of the collateral;

2 Quality of the servicer; and

3 The presence of lender-paid mortgage insurance.

The rating agencies periodically update their baseline prepayment, loss, and interest rate assumptions to address the changing economic environment.

A typical credit structure of two recent HEL deals is shown in Figure 34. The percentage for each credit rating shows the sum of subordination and OC. Together, subordination and OC are referred to as “credit support,” or “hard credit enhancement,” or, confusingly, as “credit enhancement.” We will use the term credit support to distinguish it from the total credit enhancement, which includes excess spread. The credit support of 11% for the double-As means, for example, that the sum of principal balances of all the bonds rated below double-A, plus the OC is 11% of the deal balance. For the deal shown in Figure 33, the credit support of the

11

REMIC stands for Real Estate Mortgage Investment Conduit. This is the standard HEL structure we have been describing.

There is no writedown on seniors.

Writedowns do not accrue interest.

Principal deficiencies on notes accrue interest.

Initial typical credit support for a top-tier

issuer: 19% to triple-As, 11% to double-As, 6% to

single-As, 3% to triple-Bs, and 1.3% to

double-Bs.



M5 class is 3.2%. (This is the sum of 0.7%, 1.0%, and 1.5%.) The credit support of the seniors is 21.0%.

Figure 34. Typical Credit Enhancement for 2005 HEL Deals

Top Tier Issuer Mid-Tier Issuer

Class Initial Support Target Support Initial Support Target SupportTriple-A 19.0% 38.0% 25.0% 50.0%Double-A 11.0 22.0 14.0 28.0 Single-A 6.0 12.0 10.0 20.0 Triple-B 3.0 6.0 6.0 12.0 Double-B 1.3 2.6 1.8 3.5

Overcollateralization 1.3% 1.30% IB / 2.60% OB 1.75% of IB 1.75% IB / 3.5% OBInitial Excess Spread 350bp 260bp

IB = Initial Balance. OB = Outstanding Balance. Source: Citigroup.

The credit support of the lowest-rated class, which is rated double-B in Figure 33 and Figure 34, is the OC. Most new deals start with an initial OC, which is typically 1%–2%. Occasionally, a deal is issued with 0% initial OC. In that case, excess spread is used to accelerate the paydown of seniors within the first year or so (turboing of bonds) and build up the OC to the target level of 1%–2% of the original balance.

Top-tier HEL issuers generally have lower credit supports than mid-level issuers, because of higher collateral credit quality and their servicing record. As shown in Figure 34, the typical difference in the initial credit support is 6% to the triple-As. However, the variation between deals is large, with the initial credit support on triple-As ranging from about 17% to 30%. Credit support can be materially lower if the deal contains lender-paid mortgage insurance, as we discuss later in the article.

Initial excess spread for most HEL deals is now between 250bp and 350bp. If we assume a collateral WAL of three years, this excess spread could add as much as 9% of credit enhancement to the deal in a flat interest rate environment. However, if the credit performance in any payment period is satisfactory (to be defined below) and the OC target has been met, the excess spread for that payment period is released to the holder of residual securities, and is not available to cover losses in future payment periods.

Investors should be mindful of several factors when gauging their reliance on excess spread. These include the following:

➤ Because bonds reset monthly, while the underlying loans are hybrids, an increase in short rates during the loans’ fixed-rate period compresses excess spread. (See the discussion of the available funds cap in Appendix B.)

➤ The weighted-average margin on the bonds increases with deal seasoning because the lower-cost senior bonds are paid off first. As a result, deal seasoning thins out excess spread.

➤ Because higher-yielding loans naturally default at higher rates than the average loans in a pool, defaults act to lower the pool’s WAC and reduce excess spread.

➤ In a static interest rate scenario, higher-yielding loans tend to prepay at a faster rate owing to credit curing, reducing the spread cushion available to the deal.

The credit support of the lowest-rated class is

provided by OC.

Top-tier issuers generally require lower

credit support.

Initial excess for HEL deals is now between

250bp and 350bp.



Trends in Credit Enhancement

Subordination and Overcollateralization

The credit support of HEL deals has been mostly steady between 2000 and 2005. Figure 35 shows the average S&P initial credit support for triple-A, triple-B, and single-B classes, by quarter of issuance. The dip in credit support between the third quarter of 2000 and the second quarter of 2001 was caused by popularity of lender-paid mortgage insurance. Although single-B rated bonds are rarely issued, the single-B level of support is the amount that would be needed to absorb the expected amount of losses, without any stress.

Figure 35. Credit Support on S&P Rated HEL Deals, 1Q 00–1Q 05

0.0

5.0

10.0

15.0

20.0

25.0

30.0


AAA Floating AAA Fixed BBB Floating BBB FixedB Floating B Fixed

Source: Citigroup.

The majority of HEL deals issued today contain floating-rate bonds that are backed by a mixture of fixed- and floating-rate collateral. The percentage of fixed-rate collateral backing floating-rate bonds rarely exceeds 20%. For these deals — called mixed deals — the credit enhancement falls between the fixed- and floating-rate lines shown in Figure 35.

The average credit support increased in the first quarter of 2005 compared to the fourth quarter of 2005. For example, the support of triple-A floaters increased from 21.5% to 23.4%, and the support of triple-A fixed-rates increased from 16.2% to 20.1%. Several factors are responsible for the increase, including the following:

1 More stringent interest rate stresses, which S&P started applying on November 1, 2005. These stresses reduce the credit enhancement value of excess spread, requiring additional subordination and OC for each credit rating. Other rating agencies also strengthened their interest rate stresses in 2005.

2 A higher proportion of IO loans in subprime pools, as we discussed in the collateral section. S&P started requiring higher supports for IOs in February 2005. Other rating agencies also require higher credit support for IOs.

3 Growth of limited or no-documentation loans between 2004 and 2005.

4 Random variation of support levels from quarter to quarter, owing to the specifics of individual deals.

The initial credit support has been mostly steady between 2000 and 2005.

For mixed deals, the credit support is

between the fixed- and floating-rate levels.

The average credit support increased in

2005.



Hypertranching

In a continued quest to tailor the bonds to investors’ needs and thereby optimize deal execution, issuers have been turning to ever-finer tranching of deals in the last two years. This process is called hypertranching. Whereas older deals may have included three or four subordinates, current deals have as many as 12 subordinate tranches (classes) with different, and often split, credit ratings. The differentiation of criteria between the rating agencies has contributed to this trend. Investors should be aware that, conditional on a loss occurring, thinner subordinate tranches imply higher bond loss severities.

Excess Spread

Excess spread on new-issue floating-rate deals has declined steeply in the past 18 months, as one-month LIBOR increased by about 275bp, while the initial WACs on subprime hybrids declined by about 80bp (see Figure 10). Competition among lenders has been the driving factor behind the compression of the WAC-LIBOR spread. However, the tightening of secondary market HEL spreads has partly offset the WAC-LIBOR spread compression. Figure 36 shows the history of excess spread at origination for a large subprime issuer. In this case the drop of excess spread between April 2004 and June 2005 was 187bp.

The drop in excess spread is more a challenge for deal structurers than investors. The spread compression was more than offset by the increase in the credit support we described earlier. As a result, the 2005 HEL deals are more resilient to losses than the 2004 HEL deals.

Figure 36. Excess Spread on HEL Deals Securitized by a Large Issuer, Apr 00–Jun 05

3.0

3.5

4.0

4.5

5.0

5.5

6.0

Mar 00 Oct 00 May 01 Dec 01 Jul 02 Feb 03 Sep 03 Apr 04 Nov 04 Jun 05

Exce

ss S

prea

d (%

)

Source: Citigroup.

Cash Flows in the Senior/Subordinate Structure Almost all HEL deals stipulate monthly payment of interest and principal to the bondholders. The available funds eligible for distribution include the following:

1 Scheduled interest and principal payments by the borrowers;

2 Prepaid principal in the current payment period, including recoveries on defaulted loans;

Current deals have as many as 12 subordinate

classes with different credit ratings.

Excess spread has declined in the last 15

months.

The increase in credit support offsets the drop

in excess spread.



3 Servicer advances on delinquent loans;

4 Compensating interest that covers interest shortfalls on loans that prepaid prior to the end of the month;

5 Payments received from insurance guarantees, if any; and

6 Payments from swap or cap contracts, if any.

Prepayment penalties are excluded from this list. Those payments are usually earmarked for the holders of NIM certificates.

Definition of Servicer Advances

The master servicer is obligated to advance scheduled principal and interest on delinquent loans. The purpose of this provision is to add stability to the bond cash flows. It is not a form of credit protection, for two reasons:

1 The servicer is required to advance principal and interest only to the extent that it is deemed recoverable from the proceeds at loan liquidation; and

2 Servicer advances are the first to be reimbursed after loan liquidation. Because the servicer advances generally proceed until liquidation, the loss severity of defaulted loans is directly proportional to the time the loan spends in delinquency and foreclosure.

Some high-LTV deals and manufactured housing deals do not include servicing advances because the recovery on the loans is deemed uncertain.

The Waterfall

Distribution of available funds in any payment period is spelled out in the priority of payments (or cash flow waterfall) found in the prospectus. In reality, several waterfalls exist, each corresponding to a different category of funds: interest, principal, or excess funds. Furthermore, the order of principal payments depends on the seasoning of the deal. Until the stepdown date, which is the later of month 37 or when the credit support of seniors reaches its target, all principal payments are directed to the senior bonds in the structure. Following the stepdown date, the subordinates start to share the principal payments with the seniors, provided that several credit conditions are met.

A deal’s priority of payments can be classified according to whether interest and principal collections are merged and distributed in order of strict seniority (combined waterfalls or IPIP) or whether interest and principal are kept segregated in their own respective waterfalls, and paid according to substantially independent protocols (separate waterfalls or IIPP). Of these two structures, the separate waterfalls are far more common. Figure 37 illustrates the IIPP structure. As we pointed out, if there is insufficient cash in a payment period to cover all the interest and principal due on the bonds, the principal payments from the borrowers can be used to cover the interest payments on the bonds, generating a principal writedown on the subordinate certificates. In contrast to the interest and principal waterfalls, which are standard across deals, the payment priority of excess funds (if available) varies from deal to deal.

The master servicer is obligated to advance

scheduled principal and interest on delinquent loans.

In most deals there are separate waterfalls for the

distribution of principal, interest, and excess funds.



Figure 37. Distribution of Funds in HEL Deals

EXCESS FUNDS WATERFALL

AVAILABLE FUNDS

-stepdown ? Or Trigger Fail? Y N

NIM FUNDS

EXCESS FUNDS WATERFALL

AVAILABLE FUNDS

Pre-Stepdown? Or Trigger Fail?

SENIOR ONLY PRINCIPAL

Y N

NIM FUNDS

I P

INTEREST WATERFALL

SHARED PRINCIPAL WATERFALL

Source: Citigroup.

Distribution of Interest

The priority of interest distributions is straightforward. We outline the payments in the order of priority.

1 Servicing fee (typically 50bp), trustee fee (typically less than 1bp), and various small administrative fees;

2 Insurance premiums, if the deal has lender-paid insurance;

3 Payments to the swap counterparty, if the deal has an interest rate swap;

4 Pro-rata interest payment to the seniors;

5 Unpaid accrued interest on seniors from a prior distribution date;

6 Interest payments to the subordinates, sequentially; and

7 Remainder flows into the excess funds waterfall.

A notable difference between the seniors and the subordinates is the treatment of the unpaid interest from prior distribution dates. This unpaid interest is called interest carry forward amounts. Interest carry forwards on seniors are paid high in the waterfall, right after the current interest on seniors. Interest carry forwards on subordinates are paid from excess funds. The excess funds serve several purposes, which implies that even if excess funds are available, the subordinates may not be reimbursed for the full amount of interest carry forwards.

Available Funds Cap

All HEL deals limit the interest payment on the bonds in any period to the net WAC of the deal. The net WAC is the gross WAC minus the required payments, which include servicing and trustee fees, insurance premiums, and swap payments. This ceiling on bond coupons is called the net WAC cap or the Available Funds Cap (AFC). If the coupon exceeds the net WAC, the resulting shortfall may be disbursed lower in the priority of distributions, or it may be carried forward. The unpaid interest resulting from the net WAC cap is called LIBOR Carryover Amount or Net WAC Rate Carryover Amount or Unpaid Basis Risk Shortfall.

Interest carry forwards on seniors are paid high

in the waterfall.

Interest payments on the bonds are limited to the

net WAC cap.



Although the AFC is in effect for both fixed- and floating-rate bonds, it rarely plays a role for fixed-rate bonds. All fixed-rate bonds are backed by fixed-rate collateral, so the spread between the net WAC and the bond coupon is fixed at origination. A small deviation from this occurs after the stepdown date, when the coupon on the bonds increases, or when the high-coupon loans in the deal pay off, leading to a downward drift of the net WAC.

The AFC is very important for floating-rate bonds. The bonds are indexed to one-month LIBOR, and they reset monthly. The loans underlying the bonds are generally a mixture of fixed-rate loans and hybrids. As we explained in the collateral section, the hybrids typically carry a fixed coupon for two years. After the two years, the coupon resets every six months, subject to an initial and subsequent periodic caps. Therefore, in a sharp interest rate selloff, the coupon on the bonds may increase much faster than the coupons on the loans, leading to the capping out of the bonds.

The AFC risk is well illustrated with the actual numbers. According to Figure 9, the current WAC on 2/28 hybrids is 7.12% and the net WAC is 6.62%. If we start with the current value of one-month LIBOR of 4.00%, and add a margin of 25bp for three-year triple-As, we see that a 237bp selloff of one-month LIBOR within two years would lead to a capping out of triple-As. The cap is riskier for subordinates. For example, the coupon on double-B pluses is typically 250bp over one-month LIBOR, implying a near-instantaneous capping out double-Bs.12

Interest Rate Corridor

Almost all new HEL deals have some mechanism to reduce the risk of the AFC. The most common of these is the interest rate corridor. In this approach the issuer buys a cap on one-month LIBOR at a strike exactly at the level where the average bond coupons would get capped out. The issuer then recoups some of the cost of the cap by selling the cap at a higher strike. The effect of this transaction is to raise the AFC. The corridor is typically in effect for two to three years, until the hybrids start resetting. The notional balance on the corridor decreases with the deal pricing speed of 100PPV. The corridor is provided entirely by the issuer. No funds are directed from the deal to pay for the LIBOR caps. In Appendix B we discuss corridors and the AFC in detail.

The effect of the corridor is significant. For seniors the effective cap is raised to 10%–11% over the first two years, while for subordinates the effective cap is raised to 9%–10%. Figure 38 shows the effective net WAC cap from a recent HEL deal. Issuers typically provide separate corridors for seniors and subordinates. The notional balance on the corridor for subordinates does not decrease, because the bonds are locked out for at least three years.

12

Because new-issue double-Bs are sold at a discount, the initial DM is higher than the margin over one-month LIBOR.

The AFC is of small importance for fixed-rate

bonds.

The AFC is very important for floating-

rate bonds.

Without additional protection, triple-As

would cap out in a 237bp LIBOR selloff.

The most common protection for the AFC is the interest rate corridor.

The corridor raises the AFC on seniors to

10%–11% and for subordinates to 9%–10%.



Figure 38. Net WAC Cap With Maximum Corridor Payments for Triple-As and Mezzanines in Typical HEL Deal

9.5

10.0

10.5

11.0

11.5

12.0

12.5

0 10 20 30 40 50 60 70 80 90

Seniors Subordinates

Source: Citigroup.

Interest Rate Swaps

Another mechanism to deal with the AFC risk is the interest rate swap agreement. In the swap agreement, the HEL trust pays the swap counterparty a fixed rate and receives one-month LIBOR. There are several differences between the corridors and swap agreements:

➤ Fixed payments in the swap are made by the trust. Therefore, they initially subtract from the excess spread. The issuer provides the corridor.

➤ The notional balance on the swap agreement typically amortizes 15%–25% faster than the pricing speed. This feature avoids an excessive depletion of excess spread if prepayments are faster than the pricing speed, as is usually the case (see Figure 26).

➤ If the floating rate exceeds the fixed payment of the swap, the trust will receive net proceeds from the swap agreement, regardless of the cap on the bonds. Therefore, the swap agreement is also a form of credit protection, whereas the corridor is not.

The relative merits of the swap and cap agreements depend on many variables, including the path of interest rates, prepayments, and the timing of losses. Keeping all else equal, a selloff of interest rates that exceeds the forward curve benefits the deals with a swap agreement, and vice versa. Swap agreements have gained in popularity in 2005.

The Cleanup Call

All HEL deals have a cleanup call. The most common type of the cleanup call gives the issuer, or other holder of residual certificates, the right to call the deal at any time after the collateral principal balance reaches 10% of the original principal balance. All the bonds are called at par plus accrued interest. The cleanup call is an option of the issuer; it does not oblige the issuer to call the deal.

The deal is structured in such a way as to provide additional incentives to the issuer to exercise the call. The coupons on both fixed- and floating-rate bonds step up on

Interest rate swaps are a popular alternative to

corridors.

The cleanup call gives the issuer the right, but

not the obligation, to call the deal when the

balance falls to 10% of the original value.

Issuers have incentives to call the deal.



the call date. (The call date is often referred to as the Optional Termination Date.) The coupon step-ups are illustrated in Figure 39.

Figure 39. Coupon Step-Ups on Call Date Coupon Type Credit Rating After Step-Up Date

Floating/1ML + Margin Triple-A Margin -> 2 X Previous Margin Floating/1ML + Margin Subordinate Margin -> 1.5 X Previous Margin Fixed Triple-A Coupon - > Previous Coupon + 50bp Fixed Subordinate Coupon - > Previous Coupon + 50bp or no change

Source: Citigroup.

In addition to paying higher coupons, the issuer has an incentive to call the deal because the fixed administrative costs become an increasing percentage of the revenues as the collateral pays down. The issuer may fail to call the deal if its credit performance is very poor, so that the redemption of bonds at par does not make economic sense, or if the interest rates have risen steeply and have offset the increasing coupons on the bonds and the administrative burden. In the past few years, most of the cleanup calls have been exercised efficiently. Strong credit performance and generally falling interest rates have helped the trend.

One variation on the cleanup call is to mandate a trustee auction of the collateral within three months of the call date, if the issuer has failed to call the deal. The auction is successful only if the trustee can get sufficient funds to redeem all the bonds at par and pay the accrued interest. Another variation of the cleanup call is to set the call at 20%.

In the new-issue market all bonds are priced to call. However, in the secondary market, deep discounts, or bonds under credit stress are often priced to maturity.

Distribution of Principal to Seniors — Floating-Rate Bonds

The traditional floating-rate triple-a structure is simply a pass-through, in which all the principal allocated to seniors goes to a single class. Although pass-throughs are still common, several innovations have been developed over the past few years. They include the following:

1 Time-tranching of the cash flows to create sequential bonds (sequentials). Sequentials offer the investor a range of WALs and tighter payment windows compared to pass-throughs of the same WAL. They generally trade at a 3bp–4bp premium compared to pass-throughs.

2 Creation of super-senior classes within the triple-A cash flows. Super-seniors have the same payment characteristics as the companion bonds, which are also rated triple-A, except in the case where the losses are so severe that principal or interest shortfalls reach the seniors. In that case, the super-senior class has priority of distribution over the companion class.

3 Splitting of collateral into collateral groups, typically according to loan balance. Each collateral group then supports one group of triple-As. By contrast, the subordinates are typically cross-collateralized by several collateral groups.

The issuer may not call the deal if the credit

performance is poor, or if the loans are deep

discounts.

In the new-issue market all bonds are priced to call.

Common structures include pass-throughs,

sequentials, and a breakdown of collateral

into groups.



The grouping of collateral into loans with balances below the conforming limit and those above it is motivated by the GSEs’ active participation in the HEL market. Recently, GSEs have accounted for 35% of purchases of triple-A HEL floaters. The GSEs do not buy bonds backed by large-balance loans, and have some additional restrictions based on the credit profile of the loans.

The senior bonds in Figure 33 contain all of the characteristics we just described. Group I consists of $217 million of nonconforming balance loans and group II consists of $217 million on conforming balance loans. The classes A-I-1, A-I-2, and A-I-3 are sequentials, while the classes A-II-1 and A-II-2 are pass-throughs. The class A-II-1 is senior to A-II-2. At the deal pricing speed, the WALs and payment windows on the bonds are shown in Figure 40.

Figure 40. WALs and Payment Windows on Triple-A Floaters in a Typical HEL Deal

WAL (Years) Payment Window (Months)

Class Call Maturity Call Maturity

A-I-1 0.97 0.97 1 - 21 1 - 21A-I-2 2.96 3.04 21 - 71 21 - 97A-I-3 5.91 10.12 71 - 71 97 - 160A-II-1 2.10 2.27 1 - 71 1 - 161A-II-2 2.10 2.27 1 - 71 1 - 161

Source: Citigroup.

The cleanup call has no effect on the WAL of class A-I-1, and it has a small effect on the WALs of classes A-I-2, A-II-1, and A-II-2. However, it has a big impact on the WAL of the last sequential, which is the class A-I-3. If the call is not exercised, the WAL extends from 5.91 years to 10.12 years.

The cleanup call also affects the payment window of all the classes, except the A-I-1.Even for classes A-I-2, A-II-1, and A-II-2, a failure to call the deal gives the bonds a long tail of small principal payments. Sometimes the three-year sequential is structured in such a way so that it pays off prior to the cleanup call. A typical payment window in that case may be in months 19 through 68.

Figure 41 shows the principal payments on triple-A floaters introduced in Figure 40, with the cleanup call. The cash flows are computed at the deal pricing speed of 100PPV. The spike in principal payments after two years corresponds to the spike in prepayments following the two-year reset on the collateral. The class A-I-3 has only one principal payment, which occurs at the deal call date in month 71.

GSEs’ purchases of triple-A HEL floaters

motivate the breakdown of ARMs into groups

according to loan balance.

The cleanup call has a big impact only on the WAL

of the cash flow. . .

. . . however, if the deal is not called, most bonds

acquire a long tail.



Figure 41. Principal Payments With a Cleanup Call on Triple-A HEL Floaters (Dollars in Millions)

0

2

4

6

8

10

12

14

16

$18

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70

Dolla

rs in

Mill

ions

AI1 AI2 AII1 AII2

Source: Citigroup.

The gap in principal payments to the seniors, which occurs between months 37 and 50, is the result of a paydown of subordinates. If the stepdown tests pass and prepayments are fast, the structure directs the cash flows for several months only to the subordinates, in order to establish the target support levels for all classes. At fast prepayment speeds, the balance of seniors drops rapidly in the first 36 months, leading to the support levels that are above target in month 37. The paydown of subordinates then reduces the support levels to their specified targets. (More on this in the section on subordinates.)

Distribution of Principal to Seniors — Fixed-Rate Bonds

All fixed-rate triple-A cash flows have a sequential structure. The WALs of the bonds are one year, two years, three years, five years, and the last cash flow, with a WAL of 6.5–8.5 years, depending on deal. Sometimes the two-year bond is omitted and the short and three-year sequentials are combined. All the structures also contain a non-accelerated senior (NAS) class. The NAS typically has a WAL of 6.5 years and pays principal together with the other triple-As. Its share of the principal, however, follows a specified schedule. A typical schedule is shown in Figure 42. The lockout percentage is applied to the NAS pro-rata share of the senior principal distributions.

Figure 42. NAS Allocation of Its Pro-Rata Share of Senior Principal Distributions Payment Period Lockout Percentage

1 – 36 0%37 – 60 45%61 – 72 80%73 – 84 100%85 and thereafter 300%

Source: Citigroup.

As with floating-rate seniors, the WALs and payment windows on fixed-rate seniors depend on the cleanup call. Figure 43 shows the WALs and payment windows at pricing speed on a typical HEL deal, and Figure 44 shows the principal cash flows. At the deal pricing speed, the cleanup call pays off the outstanding balance of the

If prepayments are fast and the credit

performance is good, triple-As do not receive

principal for several months after the

stepdown date.

All fixed-rate triple-A cash flows have a

sequential structure.



NAS and the total balance of the long sequential (AF5). Compared to the three-year floating-rate sequential shown in Figure 40, the three-year fixed-rate sequential has a much tighter window. Window variability in fixed-rate deals is taken up by longer bonds, with WALs of five, six, or eight years.

Figure 43. WALs and Payment Windows on Triple-A Fixed-Rates in a Typical HEL Deal

WAL (Years) Payment Window (Months)

Class Call Maturity Call Maturity

AF1 0.87 0.87 1 - 18 1 - 18AF2 2.14 2.14 18 - 34 18 - 34AF3 3.16 3.15 34 - 43 34 - 43AF4 5.21 5.33 43 - 91 43 - 114AF5 7.58 12.97 91 - 91 114 - 233AF6 (NAS) 6.13 6.52 34 - 88 34 - 228

Source: Citigroup.

Figure 44. Principal Payments With a Cleanup Call on Triple-A Fixed-Rates (Dollars in Millions)

0

2

4

6

8

10

12

14

$16

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88

Dolla

rs in

Mill

ions

AF1B AF2 AF3 AF4 AF6

Source: Citigroup.

The purpose of the NAS principal payment schedule shown in Figure 42 is to increase the stability of its cash flows under different prepayment scenarios. If prepayments are faster than the pricing speed, and the principal is distributed to the bondholders earlier than expected, the NAS gets a smaller percentage of that principal than its pro-rate share. If prepayments are slower than the pricing speed, and the principal is distributed to the bondholders later than expected, the NAS gets a bigger percentage of that principal than its pro-rata share. In this way the structure adds stability to the NAS bond.

Because fixed-rate bonds carry a significant amount of interest rate duration, prepayments are much more important for their valuation than they are for floating-rate bonds. The NAS bond serves investors who want to limit their exposure to prepayment risk and are willing to pay a premium for it. The stability of the NAS bond comes at the expense of the other triple-A rated bonds in the structure, whose cash flows absorb the variability of the collateral cash flows in order to stabilize the NAS. We revisit the stability of the NAS bond in the section entitled “Valuation of HEL Securities.”

The NAS payment schedule is designed to increase the stability of

its cash flows.

NAS is suitable for investors who want

reduced prepayment exposure at the cost of

tighter spread.



Triggers

Stepdown tests, or triggers, determine if subordinate bonds receive principal starting on the stepdown date. In all HEL deals, the stepdown date, which is the later of month 37 or when the credit support of seniors reaches its target. The purpose of the triggers is to protect senior bondholders if the credit performance of the deal is poor. If triggers fail, all the principal payments are directed to seniors, lowering their percentage in the deal and therefore increasing the credit support of the remaining seniors. The triggers are tested each month, starting in month 37.

Almost all new HEL deals have a two-step trigger. Failure of either one of the conditions shuts off the principal to subordinates in that month. The following two conditions are standard:

➤ Sixty-plus day delinquencies cannot exceed a specified percentage of the current credit support of the most senior class outstanding. The sixty-plus day delinquencies include all loans that are at least 60 days delinquent, as well as loans that are in foreclosure, bankruptcy, or REO. The specified percentage is typically 35%–50%.

➤ Cumulative losses expressed as a percentage of the original deal balance have to be below loss targets. The loss targets can either step-up every 12 months, or they can increase each month according to a schedule. (The schedule is usually a straight-line interpolation between loss targets at 12-month intervals.) Figure 45 provides a sample schedule of cumulative loss targets.

Figure 45. Schedule of Cumulative Loss Targets for the Stepdown Test Payment Period Cumulative Loss Target (%)

1 – 36 NA37 – 48 3.0049 – 60 4.7561 – 72 5.7573 and thereafter 6.50

Source: Citigroup.

According to Moody’s, the loss targets are set as follows: If the lowest-rated bond in the structure has an investment-grade rating, the loss target is at a level where a bond two notches below it would lose the first dollar of principal. If the lowest-rated bond in the structure is rated below investment grade, then the loss target brings about a loss on the bond rated one notch below. These bond defaults assume a specific loss-timing curve, a path of interest rates, and a prepayment curve. These are described in the section on the rating agencies’ methodology.

Failure of the delinquency trigger is common in HEL deals, with about half of HEL deals failing the trigger at some point in their life. However, the delinquency trigger cures itself. Because failure of the trigger implies a paydown of seniors in that month, and therefore an automatic increase in their credit support, the trigger is more likely to pass in the subsequent month. For a deal with high delinquencies, the delinquency trigger may oscillate between passing and failing for many months.

Triggers determine if subordinates receive

principal starting on the stepdown date.

New HEL deals have a two-step tirgger.

The lowest-rated class in the deal does not default

if losses reach the cumulative loss trigger.

Failure of the delinquency trigger is

fairly common, but the trigger cures itself.



Failure of the cumulative loss trigger is a much more rare than failure of the delinquency trigger and indicates serious credit distress. Because the cumulative loss trigger is specified in terms of percentages of the original balance, rather than credit support, it is harder to cure than the delinquency trigger.

The delinquency triggers in older HEL deals were often specified in terms of absolute percentages, rather than percentages of credit enhancement. (For example, 60+ day delinquencies cannot exceed 18% of the outstanding balance.) These triggers, which are harder to cure, have not been included in HEL deals for the last two years. Older HEL deals sometimes also included triggers defined in terms of rolling three-month average of net losses. These are rare in new deals.

Distribution of Principal to Subordinates

The rules of principal distribution to subordinates are substantially the same for fixed- and floating-rate bonds. Apart from the prepayment speed and cleanup call, the key determinant of the payment windows and WALs is the stepdown test.

Stepdown Test Passes

If the stepdown test passes, principal can be directed to the subordinates and the OC can step down. The amount of principal distribution, if any, depends on the available credit support relative to the target support levels. The target support level for each class is almost always twice the original amount, expressed as a percentage of the outstanding balance. Figure 34 shows the target support levels for two HEL deals.

Based on the available credit support on stepdown date, we distinguish two cases.

Case I: Credit Support Exceeds Target

The actual credit support will exceed the target if prepayments are fast. In this case, all of the principal payments on and after the stepdown date are directed to the subordinates, until the target support levels are reached. After that, the seniors and subordinates are paid down pro-rata, so as to maintain the target enhancement levels.

The paydown of subordinate bonds occurs from the bottom up. First the target enhancement level is established for the lowest-rated bond in the structure (class B in Figure 33) by releasing the OC until the bond reaches its target enhancement level. Next, the lowest-rated bond and the OC are paid down until the next higher-rated bond reaches its target enhancement level, etc. (The class above the class B is the M6.)

Figure 46 shows the cash flows to the subordinate bonds in the deal introduced in Figure 33. First, the class B starts receiving principal, then the class M6, and so on. The gap in the cash flows in month 37 corresponds to the preferential paydown of OC in that month. In most HEL deals, the OC has a floor, which is typically 0.5% of the original deal balance.

Failure of the cumulative loss trigger is rare, and indicates serious credit

distress.

If the stepdown test passes, principal can

be directed to the subordinates.

If the credit support exceeds target, all of the

principal is directed to subordinates.



Figure 46. Principal Payments to Subordinates After Stepdown Date

0

2

4

6

8

10

12

14

16

$18

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70

Dolla

rs in

Mill

ions

Seniors M1 M2 M3 M4 M5 M6 B

Source: Citigroup.

The bottom-to-top paydown of subordinates means that the WAL of the lowest-rated bonds in the structure is slightly shorter than the WAL of higher-rated bonds. This is illustrated in Figure 47. The figure also shows the payment windows of all the subordinate bonds from Figure 33.

Figure 47. WALs and Payment Windows on Subordinates in a Typical HEL Deal WAL (Years) Payment Window (Months)

Class Credit Rating (M/S&P/Fitch) Call Maturity Call Maturity

M1 Aa2/AA/AA 4.47 4.89 42 – 71 42 – 134M2 A2/A/A 4.26 4.62 39 – 71 39 – 118M3 A3/A-/A- 4.21 4.50 39 – 71 39 – 102M4 Baa1/BBB+/BBB+ 4.18 4.42 38 – 71 38 – 95M5 Baa2/BBB/BBB 4.17 4.33 38 – 71 38 – 87M6 Baa3/BBB-/BBB- 4.15 4.21 37 – 71 37 – 78B Ba1/BB+/BB+ 4.00 4.00 37 – 71 37 – 71

Source: Citigroup.

Case II: Credit Support is Below Target

In the credit support is below the target on stepdown date, then all of the principal continues to be directed to the seniors, until the target support levels are reached. After that, and provided that the stepdown tests continue to pass, a portion of the principal will be directed to the subordinates. There is no interruption of principal cash flows to the seniors.

The actual credit support is below the target on stepdown date if the prepayment speeds are significantly slower than the deal pricing speed. This case of slow prepayments illustrates the fact that the passage of a stepdown test does not guarantee payment of principal to subordinates.

Stepdown Test Fails for Life

If the stepdown test fails for life, the structure becomes purely sequential. Seniors are paid off first, followed by the M1 class, then the M2 class, and so on. (The distribution of principal among the senior classes is unaffected by the trigger.) Compared to the stepdown-pass scenario, the WAL of the seniors shortens, while the

WALs of lower-rated bonds are shorter.

If the credit support is below target, then all of the

principal continues to be directed to the seniors.

If the stepdown test fails for life, the structure becomes sequential.



WAL of the subordinates extends. The extension is the most severe on the lowest-rated bonds.

Realistic Failure of the Stepdown Test

Delinquency triggers, which fail much more often than cumulative loss triggers, cure themselves, as we explained in the section on triggers. Therefore, if a deal fails the delinquency trigger, it will typically fail for only a few of months, followed by a passage of the trigger. If the amount of 60+ day delinquencies stays high, the trigger will not pass for the life of the pool — it will flip back to failing after a few months. In this way the trigger may oscillate between passing and failing for an extended period.

The reason for trigger oscillation is a combination of trigger curing and the buildup of credit support in excess of the target during the months when the trigger is failing. When the trigger starts passing again, the first bonds to receive principal are the lowest-rated bonds in the structure.

Under realistic prepayments, the oscillation of the delinquency trigger leads to a non-intuitive pattern of bond paydowns. Far from a mere oddity, this payment pattern has real consequences on returns. Figure 48 shows the WALs of the long senior and subordinate bonds under three different trigger scenarios:

1 Trigger passes for life;

2 Sixty-plus day delinquencies are fixed at 30%, and the trigger oscillates between passing and failing; and

3 The trigger fails for life.

In each case we show the WALs of the bonds to call and to maturity. To avoid the adjustments of cash flows due to losses, we do not include losses in the calculation.

Figure 48. Effect of Trigger Failure and Trigger Oscillation on WALs WAL (Years)

Call / Maturity

Class Credit Rating (M/S&P/Fitch) Pass for Life 30% Delinquencies Fail for LifeA-I-3 Aaa/AA/AA 5.9 / 10.1 5.9 / 8.6 4.0 / 4.0M1 Aa2/AA/AA 4.5 / 4.9 5.5 / 6.7 4.7 / 4.7M2 A2/A/A 4.3 / 4.6 4.6 / 5.0 5.8 / 6.0M5 Baa2/BBB/BBB 4.2 / 4.3 4.3 / 4.5 5.9 / 8.3B Ba1/BB+/BB+ 4.0 / 4.0 4.1 / 4.1 5.9 / 9.9

Source: Citigroup.

The key takeaways from Figure 48 are the following:

➤ Failure of the trigger always shortens the seniors and extends the subordinates.

➤ If the trigger fails for life, the lower-rated bonds have longer WALs.

➤ If the trigger oscillates between passing and failing, the highest-rated subordinates (class M1 in Figure 48) extend the most and the lowest-rated subordinates (class B in Figure 48) extend the least.

➤ If the trigger oscillates, the highly rated subordinates extend more than in the trigger-fail-for-life scenario, while the lowest rates subordinates extend much less than in the trigger-fail-for-life scenario.

If delinquencies are high, the trigger may oscillate

between passing and failing for an extended

time.

Trigger oscillation has consequences for

returns.



Therefore, in a realistic scenario of trigger failure, the investor has less extension risk in lower-rated classes. However, this does not mean that the credit risk is lower in the lower-rated classes. In each payment period, the credit support for each class is at least as high as its target level, and the support is higher for higher-rated classes.13 Differences between the WALs of the bonds can be higher still for a non-constant delinquency curve. For simplicity we did not use such a curve.

Distribution of Excess Funds

After payment of all obligations mandated by the interest and principal waterfalls, the trust allocates the remaining funds (if any) according to the distribution of excess funds rules. Distribution of excess funds accomplishes the following goals:

1 Curing of various payment shortfalls on the rated certificates.

2 Release of leftover amounts to the residual holders.

The obligations included in the excess funds waterfall are fairly standard. They typically include the following:

➤ Paydown of bonds to cover any realized principal loss or writedown;

➤ Paydown of bonds to increase the OC;

➤ Reimbursement of current or prior interest shortfalls on the mezzanine bonds;

➤ Reimbursement that covers basis point shortfalls attributable to the AFC; and

➤ Payments to bondholders that cover shortfalls in the compensating interest paid by the servicer.

As a general rule, interest accrues on any interest shortfall so that interest-on-interest is paid. Interest on principal shortfalls follows the rules on notes and certificates we discussed earlier.

The order of payments of excess funds varies from deal to deal. Two variants are shown in Figure 49. In the standard scenario — shown on the left — each item in the list, such as principal losses and interest carry-forwards, is completely paid off to all the certificates before any reimbursements can be made under the next item. In other words, the payments are item-ordered. In the sequential scenario, which is less common, many items are grouped together and paid all at once to a single class before paying like amounts due to junior classes.

Even within the standard structure, there is variation in the order of payments. For example, some deals cover net realized losses at the top of the waterfall and others pay them at the bottom of the waterfall, just prior to the distributions made to the residual holders. These variations can lead to differences in performance of distressed deals and should be reviewed in such cases.

13

One criticism of the credit support argument is that for each dollar of the M1 class outstanding, the trigger oscillation reduces the number of dollars outstanding of the lower-rated classes.

In a realistic trigger failure scenario, the

investor has less extension risk in

lower-rated classes.

Excess funds include what is left after payment of principal and interest.

The order of payments of excess funds varies from

deal to deal.



Figure 49. Distribution of Excess Funds Profile Standard Excess Funds Waterfall Sequential Excess Funds Waterfall 1.

2.

3.

4.

5.

6.

7.

To cover realized principal losses on rated certificates.

To pay any O/C Increase amount to note certificates.

To pay mezzanine bonds an Interest Carry Forward Amts.

To pay, pro rata, Prepayment Interest Shortfalls allocated on that date not covered by master servicer; then any previously allocated unpaid prepayment interest shortfalls.

To pay, pro rata, the senior certificates, and only then, sequentially, the mezzanine certificates, any unpaid Basis Risk Shortfall Amt.

To pay any remaining unpaid realized losses.

To pay residuals any remaining balance.

1.

2.

3.

4.

To pay any O/C Increase amount to certificates.

To pay (a) unpaid Accrued Interest, (b) Interest Carry Forward, and (c) realized principal losses:

— First, to pay (a) and (b) to senior classes;

— Next, to pay (a), (b), and (c) to M-1 mezzanine;

— Next, to pay (a), (b), and (c) to M-2 mezzanine;

. . .

— Then, to pay (a), (b), and (c) to junior-most mezzanine;

First to senior classes, then sequentially to mezzanines any Basis Risk Shortfall Amt

To pay residuals any remaining balance.

Source: Citigroup.

Net Interest Margin Securities (NIMS) Net interest margin securities (NIMS) are structured from residual cash flows. They include the following components:

1 Excess spread;

2 Borrower payments of prepayment penalties;

3 The OC release;

4 Cash flows specifically designed to enhance the NIMS, such as a cap corridor (which is separate from the cap corridor used in the underlying deal to lift the AFC); and

5 Payments from the swap contract, if present in the underlying deal.

Figure 50 shows a typical NIMS structure.

Figure 50. Sources of NIM Cash Flows

Interest Rate Cap

Swap

Excess Spread

Prepayment Penalties (Class P)

(Classes CE and R)

Underlying

HEL Deal

NIM

AVAILABLE

FUNDS

NIM

Trust

and/or:

Source: Citigroup.



As the underlying HEL deal pays down and excess spread diminishes in dollar terms, NIMS payments decline over time. We show a schematic profile of NIM cash flows in Figure 51. NIMS cash flows do not have identifiable principal and interest components; instead the trust imputes principal and interest components to the NIM cash flow.

Figure 51. NIMS Payment Profile

NIM CF’sImputed P+I

HEL Bonds CF’s

Colla

tera

l Cas

h Fl

ows

Source: Citigroup.

The front-end NIMS, which typically include the first two years of NIM cash flows, are readily sold in the HEL market as private placement notes. They have fixed-rate coupons and carry a credit rating from at least one credit rating agency. The back-end NIMS are typically retained by the issuer. (The back-end NIMS are also called residuals.) Figure 52 shows the typical WALs and payment windows on tranched front-end NIMS.

Figure 52. WALs and Payment Windows on Securitized NIMS Credit Rating WAL Payment WindowClass Fitch (Years) (Months)A BBB 0.79 2 - 20B BBB- 1.72 20-22C BB+ 1.88 22-24

Source: Citigroup.

NIMS are the easiest way for originators to extract the investment they have locked up in the residual cash flows of the securitizations and to reduce their credit exposure to the underlying deals. Between the first quarter of 2000 and the second quarter of 2005 the most active NIMS issuers were Ameriquest with 71 issues, Lehman (SASCO) with 62, Option One with 27, Countrywide with 25, and Long Beach with 22.14

14

NIMS Quarterly Highlights: Second Quarter 2005 Issuance Volume Slowed as Performance Continues Ahead of Original Projections, Standard & Poor’s, August 17, 2005.

The front-end NIMS are readily sold as private

placement notes.

Many large HEL issuers also issue NIMS.



NIMS were introduced in the HEL market in the mid 1990s. Their structure has evolved since that time, making the cash flows more predictable. The key improvements include the following:

1 Introduction of prepayment penalty cash flows;

2 Structuring NIMS that are backed by only one underlying deal, thus reducing the dispersion of loan ages and other collateral characteristics;

3 Creating NIMS soon after the pricing of the deal, so that the collateral is relatively unseasoned;

4 Shortening the WALs of NIM notes;

5 Pricing the NIMS with more realistic prepayment and default curves (these curves often differ from the pricing curves for the underlying HEL deal);

6 Prefunding of OC in most HEL deals (the cash flows that are not used to build up the OC are directed to the NIMS);

7 Decreasing the size of NIMS relative to the underlying collateral; and

8 Introduction of interest rate caps.

These changes have led to a substantial improvement in performance of modern NIMS compared to the NIMS issued in the 1990s. For example, in the second quarter of 2005, the average NIM holder was repaid in 20 months, well ahead of the pricing projection of 28 months. The caps and swaps have effectively limited the impact of increases of short rates, while the strong credit performance has outweighed the negative effects of fast speeds. In the last section of the primer we discuss key NIMS valuation issues.

Other Forms of NIMS Credit Enhancement

NIMS occasionally have credit enhancement in addition to or in place of the credit enhancement provided by the senior/sub structure. One of these is the NIMS reserve account. The reserve account protects NIMS against credit losses and interest shortfalls. It is separate from any reserve account for the underlying deal. NIMS can also carry monoline insurance. In that case the NIMS interest and principal cash flows are guaranteed by a bond insurer, bringing the rating of the NIMS to double-A or triple-A. Lender-paid mortgage insurance on the underlying pool may also benefit the NIMS by reducing losses. This reduction in losses usually comes at the cost of lower excess spread.

Lender-Paid Mortgage Insurance — A Variation on the Senior/Subordinate Structure The popularity of lender-paid mortgage insurance (LPMI) has ebbed and flowed since its introduction in 2000. In 2001 it was used in more than 50% of new HEL deals; today it covers about 10% of HEL securitizations. The largest providers of LPMI for subprime mortgages are MGIC (rated Aa2/AA/AA+ by Moody’s, S&P, and Fitch), PMI (Aa2/AA/AA+), and Radian (Aa3/AA/AA).

NIM structures have improved since the 1990s, making cash

flows more predictable.

NIMS have been performing very well

recently.



LPMI is paid by the lender in order to reduce the credit risk and qualify for lower credit enhancement. Insurance is applied to individual loans, where it typically provides insurance coverage down to an effective LTV of 60%. In all securitized deals, LPMI is applied only to a subset of loans in the pool. The percentage of covered loans varies widely, from 25% to over 90%. In contrast to borrower-paid mortgage insurance, LPMI cannot be cancelled after the loan has amortized part of the way.

Coverage Percentage

The amount of insurance coverage on a loan is typically expressed in terms of “covered LTV.” This LTV is lower than the actual LTV of the loan and represents the effective LTV that the insured loan carries, before adding any cost incurred in the foreclosure. The coverage percentage is defined as:

Coverage Percentage = (Actual Original LTV-Covered LTV)/Actual Original LTV.

Coverage percentage is applied to the total insurance claim to determine the dollar amount of the insurer’s liability. The total insurance claim includes the defaulted loan balance, delinquent interest, and expenses incurred in the foreclosure. Effectively, LPMI reduces loss severity on defaulted loans.

The most common covered LTV is 60%. Sometimes issuers provide LPMI for all loans with original LTVs in excess of 80%, reducing them for the purposes of loss severity to 60%.

Claim Payment Options

Once an insurance claim has been submitted, the insurer has several options:

1 Pay the coverage percentage of the total insurance claim.

2 Pay the full claim amount and take title to the property.

3 Approve the sale of the property and pay the difference between the claim amount and the net sale proceeds. Other loss mitigation procedures, such as deed in lieu, may also be followed.

Mortgage insurers have a strong record of paying claims. For example, out of 3,100 claims submitted by Option One, fewer than 3% were denied or rescinded. Out of the 7,500 claims submitted by RFC, about 5% were denied. Fraud or misrepresentation of loan characteristics were the main reasons for the denial of coverage.

Policy Exclusions and Underwriting Criteria

LPMI policies carry a number of exclusions, including the following: (1) balloon loans, (2) negative amortization loans, (3) high-cost (Section 32) loans, (4) loans that are not first liens, (5) loans originated without down payment, (6) loans that are more than 30 days delinquent at the time the policy was purchased, (7) servicing performed by a non-approved servicer, (8) insurance claims submitted before the effective date of the policy, (9) claims arising from preexisting environmental conditions, and (10) loans collateralized by property that is only partially constructed.

In addition to these exclusions, mortgage insurers apply stringent selection criteria to the subprime loans they insure. Typically, the loan has to fall above specified cutoffs

LPMI is paid by the lender and results in

lower credit enhancement.

LPMI lowers the actual LTV to the covered LTV,

effectively reducing loss severity.

The most common covered LTV is 60%.

Mortgage insurers have a strong record of

paying claims.

LPMI policies carry a number of exclusions.

Mortgage insurers are selective about the loans

they insure.



on a grid of FICO scores and LTVs, and the borrower’s mortgage payment history has to be satisfactory. Other common criteria include maximum LTVs for a cash-out loan, limits on the debt-to-income ratio (commonly at 55%), and restrictions on the type of property collateralizing the loan (typically, only one-to-four unit residential properties are eligible). Most insurers also cap the maximum loan amount, at a level that is substantially higher than the average loan amount in the deal. The purpose of the cap limits is to limit the insurer’s exposure to any single loan.

LPMI and Credit Support

LPMI lowers the required credit support. Therefore, for the issuer the decision to purchase LPMI is based on a comparison of the lower support level with LPMI and the higher support level without LPMI. The expected execution of the transaction is also part of the decision process; at the moment, deals with and without LPMI trade about the same across all credit ratings. Figure 53 provides a dramatic comparison of the initial credit supports for two deals done by the same issuer six months apart. In CWL 2002-BC1, 97% of the loans carry LPMI. CWL 2002-BC3, by contrast, does not include LPMI.

Figure 53. Effect of LPMI on Initial Credit Support

Credit Support (%)

Deal Issue Date Aaa/AAA Aa2/AA A2/ACWL 2002-BC1 25 Feb 02 5.50 3.75 2.50CWL 2002-BC3 29 Aug 02 15.75 10.00 4.50

Source: Citigroup.

LPMI’s effect on credit support is evident in average industry support levels – see Figure 54. The left panel shows the percentage for deals with any level of LPMI. The right panel shows the industry average initial credit support to triple-As. The dip in credit support in 2001 clearly correlates with the high popularity of LPMI.

In addition to its diminished presence since 2001, in recent deals with LPMI, the insurance has covered a smaller percentage of loans than in the past. This is in part a reflection of the greater selectiveness of insurers and of higher insurance premiums. As well, the rating agencies appear to have become more restrictive in giving credit to LPMI.

LPMI lowers the required credit support.

LPMI’s effect on credit support is evident in

average industry support levels.



Figure 54. Negative Correlation Between Use of Mortgage Insurance and Credit Enhancement Levels Deal with Deep MI Credit Enhancement of Triple-As

0

10

20

30

40

50

60

Sep 00 Jun 01 Mar 02 Dec 02 Sep 03 Jun 04

Perc

ent (

%)

Deep MI (%)

10

20

30


LTV

(%)

Fixed Floating

Source: Citigroup.

Benefits and Risks of LPMI

LPMI diversifies credit enhancement in a deal. If the collateral credit performance is worse than expected, LPMI that covers a large fraction of loans in a deal and offers a welcome independent layer of protection compared to a senior/sub deal without LPMI. LPMI has been very effective at reducing loss severities on covered loans. Based on the Option One experience, for example, LPMI reduces the loss severities on covered loans from 42% to 17%.

Insurers that provide LPMI in general conduct detailed due diligence of the lender and servicer, providing an additional benefit to the bondholder.

Risks of LPMI to the HEL investor include the following:

➤ Concentration of credit risk in a small number of uninsured loans;

➤ Variance of loss severities, which reduces the effectiveness of LPMI, and

➤ Administrative errors by the servicer and trustee.

LPMI in general does not cover the riskiest loans in a pool. The risk to the investor is that the rating agencies may not fully recognize the magnitude of the credit risk carried by these loans, while the reduced credit support of the deal leaves less room for error.

Variance of loss severities from one defaulted loan to the next lowers the effectiveness of LPMI. Even if LPMI covered all the loans in a pool, and was sized such that the average loss severity was zero, the variation of loss severities from loan to loan would imply that some loans would be overinsured, while others would be underinsured. Based on the performance of LPMI to date, this has not turned out to be a major stumbling block.

If the trustee fails to pay the insurance premiums, LPMI could be canceled. As well, if the servicer fails to follow the insurer’s guidelines in the management of delinquencies and foreclosures, the insurance could be lowered or cancelled. For large HEL servicers, these risks have not been significant to date.

LPMI diversifies credit enhancement.

Additional due diligence of the servicer is another

benefit of LPMI.



Bond Insurance Bond insurance provided by highly rated insurance companies (monoline insurers) was once a dominant form of credit protection in HEL deals. Its importance has been greatly reduced, owing mostly to the investor appetite for subordinate bonds. Today, monoline insurance is sometimes used to provide additional protection on a class that is already part of a senior/subordinate structure. The insurance policy (wrap) provided by a monoline allows the investor to diversify his credit risk away from HEL credit to corporate credit.

The rating of a wrapped class is the same as the rating of the guarantor and is based on the guarantor’s explicit promise of timely payment of interest and ultimate payment of principal. The credit rating of the insurer is founded largely on the amount of capital available to pay claims, usually expressed as a “margin of safety” under a theoretical worst-case scenarios hypothesized by the rating agencies. For example, S&P requires a margin of safety of 1.25 times worst-case losses to obtain a triple-A rating.

Most of the bond insurers are rated triple-A. Figure 55 shows the credit rating and market share by insurer for the outstanding ABS bonds at the end of 2004. Across all ABS markets, which include autos, credit cards, and HELs, the total amount of wrapped bonds was $197 billion at the end of 2004. The recent insurance activity in HELs has been low. Only two deals in the first-half of 2005 featured full wraps, comprising roughly 2% of the issuance. Only seven deals used a partial wrap, accounting for another 1% of the issuance.15

Figure 55. Largest ABS Bond Insurers By Percentage of Insured Par

XLCA - AAA 9%

FSA - AAA15%

MBIA - AAA21%

FGIC - AAA 7%

CIFG AAA 4%Radian AA 5%

Ambac - AAA39%

Sources: Standard and Poor’s, Fitch Ratings, and Citigroup.

Their current low popularity notwithstanding, the monolines would likely be a key source of HEL market support in case of a severe credit downturn. During the liquidity crisis of 1998 and 1999, when most investors shied away from subordinate HEL bonds, the insurers continued providing credit protection. This outlet for credit risk made securitizations possible, providing a lifeline to lenders who depend on securitizations for their operations.

15

Asset Securitization Report, August. 1,2005. HELOCs are a major exception to the decline of monoline wraps. Of the $10 billion that priced in the first-half of 2005, roughly 85% was fully wrapped.

Monoline insurance has greatly diminished in popularity, owing to investor appetite for subordinate bonds.

The rating of a wrapped class is the same as the rating of the guarantor.

Monolines would likely be a key source of credit

support in a severe credit downturn.



Rating Agencies’ Methodology

The rating agencies typically arrive at the credit ratings for a HEL transaction through a two-step process. First, they determine net cumulative loss coverage and second, they perform bond cash flow analyses to evaluate credit for excess spread.

Cumulative Loss Coverage

The rating agencies determine the amount of credit support appropriate for each rating level based primarily on the quality of loans in the pool, but they also take into account additional factors such as the experience and past performances of the loan underwriter, issuer, and servicer.

The first task is to calculate expected losses for each loan in the pool. The loans are then aggregated to arrive at an expected cumulative loss assumption for the whole pool. This cumulative loss assumption is the basis for the sizing of credit support — each rating category requires credit enhancement that is a multiple of the loss expectation. Loss coverage rules-of-thumb for Moody’s and S&P are given in Figure 56.

Figure 56. Typical Required Loss Coverage for Moody’s and S&P Rating Level Moody’s S&PTriple-A 6x-8x 5x-8xTriple-B 1.5x-3x 2x-3x

Source: Citigroup.

The agencies consider two primary factors that contribute to the risk of loss on each loan:

1 Probability of default or “frequency of foreclosure” (FF); and

2 Loss severity upon default.

The loans in a portfolio are analyzed via an econometric model, using mortgage and credit file data, to determine the likelihood of default. The agencies start with a baseline assumption for the FF of any loan. This percentage is then adjusted up or down via multiplicative factors that depend on various loan risk characteristics. For example, let’s assume that the base FF is 15%. According to S&P, if the LTV of the loan is less than 80% the multiplier is 1.0; between 80% and 90% the multiplier is 1.5; between 90% and 95% the multiplier is 3.0; and between 90% and 100% the multiplier is 4.5. This means that if a loan has an LTV of 85%, then the FF is adjusted upwards to 22.5% (=1.5×15%). Similar multiplicative adjustments are made for other risk characteristics of the loans in order to arrive at the cumulative FF for a single loan.

The main factors considered by the models are the following: credit grades and FICO score, LTV, property type (single-family, multi-family, planned urban development, etc.), loan purpose (purchase, cash-out refinancing, interest rate refinancing), occupancy status (owner-occupied, investor property, second home), loan seasoning, loan balance, loan term, level of documentation, lien, and loan type (fixed, 2/28, 3/27, IO, or amortizing).

The rating agencies typically start with loss

coverage and then review the cash flows.

Collateral quality is the primary driver of ratings,

but quality of issuer, underwriter, and servicer

also matter.

The baseline FF is adjusted by multiplicative factors that account for the loan

characteristics.



Each loan is also assigned a loss severity, based on a similar econometric methodology. Given each loan’s FF and its projected loss severity, the ratings agency aggregates this information into an expectation of the pool cumulative loss.

Bond Cash Flow Analyses

Bond cash flow analysis follows the calculation of cumulative loss coverage. Its purpose is to estimate the amount of excess spread available for credit protection and for the buildup of OC. Then the subordination levels and class sizes are finalized.

Cumulative losses are a key variable in determining the excess spread. However, many other factors play a role, including the following:

➤ Timing of losses;

➤ Prepayments;

➤ Interest rate stresses;

➤ Triggers; and

➤ Evolution of pool collateral.

Timing of Losses

The timing of losses matters a great deal in determining the credit performance of HEL bonds, as we discuss in the section on valuation. The rating agencies use the loss seasoning curves shown in Figure 57. These curves are based on historical performance. The losses are displayed as a percentage of the lifetime cumulative loss.

Figure 57. Ratings Agencies’ Net Loss Curves As Percentage of Lifetime Cumulative Losses

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85+ Loan Age (Months)

% o

f Cum

ulat

ive

Loss

es

Fitch <=A+ Fitch >=AA- Moody's FRMs Moody's ARMs S&P

Source: Citigroup.

Prepayments

Prepayment CPR vectors assumed by the ratings agencies for 2/28 hybrid loans are shown in Figure 58. The curves represent the total prepayments, including voluntary prepayments and defaults. The basis risk in the transaction can be increased over time by assuming that ARMs prepay faster than fixed-rate loans, leading to an increase of fixed-rate concentration.

Bond cash flow analysis estimates the available

excess spread.



Figure 58. Ratings Agencies’ Prepayment Vectors for 2/28 Hybrid ARMs

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70

Loan Age (Months)

CPR

(%)

Fitch Moody's Baa2 Moody's Aaa S&P

Source: Citigroup.

Interest Rate Stresses

Interest rate stresses are used to assess the basis risk in a transaction and the corresponding compression of excess spread. Basis risk arises from the mismatch between the bond coupons, which reset monthly, and the loan coupons, which are fixed for the first two years and are subject to caps afterwards. Prior to 2005, the collateral backing floating-rate bonds has sometimes included as much as 40% of fixed-rate loans initially.

To stress the deals, all three ratings agencies assume steep increases in interest rates over at least the early part the life of the deal. Compared to the old interest rate vectors, which were updated in 2004, the new vectors assume a much steeper rise and much higher maximum values of one-month LIBOR and six-month LIBOR. Figure 59 gives the interest rate stress scenarios mandated for one-month LIBOR as of September 2005.16

16

See Rating Agencies Strengthen Interest Rate Stress Tests, I.Gjaja, Citigroup, August 8, 2004 for a discussion of the new interest rate vectors and their impact on credit enhancement.

Interest rate stresses assess the basis risk.



Figure 59. Ratings Agencies’ One-Month LIBOR Stress Vectors

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

1 13 25 37 49 61 73 85Loan Age (Months)

1-m

onth

LIB

OR (%

)

Fitch AAA Fitch BBB Moody's S&P AAA S&P BBB

Source: Citigroup.

Ratings Surveillance

The ratings agencies maintain surveillance programs to assess the ratings integrity of HEL bonds. These programs base their evaluation on a comparison of current and original credit support, an examination of the collateral and its performance to date, and on the evaluation of the threat to credit support from projected and/or stressed losses. All the information necessary for analyzing a transaction is contained in a monthly remittance report prepared by the servicer.

The surveillance process generally consists of quantitative tests of collateral and structural performance, which, if failed, invite increased scrutiny of the bond, the deal as a whole, and perhaps the issuing shelf. Failure of these tests alerts surveillance staff to potential credit threats, which may precipitate a re-rating action by the surveillance committee. For brevity and concreteness, we confine ourselves to a broad-brushed sketch of S&P’s subprime surveillance program.17 Similar methodologies are employed at the other ratings agencies.

17

US Residential Subprime Mortgage Criteria, Standard & Poor’s, September 2004.

Surveillance programs assess the ratings

integrity of HEL bonds.

Failure of quantitative tests invites further

scrutiny and may lead to a re-rating.



Figure 60. S&P’s HEL Deal Surveillance Tests

Source: Standard and Poor’s.

S&P’s surveillance program is founded on four basic tests of structural and collateral performance, which are summarized in Figure 60.

Test 1: A Trend Analysis of the Adequacy of Excess Spread to Cover Losses

If OC has been used to cover period losses in each of the three preceding months, test 1 is failed, indicating that excess spread is inadequate to cover losses. After failure of this test, S&P examines 12 months of delinquency performance and excess spread production to gauge the transaction’s capacity to reach its OC targets (if not already met) and its ability to continue to cover losses.

Test 2: An Analysis of the Certificate’s Current Credit Enhancement

When evaluating a transaction’s total credit enhancement, S&P includes 12 months of excess spread production, as determined by the pool’s prepayment experience over the previous 12 months. To arrive at a total credit enhancement percentage, the 12 months of excess interest in dollars is added to other forms of credit enhancement such as OC and subordination. Dividing the total credit enhancement in dollars by the outstanding collateral balance gives the total credit enhancement. If this total credit enhancement is less than the required enhancement percentage for the class, test 2 is failed, and the surveillance staff is alerted to the problem.



Test 3: A Trend Analysis of the Severely Delinquent Loans

S&P computes a three-month rolling average of loans that are 90-plus day delinquent (including loans in foreclosure and REO) and compares this amount with the certificate’s current credit support. If the average of 90-plus day delinquencies exceeds one-half the certificate’s current credit support percentage, test 3 is failed.

Test 4: Potential for Losses to Exceed a Certificate’s Credit Enhancement Over the Next 12 Months

S&P applies two separate stress tests, a standard loss stress test and a cash flow stress test.

1 In the first test, projected losses are calculated by foreclosing on delinquent loans at a rate that depends on the loan’s state of delinquency. Loss severities are based on the certificate’s seniority and the collateral’s concentration of second liens. The projected losses are then compared to the certificate’s current credit enhancement (including credit for excess interest) to gauge its ability to meet loss coverage requirements once losses on delinquent loans have been absorbed.

2 The cash flow stress test works as follows: All loans in foreclosure and REO are liquidated evenly over a 12-month period (with rating-dependent loss severity assumptions). Using similar assumptions for prepayments and cash flow models as in test 2, the net total credit enhancement after losses is computed in each of the subsequent 12 months. If losses exceed credit enhancement in any period, test 4 is failed.

Failing test 4 is especially significant, because that implies that a writedown of the lowest-rated bond is imminent. For this reason, a failure of test 4 alone may warrant a ratings downgrade.



Valuation of HEL Securities

HEL securities are exposed to credit risks and to the risk of extension or contraction. We discuss each one of these risk factors in turn.

Credit Risk

Level and Timing of Losses

Credit risk in a HEL transaction is shared between investors and the holders of NIM residuals. In general, little credit analysis outside of stepdown triggers is needed for triple-A and double-A rated bonds. However, investments in subinvestment grade securities involve a significant amount of credit exposure, which must be weighed against the higher yields. In all of the analyses, the key is to gauge the credit risk relative to the credit enhancement, rather than to simply estimate the level of collateral defaults.

Although the credit performance of securitized HEL pools has been improving steadily since the 2000 originations, as shown in Figure 16, credit questions have lately been receiving a lot of attention. Reasons include a possible slowdown of the housing market, rising short-term interest rates, and the growing popularity of interest only loans.

Term-Sheet Breakeven Default Rates

The first test of the bond’s credit risk is the breakeven analysis shown in the deal term sheet. In this case, the structuring team calculates a constant CDR at which the bond loses the first dollar of principal. The CDR calculation includes an assumption on loss severities and often includes an initial lag of 12 months. The lag means that CDRs are assumed to be zero for the first 12 months and then jump to the specified rate. The 12-month lag simulated the onset of defaults starting from zero. The runs are often displayed for several loss severities.

Figure 61 shows the typical breakeven analysis at the loss severity of 40% for all subordinates from a recent HEL deal. The figure shows the breakeven CDR for each bond and the cumulative loss in the deal at that CDR. Voluntary prepayments (that is, prepayment apart from defaults) are assumed to occur at the deal pricing speed, and the interest rates are assumed to follow the forward curve.

Figure 61. Typical Breakeven Scenario Analysis Class M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11Rating (M/S/F) Aa1/AA+/

AA+ Aa2/AA/

AA Aa3/AA-/

AA- A1/A+/

A+ A2/A/

AA3/A-/

A-Baa1/BBB+/

BBB+Baa2/BBB/

BBBBaa3/BBB-/

BBB- Ba1/BB+/

BB+ Ba2/BB/

BBLoss Severity 40% CDR (%)% 24.1 19.5 17.1 14.9 13.0 11.4 9.8 8.7 8.0 7.5 6.8

Cum Loss (%) 20.7 18.0 16.4 14.8 13.4 12.1 10.7 9.7 9.0 8.5 7.9

Source: Citigroup.

Little credit analysis outside of triggers is required for triple-As

and double-As.

The first test of the bond’s credit risk is the

breakeven analysis.



The Timing of Losses Matters

The static CDR breakeven calculation is a good starting point in the analysis. However, the timing of losses also matters for the credit stability of HEL subordinates. Losses that occur early in the life of the deal, known as front-loaded losses, are less stressful than back-loaded losses, which occur late in the life of the deal.

To illustrate the effect of loss timing, we rerun the breakeven calculation on the M10 and M11 classes shown in Figure 61, using the net loss curves shown in Figure 62. (The CDR curves are obtained by dividing the net loss curves by loss severity.) These curves are derived from Citigroup’s delinquency roll rate model under different assumptions for home price growth, prepayments, and interest rates. Low or negative home price growth generally makes the losses more back-loaded, in addition to raising the overall level of cumulative losses.18 We assume that voluntary prepayments occur at the deal pricing speed, and we scale the curves up or down to determine the breakeven loss on the classes M10 and M11.

Figure 62. Front-Loaded and Back-Loaded Net Loss Curves

0

1

2

3

4

5

6

0 12 24 36 48 60 72 84 96 108 120Deal Age (months)

Net L

oss

Rate

(%)

Front Loaded

Back Loaded

Source: Citigroup.

Back-loaded losses lead to defaults on bonds at lower cumulative losses, as Figure 63 shows. For the M11 bond the difference between front-loaded and back-loaded losses is 0.9% on the cumulative loss, which is 12% of the loss level. The difference between back-loaded losses and the flat CDR curve is greater — 1.2%. For the M11 class in Figure 63 the flat CDR corresponds to the highest breakeven level of cumulative losses. Back-loaded losses affect the bonds more because they occur when there is less excess spread in a deal.

The difference between front-loaded and back-loaded losses becomes more pronounced if the total prepayments are held constant between the runs, as opposed to holding the voluntary prepayments constant.

18

See How Much Do Losses Increase as Home Price Growth Slows Down, I.Gjaja and R.Singh, Citigroup, June 3, 2005.

Front-loaded losses are less stressful to the

bonds than back-loaded losses.

We rerun the breakeven analysis using the net

loss curves generated by Citigroup’s delinquency

roll rate model.

The M11 class breaks down at 6.7% with

back-loaded losses and at 7.9% with the flat

loss curve.



Figure 63. Comparison of Breakeven Cumulative Losses on the Double-B Bonds For Three Different CDR Curves Class M10 M11Rating (M/S/F) Ba1/BB+/BB+ Ba2/BB/BBLoss Severity 40% BECL Constant CDR (%) 8.5 7.9BECL Front Loaded Curve (%) 8.6 7.6BECL Back-Loaded Curve (%) 7.9 6.7

BECL: Breakeven Cumulative Loss. Source: Citigroup.

Loss-Adjusted Returns

The tradeoff of higher credit risk is always balanced by higher return in the absence of default. A typical analysis reviews the yields (returns) of bonds with different credit ratings under several loss, prepayment, and interest rate scenarios. For bonds that are near the bottom of the capital structure, the losses scenarios are the most important point of comparison.

As an illustration, we compare the WALs, yields, and principal losses for the triple-B minus and double-B plus rated bonds from two recent HEL deals under various loss and interest rate scenarios. The triple-B minus classes are priced at 230 DM and 100 PPV to call and the double-B classes at 700DM and 100 PPV to call. We assume that the voluntary prepayments take place at 100PPV and that the timing of losses is the same as in the historical average.19 Loss severities are set at 35% for both deals, which leads to baseline cumulative losses of 3.5% in deal 1 and 3.3% in deal 2. For the stress scenarios we increase the loss severities to 50% and multiply the default curves by a uniform scaling factor. The results are shown in Figure 64.

19

The HELLO Report, I. Gjaja and R. Joshi, Citigroup, September 9, 2005, provides the history of prepayments and losses for 13 large HEL issuers from 1997 to the present. The report is updated approximately bimonthly.

The tradeoff of higher credit risk is always

balanced by wider spread.

We compare loss-adjusted yields on

double-B and triple-B bonds.



Figure 64. Comparison of WALs, Yields, and Principal Losses on Triple-B Minus and Double-B Plus Bonds Under Different Credit Scenarios

Security /Credit Rating (S/M/F) /DM /Price

Deal 1 Deal 2

BB+/Ba1/BB+ BBB-/Baa3/BBB BBB-/Ba1/BB+ BBB/Baa3/BBB- 700bp/ $83.39 230bp/ $104.15 700bp/ $89.23 230bp/ $102.16

Bond P. Bond P. Bond P. Bond P. Cumulative Call/ Interest WAL Yield Loss WAL Yield Loss WAL Yield Loss WAL Yield LossLoss Trigger Rates (Yr) (%) (%) (Yr) (%) (%) (Yr) (%) (%) (Yr) (%) (%)0% Yes/Pass Forward-100bp 4.2 8.89 0 4.2 3.78 0 3.6 8.59 0 3.9 3.85 0 Forward 4.2 10.04 0 4.2 4.77 0 3.6 9.69 0 3.9 4.85 0 Forward+100bp 4.2 11.21 0 4.3 5.77 0 3.6 10.80 0 3.9 5.86 0 Forward+200bp 4.2 12.37 0 4.3 6.77 0 3.6 11.92 0 3.9 6.87 0 Forward+300bp 4.2 13.55 0 4.3 7.78 0 3.6 13.04 0 3.9 7.89 0

0% No/Fail Forward-100bp 9.1 6.84 0 8.1 4.57 0 10.2 7.19 0 9.0 4.61 0 Forward 9.1 7.97 0 8.2 5.56 0 10.3 8.27 0 9.0 5.61 0 Forward+100bp 9.1 9.11 0 8.2 6.55 0 10.3 9.36 0 9.0 6.61 0 Forward+200bp 9.1 10.26 0 8.2 7.54 0 10.3 10.46 0 9.0 7.61 0 Forward+300bp 9.1 11.41 0 8.2 8.44 0 10.3 11.56 0 9.1 8.62 0

Baseline No/Fail Forward-100bp 7.6 7.23 0 6.8 4.48 0 8.9 7.37 0 7.7 4.57 03.5% PPSI, Forward 7.6 8.36 0 6.8 5.47 0 8.9 8.46 0 7.7 5.57 03.3% RASC Forward+100bp 7.6 9.50 0 6.8 6.46 0 8.9 9.55 0 7.8 6.57 0 Forward+200bp 7.7 10.64 0 6.8 7.44 0 8.9 10.65 0 7.8 7.58 0 Forward+300bp 7.7 11.80 0 6.8 8.36 0 9.0 11.75 0 7.8 8.59 0

5% No/Fail Forward-100bp 7.8 7.20 0 7.0 4.52 0 8.8 7.39 0 7.7 4.58 0 Forward 7.9 8.32 0 7.0 5.52 0 8.8 8.48 0 7.7 5.58 0 Forward+100bp 7.9 9.45 0 7.1 6.52 0 8.9 9.57 0 7.7 6.58 0 Forward+200bp 7.9 10.58 0 7.1 7.51 0 8.9 10.65 0 7.8 7.58 0 Forward+300bp 8.1 11.71 0 7.2 8.43 0 9.6 11.44 0 8.2 8.46 0

6% No/Fail Forward-100bp 8.2 7.17 0 7.1 4.60 0 9.7 7.39 0 8.0 4.66 0 Forward 8.3 8.28 0 7.2 5.61 0 9.9 8.45 0 8.1 5.65 0 Forward+100bp 8.4 9.41 0 7.3 6.62 0 10.3 9.53 0 8.3 6.66 0 Forward+200bp 8.5 10.54 0 7.3 7.63 0 11.1 10.58 0 8.5 7.69 0 Forward+300bp 8.8 11.63 0 7.5 8.54 0 7.0 -0.23 79 10.5 8.72 0

7% No/Fail Forward-100bp 9.1 7.03 0 7.5 4.69 0 9.7 3.09 40 9.0 4.77 0 Forward 9.3 8.12 0 7.6 5.71 0 9.3 2.89 50 9.2 5.79 0 Forward+100bp 9.7 9.22 0 7.7 6.73 0 8.7 2.20 61 9.5 6.81 0 Forward+200bp 10.3 10.29 0 7.9 7.76 0 4.6 -28.30 100 11.4 7.69 3 Forward+300bp 12.1 10.81 4 8.4 8.36 0 3.1 -55.21 100 6.1 -5.51 85

8% No/Fail Forward-100bp 11.4 5.85 11 8.2 4.83 0 4.5 -42.20 100 10.5 3.73 13 Forward 11.1 5.78 24 8.4 5.75 0 4.3 -40.90 100 10.1 3.62 24 Forward+100bp 10.8 5.76 35 8.7 6.69 0 4.0 -42.25 100 9.2 2.08 45 Forward+200bp 10.1 5.10 49 9.0 7.56 0 3.2 -53.64 100 4.6 -33.92 100 Forward+300bp 8.9 2.85 70 9.8 8.40 0 2.5 -74.73 100 3.4 -54.34 100

9% No/Fail Forward-100bp 7.0 -6.45 87 10.1 5.08 0 3.6 -59.31 100 5.6 -13.43 93 Forward 6.0 -11.88 98 10.9 5.98 0 3.5 -56.45 100 4.8 -39.27 100 Forward+100bp 2.8 -26.21 100 11.4 6.29 8 3.2 -59.53 100 4.1 -46.38 100 Forward+200bp 5.0 -26.24 100 11.1 5.90 22 2.7 -69.46 100 3.4 -55.88 100 Forward+300bp 4.6 -26.98 100 10.4 4.44 43 2.1 -89.57 100 2.8 -69.72 100

Source: Citigroup.

Relative Value Part I: Is the Added Risk Worth It?

Through cumulative losses of 5%, the double-Bs outperform the triple-Bs under all interest rate scenarios. For example, at the cumulative loss of 5% and the forward curve, the double-B class from deal 1 carries a yield that is 2.80% higher than the yield on the triple-B class. Because we assume that triggers fail, the WAL of the double-B classes is slightly longer than the WAL of the triple-B classes.

In deal 1, the double-B is attractive relative to the triple-B through cumulative losses of 7%, regardless of the level of interest rates. However, the double-B bond loses its appeal at the loss level of 8% and interest rates above the forward curve. (The yields are equal at an 8% cumulative loss and at the forward curve, but the double-B is

For cumulative losses through 5%, double-Bs

are superior to triple-Bs in both deals.

In deal 1, the double-B outperforms the triple-B

through cumulative losses of 7%.



longer.) The principal on the triple-B class, by contrast, is safe through cumulative losses of 9%, provided the short rates do not exceed the forward curve. The relationship between the double-B and the triple-B bond in Deal 2 is similar, although both bonds default at a lower level of losses.

In summary, Figure 64 displays a tradeoff between losses and compensation for credit risk. Below a certain threshold level, the yield on a lower-rated bond implies superior returns. Once the bond starts to default, however, its yield advantage disappears. Citigroup has developed detailed loan-level models of HEL defaults that predict the credit performance of the loans based on the collateral characteristics and various macroeconomic inputs, such as HPA, unemployment, and the level of interest rates.

Relative Value Part II

The bonds in deal 2 default at lower cumulative losses than the bonds in deal 1. For example, the double-B class in deal 2 starts breaking down at the cumulative loss of 6% versus the cumulative loss of at least 7% for the double-B class in deal 1. A determination of relative value between the two deals requires a review of the collateral and the subordination levels. Again, a default model helps to carry out the comparison by relating expected losses to the collateral characteristics.

Relative Value Part III: Cross Sector Comparison

HEL bonds can be compared with other fixed-income sectors, such as corporate bonds, consumer ABS (such as credit cards and autos), CMBSs, and prime MBSs Spreads are compared across sectors within the same credit rating. HELs and other MBSs generally have wider spreads than alternatives. However, they also include payment windows (CMBSs, cards, and corporates are bullets or nearly bullets), prepayment risk, and structural complexities. Although some of these differences can be quantified, the comparison of different sectors is not a strict mathematical exercise. It also involves the investor’s preference for credit exposure — consumer versus corporate or CMBS, residential versus unsecured assets, etc.

Effect of Speeds on Losses

Fast prepayments in general benefit the credit performance of HEL securities. (They may be detrimental to NIMS, as we discuss under the heading of NIMS valuation.)

Outstanding Balance Reduction

Fast prepayments, irrespective of their cause, rapidly reduce the pool’s principal balance. Balance reduction implies lower losses, for the simple reason that a borrower who prepays his mortgage can no longer default on it.

Deleveraging

Fast prepayments cause fast deleveraging of HEL deals. Before the stepdown date, principal payments are directed exclusively to the senior classes, reducing their balance relative to the subordinates. As a result, the credit support of senior classes increases. The percent credit support increases for the subordinate classes as well, although the size of each subordinate class relative to the credit support does not change until the stepdown date. Nevertheless, the decrease of the senior classes is useful for subordinates: if the stepdown test fails, the wait to principal distribution is shorter.

The credit enhancements of deal 1 and deal 2

differ, requiring a view on collateral and

servicers.

HEL bonds can be compared with other

fixed-income sectors.

Fast prepayments cause fast deleveraging of HEL

deals.



Figure 65 shows a schematic of collateral and certificate balances at issuance and after 10% of the balance has paid off. (We assume that the prepays occurred prior to stepdown.) After prepayments have been applied, the balance of senior classes drops from $80 million to $70 million, the percentage OC cushion increases from 5% to 5.6%, and the senior credit enhancement increases from 20% to 22.2%.

Figure 65. Prepayments, Deleveraging, and Credit Support

Collateral

$100 MM80%

15%

5%

$90 MM

Certificates

At Issuance:

After 10% Prepays &

Amort.:

77.8%

16.7%

5.6%

O/C

O/C

Collateral

$100 MM80%

15%

5%

$90 MM

Certificates

At Issuance:

After 10% Prepays &

Amort.:

77.8%

16.7%

5.6%

O/C

O/C Source: Citigroup.

One drawback of deleveraging is the squeezing of excess spread. As the lower-coupon senior bonds pay off, the average coupon of the deal increases and excess spread becomes compressed.

Dynamic Pool Composition — Adverse Selection

While positive for the overall level of losses, higher prepayments often lead to a weakening of the credit composition of the remaining pool. As the pool undergoes prepayments, mortgagors with a higher propensity to refinance leave the pool at a faster rate. The key factors that increase speeds — high FICO, high loan balance, and low LTV — are also the factors that reduce the default rate. Therefore, as higher FICO borrowers prepay, the average FICO of the remaining pool drifts down. (The same applies for loan balances, LTVs, and other collateral characteristics.) This process is called adverse selection.

On a typical 2/28 hybrid pool, the drift in FICO scores is noticeable, but not dramatic — about 5–10 points over four years. However, the drop in average loan balances is steep: after four years, the average initial loan balance drops about $35,000. This is consistent with the prominent effect of loan balances on prepayments, as shown in Figure 29 (equity buildup) and Figure 30. Lower loan balances generate higher losses, as we showed in Figure 20.

Payoffs from Delinquency

Various features of the current mortgage landscape have been offering exit strategies for delinquent borrowers. Because of strong HPA, many delinquent borrowers have been able to sell their house and avoid foreclosure. Also, aggressive competition

One drawback of deleveraging is the

squeezing of excess spread.

Borrowers with high FICO scores and high loan balances prepay

faster, leading to adverse selection.

The drift in FICO is modest, but the drop in average loan balance is

steep, implying higher losses.

Strong HPA and lender competition have

enabled some borrowers to avoid foreclosure.



among lenders has meant that some delinquent borrowers have been able to refinance their loans on more favorable terms instead of defaulting. Product innovation has helped as well, by offering mortgages with lower monthly payments.

These exit strategies have led to voluntary prepayments on mortgages that might have otherwise defaulted. While clearly favorable for the credit performance of any deal, these trends bear watching because some of these prepayment opportunities may diminish in the future.

Downgrade Risk

Outright defaults on bonds rated triple-A and double-A are highly unlikely, as can be seen from several vantage points:

➤ The average industry HEL cumulative losses have been in the 3%–5% range, far below the 20%–25% initial credit support on triple-As and 11%–15% on double-As (excluding excess spread).

➤ Less than 1% of the rated RMBS classes have defaulted for performance reasons (0.95%), and all but three of the RMBS defaults had the original rating of BBB or lower.20

➤ As of November 2004, only three AAA-rated RMBS classes have ever defaulted, with the last one occurring in 1998 on a deal from 1991.

Even though highly rated certificates are unlikely to suffer losses, poor collateral or structural performance may subject them to a ratings downgrade. For mark-to-market portfolios the negative rating event may be disastrous, leading to large spread widening and trading losses. Further down the credit curve, the rating downgrades become slightly more common, and need to be considered in addition to the default risk.

HEL credit ratings have been extremely stable in the past. Figure 66 shows the one-year ratings transition matrices for HEL deals based on Fitch ratings from 1991 to 2004, on Moody’s ratings from 1990 to 2004, and on S&P ratings for all RMBS deals (including subprime, prime and alt-A) from 1978 to 2004.21 Triple-As suffer hardly any downgrades — 0% according to Fitch and 0.1% according to Moody’s and S&P. The one-year downgrade risk of a double-A is also very low — 0.3% according to Fitch, 0.5% according to Moody’s, and 1.5% according to S&P. The risk of a downgrade increases for lower credit ratings, but nevertheless remains very low for all investment-grade securities.

20

U.S. RMBS Default History Shows Less Than 1% of Rated Classes Have Defaulted, Standard & Poor’s, November 18, 2004. This study includes all nonagency mortgages, including HELs.

21Fitch Ratings 1991-2004 Structured Finance Transition Study, Fitch Ratings, March 22, 2005; Structured Finance Rating

Transitions: 1983-2004, Moody’s Investor Services, February 2005; Rating Transitions 2004: U.S. RMBS Stellar Performance Continues to Set Records, Standard & Poor’s, January 21, 2005.

Defaults on triple-A and double-A rated bonds are

highly unlikely.

HEL credit ratings have been extremely stable in

the past.



Figure 66. Average Annual HEL and RMBS Rating Transition Matrix Fitch's One-Year HEL Ratings Transitions 1991 to 2004

To

From AAA AA A BBB BB B CCC CC and belowAAA 100.00 0 0 0 0 0 0 0AA 2.76 96.93 0.24 0.03 0 0.03 0 0A 0.36 2.31 95.33 1.71 0.07 0.21 0 0BBB 0.10 0.31 0.88 94.04 1.23 1.87 0.92 0.92BB 0.40 0 10.00 2.20 86.40 4.40 2.20 3.40B 0 0 0.24 0.72 2.42 75.12 7.00 14.49CCC 0 0 0 0 0 0 59.34 40.66

Moody's One-year HEL Ratings Transitions 1990 to 2004

To

From Aaa Aa A Baa Ba B Caa or below WR

Aaa 94.56 0.11 0 0 0 0 0 5.33Aa 2.11 93.67 0.43 0.00 0.04 0.00 0 3.75A 0.43 1.65 93.52 1.26 0.35 0.04 0.04 2.71Baa 0.07 0.18 0.91 92.41 2.07 0.76 0.84 2.76Ba 0 0.18 0.53 3.35 84.51 2.11 5.99 3.35B 0 0 0.44 0.88 1.33 85.84 8.41 3.10Caa or below 0 0 0 0 0 0 82.35 17.65

S&P's One-year All RMBS Ratings Transitions 1978 to 2004

To

From AAA AA A BBB BB B CCC CC and below

AAA 99.90 0.10 0.01 0.01 0 0 0 0AA 8.00 90.60 1.20 0.10 0.10 0.04 0.03 0A 3.20 6.58 88.80 0.90 0.20 0.05 0.20 0.01BBB 0.70 3.90 4.70 88.90 0.60 0.90 0.20 0.23BB 0.20 0.50 4.20 8.10 84.20 0.90 0.90 1.00B 0.10 0.20 0.10 2.20 4.90 88.00 2.20 2.30CCC 0 0.40 0 0 0 0 55.00 44.60CC 0 0 0 1.80 0 0 0 98.20C 0 0 0 0 0 0 0 100.00

WR: Rating withdrawn. In most cases the bond has paid off. Sources: Fitch Ratings, Moody’s, S&P’s, and Citigroup.

Other Credit Risks

Shelf and Industry Risk

The poor credit performance of a deal may arise from systemic problems with the issuer or even with the whole HEL industry. Issuer risks include poor loan underwriting and servicing. Issuer risks have led to correlations between downgrades of deals securitized on the same shelf. A downgrade on one deal implies greater risk that the bonds in another deal done by the same issuer will be downgraded.

Industry-wide risk was a more significant factor in the late 1990s, when many HEL lenders and servicers were small specialty-finance companies pursuing the same business strategy. It has diminished over the past five years with the increasing diversification of the lender and issuer pool (see Figure 5).

Liquidity Risk

An adverse rating action on a deal or a sustained period of poor credit performance invariably impairs liquidity on all the classes. The gapping of the bid-offer spread is usually the most severe in the lowest-rated classes. However, the liquidity risk is not simply tied to the credit performance of a deal; a key role is played by the prevailing market conditions, away from a specific deal.

Poor credit performance may arise from systemic problems with the issuer

or even with the whole HEL industry.



Prepayment Risk There are three reasons for the uncertainty of cash flows on HEL bonds:

1 Cleanup call

2 Triggers

3 Prepayments

If the cleanup call is not exercised, the bonds that have not paid off extend, as we discussed in the section entitled “HEL Deal Structures.” In that section we also discussed the role of stepdown triggers. Failure of the trigger always shortens the seniors and extends the subordinates, although its effect on the various subordinates depends sensitively on the number of trigger passes and failures (see Figure 48).

Prepayments and Fixed-Rate Bonds

The variability of WAL is important for fixed-rate HEL bonds, because they carry interest rate durations as long as eight years and because extensions and contractions are correlated with interest rate movements. The bonds extend in interest rate selloffs and contract in interest rate rallies, implying negative convexities. Negative convexities, in turn, require higher yields to make the bonds attractive relative to bullet securities of the same duration.

The HEL refinancing curve implies a variability of WALs sequentials of as much as five years in a 200bp interest rate shift. Citigroup’s fixed-rate HEL prepayment model can be used to predict these changes of WALs. Figure 67 shows model prepayment projections for several parallel shifts of the swap curve. Figure 68 then shows the WALs of securities in RASC 2004-KS3, computed from the prepayment model.

Figure 67. Prepayment HEL Model Projections for Static Interest Rate Scenarios -200bp -100bp Unchanged +100bp +200bp

Long-Term CPR (%) 33.8 27.4 21.2 17.7 13.6One-Year CPR (%) 19.6 15.6 13.1 11.8 10.3

Source: Citigroup.

Figure 68. WALs of Triple-As and Subordinates Under Different Interest Rate Scenarios Change From Pct Class -200bp -100bp Unchanged +100bp +200bp +200bp to 0bp Change RASC 2004-KS3 AI2 1.13Yr 1.36Yr 1.68Yr 1.99Yr 2.35Yr 0.67Yr 40%AI3 1.58 1.99 2.51 3.09 3.79 1.28 51 AI4 2.16 2.91 4.30 5.94 7.98 3.68 86 AI5 3.10 5.17 7.94 10.59 12.71 4.77 60 AI6 4.65 5.49 6.41 6.86 7.20 0.79 12 MI1 3.81 4.24 5.39 6.73 8.13 2.74 51 MI2 3.62 4.18 5.38 6.73 8.13 2.75 51 MI3 3.52 4.14 5.36 6.71 8.11 2.75 51

Source: Citigroup.

WALs on triple-A sequentials vary as much as five years

over a 200bp interest rate shift.



The five-year bond in Figure 68, RASC 2004-KS3 AI4, extends the most, with an 86% increase in WAL in a 200bp rate selloff. On an absolute basis, the last cash flow AI5 extends more (4.77 years versus 3.68 years for the AI4), but this extension of WAL is only 60% of the unchanged-rate WAL. Short sequentials and subordinates all extend between 40% and 51% in a 200bp rate selloff. By contrast, the NAS bond is very stable, extending less than 12% or 0.79 years over the same backup in rates. The stability of the NAS bond is due to its structure, as we discussed in the section on structures. It gains the stability of WAL in part at the expense of the AI4 class.

Pricing Convention for Fixed-Rate HELs

Fixed-rate HEL bonds are quoted as a nominal spread over the swap curve at the point of the WAL. On new deals, the WAL is calculated from the deal pricing speed. 23 HEP is the most common pricing speed for fixed-rate HELs, as we discussed in the section entitled “Collateral Performance.”

OAS

Because the HEL borrower has the option to prepay his mortgage at any time, the HEL investor is short the prepayment option. This option is readily valued when the prepayments arise from changes in interest rates, for two reasons:

1 All prepayment models take into account the dependence of prepayments on interest rates.

2 The fixed-income derivatives market provides every day a set of implied volatilities that can be used to value the prepayment option.

Prepayment risk in a fixed-rate bond can be quantified through the option-adjusted spread (OAS).22 The OAS provides a better comparison between HEL and bullet securities (such as credit cards) than the nominal spread. It is an adjustment of nominal spread for several factors, including the option cost, payment window, and the extension along the forward curve.

Figure 69 shows sample OASs on triple-A rated HEL bonds as well as several other reference sectors at the same effective duration (credit cards, agency pass-through MBSs, jumbo MBSs, and alt-A MBSs). Because the OASs are currently wider on HELs than on the reference sectors, the HEL bonds are attractive. Additional analyses, such as total rates of return over different interest rate scenarios, are typically carried out to confirm the relative value in HEL bonds.

Figure 69. Triple-A HEL OASs, Credit Card Spreads, and Agency TBAs Credit Card HEL FNMA Alt-A Jumbo PPV Nom- Nominal Effective ZV Option WAL (Years) Spread OAS 30-Year TBAs 30-Year 30-Year Spread (bp) Duration (Yr) Duration Spread (bp) Cost (bp)1.9 -4 2 -13 -11 25bp 1.87yr 2.29 19bp 17bp2.9 -3 1 -13 -6 -14 32 2.73 3.28 31 30 4.9 1 10 -7 -2 -19 70 4.30 5.05 68 58 7.4/12.7 6 39/27 1 -11 82 6.39 6.18 80 40 6.2(NAS) 6 21 45 5.26 5.36 43 22

Pricing date: September 20, 2005. Source: Citigroup.

22

See Anatomy of Subprime Mortgages OASs, I.Gjaja, Citigroup, August 9, 2002, and Guide to Mortgage-Backed Securities, L.Hayre and R.Young, Citigroup, November 3, 2004.

The five-year sequential extends the most; the

NAS extends the least.

The HEL investor is short the prepayment

option.

Wider OASs imply relative value, but

additional analyses are typically performed.



Nominal durations shown in Figure 69 are calculated holding the nominal spread constant, while the effective durations and effective convexities are calculated holding the OAS constant. (Effective durations and effective convexities are sometimes called option-adjusted durations, OADs and option-adjusted convexities, OACs.) The convexities on fixed-rate HEL bonds are negative, as expected.

Prepayments and Floating-Rate Bonds

The coupon on HEL floaters resets monthly and the bonds do not have any interest rate duration. Nevertheless, prepayments are important for several reasons, including the following:

1 Spread duration is directly related to prepayments.

2 The price of bonds that are not priced at par depends on prepayments.

3 Prepayments affect the cost of the AFC.

4 Prepayments are a key determinant of credit performance, as we discussed in the previous section.

Citigroup’s loan-level model of HEL ARM prepayments takes into account the collateral characteristics, interest rates, and HPA.

The slowdown of prepayment arising from interest rate selloffs causes significant duration extensions. For example, in a 200bp selloff, the durations on long triple-A floaters increase by as much as 2.1 years, while the durations on subordinates increase by as much as 0.7 years. A slowdown of HPA and the associated slowdown of prepayments also cause durations to extend. The effect can be as high as 2.8 years of extension on long triple-As for a 15% slowdown of HPA.23 Figure 70 shows the effect of interest rate and HPA shifts on spread durations for a long triple-A bond and a triple-B bond from a recent HEL deals. For both bonds, the spread durations are shorter under most interest rate and HPA scenarios than the duration computed from the deal pricing speed of 100PPV.

Figure 70. Variation of Spread Durations With Interest Rates and HPA for the A3 and M8 Classes From RASC 2005-KS7 Last Triple-A Cash Flow Triple-B

1.5

2.5

3.5

4.5

5.5

6.5

-200 -100 0 100 200

Yield Curve Shift (bp)

Spre

ad D

urat

ion

(Yr)

0% HPA 15% HPA 100PPV

1.5

2.0

2.5

3.0

3.5

4.0

-200 -100 0 100 200

Yield Curve Shift (bp)

Spre

ad D

urat

ion

(Yr)

0% HPA 15% HPA 100PPV

Source: Citigroup.

23

For a detailed discussion of the relationship between prepayments, spread durations, and prices in HEL floaters see Effect of Interest Rates and Home Price Growth on the Valuation of HEL Floaters, I.Gjaja and O.Beeldres, Citigroup, September 9, 2005.

Interest rate selloffs and slowdowns of HPA imply duration extensions that

can exceed two years.



Apart from spread durations, prepayments can have a material impact on the pricing of bonds away from par. Secondary positions are priced away from par because of spread movements, and all new-issue bonds with a rating of double-B plus or below are priced as discounts. Typically, the coupons on sub-investment grade bonds are set at 250bp–300bp over LIBOR, implying price discounts of at least 10 points. (The current discount margin on a new-issue double-B plus is about 575bp.)

To illustrate the effect of speeds on discounts, we consider a five-year subinvestment-grade bond that trades at $86 and carries a DM of 850bp. The slowdown of prepayments due to a 200bp interest rate selloff implies a change in price of $3.5, which is worth 125bp on the DM. Similarly, a change in prepayments due to a slowdown of the housing market from 15% HPA to 0% HPA is worth about 140bp on the DM.

Even bonds trading at higher prices are affected by prepayments. For example, on a seven-year triple-A bond with a price of $99 and a DM of 87bp, a 200bp selloff in interest rates can be worth more than 40bp on the DM. (This pricing may arise if the spread on the last triple-A cash flow widened by 50bp.) For a more detailed analysis of the relationship between prepayments and the pricing of floating-rate HEL bonds the reader should review the reference in footnote 23.

Available Funds Cap

We discuss the valuation of AFC in Appendix B.

Valuation of NIMS As we pointed out in the section on structures, the NIMS cash flows come from the following sources: (1) excess spread; (2) borrower payments of prepayment penalties; (3) OC release; (4) NIMS cap corridors; and (5) payments from the swap contract on the underlying deal, if present. These cash flows depend strongly on both the prepayment and credit performance of the loans, making the valuation on NIMS challenging. The task is easier for NIM notes, which typically include only the first two years of the cash flows.

The key risks of NIMS are the following:

➤ Prepayments. Fast prepayments reduce the outstanding balance of the collateral, lower the dollar amount of excess spread and extend the NIMS. The risk of fast prepayment is partially offset by prepayment penalties. Because the NIM notes receive the penalty cash flows, faster speeds imply higher penalty collections. As well, prepayment penalties tend to slow down prepayments.

➤ Level and timing of losses. Losses reduce the excess spread and extend the NIMS High losses can also lead to trigger failure, which prevents the release of OC to the NIMS holder (if the OC is needed to pay off the NIMS.

The timing of losses also matters. For the holder of securitized NIM notes, the calculation is simple: expect that the NIMS pays off before significant losses are realized on the deal. For the NIM residual holder (which is typically the issuer), the question of timing is more complicated. It is combined with the timing of delinquencies and determines when the cash flows in the underlying HEL deal are released to the residual holders and when they are released to the bondholders.

Prepayments can have a material impact on the pricing of bonds away

from par, from the long triple-As to the

double-Bs.

The timing of losses matters mostly for NIMS

residuals.



➤ Interest rates. The level of interest rates affects prepayments and therefore the performance of the NIM. However, a sharp selloff can compress the excess spread, as described in Appendix B. Similarly, an interest rate rally can increase the excess spread and shorten the NIMS.

➤ Level of OC funding at deal issuance. Deals with prefunded OCs are more favorable to the NIMS holders, because the excess spread does not have to be diverted to the buildup of OC. Most new HEL deals include at least a partial prefunding of the OC.

The performance of NIMS also depends on the details of the cap and swap agreements. The cap agreements are similar to the cap agreements for the underlying deal, but are independent of them. If the underlying deal has a swap agreement instead of the cap corridor, the NIMS cash flows are affected by the swap.

A typical NIMS stress test calculation involves a combination of prepayment and loss scenarios. We return to the NIM bonds shown in Figure 52, which we reproduce in Figure 71.

Figure 71. WALs and Payment Windows on Securitized NIMS Credit Rating WAL Payment WindowClass Fitch (Years) (Months)A BBB 0.79 2 - 20B BBB- 1.72 20-22C BB+ 1.88 22-24

Source: Citigroup.

These bonds are priced according to the prepayment and loss curves shown in Figure 72. The underlying collateral consists of 20% fixed-rate loans and 80% ARMs.

Figure 72. Prepayment and Loss Vectors Used for the Valuation of NIMS ARM Loans Fixed Loans Cumulative Loss Curve

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45

Period (Months)

CPR

(%)

Prepayment Curve (%) with Penalty Prepayment Curve (%) No Penalty

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45

Period (Months)

CPR

(%)

Prepayment Curve (%) with Penalty Prepayment Curve (%) No Penalty

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1 13 25 37 49 61 73 85

Period (Months)

Cum

ulat

ive

Def

ault

(%)

ARM Cumulative Loss Curve Fixed Cumulative Loss Curve

Source: Citigroup.

The stress scenarios, which are expressed as a percentage of the loss curves and prepayment curves, assume that one-month LIBOR and six-month LIBOR follow the forward curve. Interest rates are sometimes stressed as well, generally by shifting the forward curves up by 100bp and 200bp. Figures 73–75 show the results of stress runs.



Class A, shown in Figure 73, has a very stable WAL and payment window over all but the most stressful scenarios. (The most stressful scenarios are in the lower right corner of the table.) Class C, shown in Figure 75, carries a much higher credit risk. The bond fails to pay down if defaults increase by 15% and prepayments increase by 25% from the pricing assumptions.

Figure 73. Class A NIM Profile at Various Prepay and Default Scenarios

Percentage of Percentage of Prepayments

Defaults 70% 85% 100% 115% 130% 150%

75% WAL (Yrs) 0.78 0.78 0.78 0.78 0.78 0.77 Principal Months 18 19 19 19 19 19 Principal Period Window 2-19 2-20 2-20 2-20 2-20 2-20 Collateral Loss (%) 2.62 2.62 2.62 2.62 2.62 2.25




175% WAL (Yrs) 0.81 0.81 0.82 0.82 0.81 a

Principal Months 22 23 27 29 29 a

Principal Period Window 2-23 2-24 2-28 2-30 2-30 2-a

Collateral Loss (%) 6.11 6.11 6.11 6.04 4.68 3.86

All prepayment speeds are limited to 90% CPR in any period and any scenario. a Indicates a scenario where the Class A Notes do not pay down. Source: Citigroup.

Class A has a stable WAL and payment

window in most scenarios; class C

breaks down under a moderate stress.



Figure 74. Class B NIM Profile at Various Prepay and Default Scenarios


Defaults 70% 85% 100% 115% 130% 150%75% WAL (Yrs) 1.63 1.65 1.66 1.67 1.69 1.75 Principal Months 3 2 2 2 3 4 Principal Period Window 19-21 20-21 20-21 20-21 20-22 20-23 Collateral Loss (%) 2.62 2.62 2.62 2.62 2.62 2.25

100% WAL (Yrs) 1.68 1.70 1.72 1.75 1.78 a



Collateral Loss (%) 3.49 3.49 3.49 3.49 3.39 2.68

125% WAL (Yrs) 1.74 1.77 1.81 1.88 a a

Principal Months 2 3 4 6 a a

Principal Period Window 21-22 21-23 21-24 21-26 22-a 23-a

Collateral Loss (%) 4.36 4.36 4.36 4.36 3.84 3.10

150% WAL (Yrs) 1.84 1.89 2.09 a a a

Principal Months 4 4 14 a a a

Principal Period Window 21-24 22-25 22-35 23-a 23-a 28-a

Collateral Loss (%) 5.24 5.24 5.24 5.24 4.27 3.49

175% WAL (Yrs) 1.98 6.91 a a a a

Principal Months 4 225 a a a a

Principal Period Window 23-26 24-248 28-a 30-a 30-a a-a

Collateral Loss (%) 6.11 6.11 6.11 6.04 4.68 3.86

All prepayment speeds are limited to 90% CPR in any period and any scenario. a Indicates a scenario where the Class B Notes do not pay down. Source: Citigroup.

Figure 75. Class C NIM Profile at Various Prepay and Default Scenarios


Defaults 70% 85% 100% 115% 130% 150%75% WAL (Yrs) 1.74 1.76 1.78 1.82 1.86 a



Collateral Loss (%) 2.62 2.62 2.62 2.62 2.62 2.25

100% WAL (Yrs) 1.81 1.84 1.88 1.97 a a

Principal Months 3 3 3 5 a a

Principal Period Window 21-23 22-24 22-24 23-27 23-a a-a

Collateral Loss (%) 3.49 3.49 3.49 3.49 3.39 2.68

125% WAL (Yrs) 1.90 1.96 2.15 a a a

Principal Months 3 3 10 a a a

Principal Period Window 22-24 23-25 24-33 26-a a-a a-a

Collateral Loss (%) 4.36 4.36 4.36 4.36 3.84 3.10

150% WAL (Yrs) 2.02 4.57 a a a a


Principal Period Window 24-26 25-181 35-a a-a a-a a-a

Collateral Loss (%) 5.24 5.24 5.24 5.24 4.27 3.49

175% WAL (Yrs) 4.10 22.71 a a a a


Principal Period Window 26-87 248-314 a-a a-a a-a a-a

Collateral Loss (%) 6.11 6.11 6.11 6.04 4.68 3.86

All prepayment speeds are limited to 90% CPR in any period and any scenario. a Indicates a scenario where the Class C Notes do not pay down. Source: Citigroup.



APPENDIX A — Does Conversion to REIT Status Matter to ABS Investors24

➤ Several large HEL issuers now operate as REITs. They include New Century, Saxon, Aames, Impac, Novastar, and Origen.

➤ Conversion to a REIT has only an indirect effect on ABS investors. Neither the origination platform, nor the servicing platform, nor the bankruptcy-remoteness of securities is affected. Because mortgage banking functions reside in a taxable REIT subsidiary, the earnings from these operations remain available to grow the business.

➤ However, the REIT operational requirements reduce the flexibility of the lender in seeking optimal monetization of its loans, prevent the lender from selling all of its credit risk, may introduce a dependence on equity infusions for continued operations, and in some cases require a robust growth of the portfolio. These requirements increase the risk to the lender in case of a severe downturn in the mortgage market.

Does Conversion to REIT Status Matter to ABS Investors? Under the Internal Revenue Code of 1986 (IRC), a Real Estate Investment Trust (REIT) is a corporation, trust, or association that may deduct dividends it pays to shareholders from its taxable income. The dividends must equal at least 90% of the income. To qualify as a REIT, the company must also satisfy a number of other rules regarding its assets, sources of income, and ownership. Recently a number of mortgage lenders have converted to REIT status, including New Century, Saxon, and Aames. These lenders joined established REITs, such as IMPAC, Origen, Novastar, American Home Mortgage Investment Corporation, Redwood Trust, and Thornburg Mortgage. In this article, we summarize the key rules that govern REITs and highlight some issues for ABS investors that are specific to REITs.

Requirements for REITs

Under the IRC, a REIT must be an entity that would be taxable as a domestic corporation, if it were not for the REIT election. REITs cannot be a financial institution, such as a bank or insurance company, and its beneficial ownership must be evidenced by transferable shares, which are to be held by at least 100 persons. A REIT cannot be closely held, in the sense that five or fewer individuals cannot own more than 50% of the shares.

In addition, REITs must satisfy certain key income and asset tests.

Income Tests

1 At least 75% of the company’s gross income for each taxable year must be derived directly or indirectly from investments related to real property or

24

This is a reprint of the article that was originally published in Bond Market Roundup: Strategy, Dennis Adler et al, Citigroup, June 25, 2004.

Several mortgage lenders have recently

filed to convert to REIT status.

A REIT cannot be a bank or an insurance

company.



mortgages on real property. In addition to mortgages, the qualifying investments include various types of MBS passthroughs and REMICs.

2 At least 95% of the company’s gross income for each taxable year must be derived from the real estate investments described in item (1), dividends, including dividends from taxable REIT subsidiaries (TRSs), interest, and gain from the sale or other disposition of securities, including derivatives used to hedge the mortgage portfolio, as well as certain other types of income.

Income that satisfies one of these tests is referred to as “good” income for tax purposes. Good income does not include servicing fees for loans serviced for third parties, which include REMICs originated by the same issuer. Furthermore, the IRC specifies prohibited transactions, which are taxed at 100% of the net income generated. Sales of mortgages that are held for less than four years are a prohibited transaction. Therefore, REITs effectively cannot participate in the whole loan (WL) market.

Most mortgage lenders that become a REIT create a TRS that serves the mortgage banking functions, such as loan originations, servicing, and WL sales. The income of TRSs is taxed at regular corporate tax rates. The TRS can sell loans either to a third party or to the REIT parent company.

The mortgages sold by the TRS to the REIT are securitized on the parent company’s balance sheet. For legal purposes the securitization is a true sale, but for accounting purposes the loans remain on the balance sheet (debt for tax accounting). Interest income is booked as it is realized, and there is no gain-on-sale. Although on-balance sheet securitizations are not unique to REITs, they are essential for them, because a substantial majority of the parent company’s assets must be contained in its balance sheet, as we outline below.

Asset Tests

1 At least 75% of the REIT’s assets at the end of each quarter of the tax year must consist of real estate assets, which may include MBS passthroughs and REMICs, cash, cash items, government securities, and stock in other REITs.

2 Not more than 20% of the company’s total assets may be represented by securities of one or more TRSs.

3 Of the securities not included in the 75% class and not in a TRS, the securities of any other entity may not exceed 5% of the REIT’s total assets, and they may not represent more than 10% of the voting power or value of any other entity.

Requirement (2) puts a severe limitation on the size of mortgage banking operations relative to the balance sheet of the REIT. Because the mortgage banking functions initially have a fixed size that cannot be easily reduced and they are expected to grow as servicing operations expand to service mortgages added to the REIT’s balance sheet, some of the companies currently converting to REITs plan on adding MBSs to their balance sheet to satisfy requirement (2). The MBSs would typically be purchased with a significant leverage. (In the case of Aames, the expected leverage is 10 to 14.) As the portfolio of mortgages originated by the TRS grows, the MBS position in the portfolio can be reduced or eliminated.

Servicing fees are not good REIT income,

and sales of whole loans are prohibited.

Loan originations, servicing, and WL sales

are generally handled by a TRS.

REITs securitize loans on their balance sheet.

Because the TRS assets cannot exceed 20% of

the total REIT assets, the REIT balance sheet must

be large.



Equity Requirements and Credit Rating of Securities

Compared to securitizations from REMICs, the on-balance sheet securitizations from REITs have additional requirements:

1 REITs can issue only investment-grade securities and NIMS.

2 REITs must maintain an equity position related to the securitizations. The amount of equity depends on the type of collateral. Alt-A mortgages usually require 4% equity comprised of overcollateralization and excess spread. Subprime mortgages usually require 7%. The equity is in the form of owner trust certificates. The equity requirement prevents the REIT from securitizing all of the cash flows from a collateral pool and limit the amount of NIM issuance.

Implications of REIT Status for ABS Investors

Equity investors perceive REITs favorably, in part because of the stability and transparency of cash flows. For example, REITs typically trade at much higher price-earnings ratios than mortgage companies. At the same time, the ability to place loan originations, servicing, and WL sales into a TRS, which is able to retain earnings and grow operations, addresses the most immediate concerns about turning a mortgage company into a REIT. Nevertheless, the complex operational requirements on REITs that we outlined above generally reduce the flexibility of the company and may have an indirect adverse effect on ABS investors. Some areas of concern are as follows:

➤ Because of requirement (2) of the asset test, a REIT must maintain a large balance sheet relative to its mortgage banking assets. If market conditions favor WL sales over securitizations, a REIT has less flexibility to take advantage of these opportunities than a taxable mortgage company.

➤ The balance sheet can be augmented by purchases of qualifying MBSs, as we mentioned previously. However, the REIT then takes on the role of a portfolio manager of a leveraged MBS portfolio, which may be distant from its original expertise in managing subprime loans.

➤ Because of the requirement to maintain equity in securitizations, a REIT cannot sell all of the cash flows from a pool of loans, even if market conditions favor such a sale. Also, a REIT cannot eliminate all of its credit exposure to the loans in the portfolio.

➤ Although a REIT is allowed to sell NIMS, the equity requirement for securitizations virtually guarantees that the securitizations are cash flow negative. To cover the cash shortfall, the REIT can use the 10% of earnings it is allowed to retain, or it can repeatedly tap the equity markets for additional capital. The latter approach has been employed by some REITs, such as Novastar. The dependence on equity markets for continued operations introduces an additional risk at the corporate level.

➤ A rapid growth of the portfolio that will be initially required for some lenders converting to REIT status may put strain on the origination and servicing platforms. In a period of rising interest rates and a likely slowdown of the housing market, it may be difficult to maintain or grow a production volume without stepping down in credit.

➤ The hedging income from derivatives that are used to hedge mortgages or residuals is not good income under the 75% rule, although it is good income under the 95% rule. In an extreme interest rate or credit scenario, the REIT may

Because of complex operational

requirements, a REIT has reduced flexibility in

seeking optimal market execution of its loans, and may be forced to

grow its portfolio rapidly.



be forced to scale back its hedging. This scenario is unlikely, however, because the hedging of mortgages is typically done only prior to securitizations, while the hedging of residuals is likely to account for only a small portion of the portfolio.

In summary, the conversion to a REIT has only an indirect effect on ABS investors. Neither the origination platform, nor the servicing platform, nor the bankruptcy-remoteness of securities is affected. Because mortgage banking functions reside in a taxable REIT subsidiary, the earnings from these operations remain available to grow the business. However, the REIT operational requirements reduce the flexibility of the lender in seeking optimal monetization of its loans, preclude the lender from selling all of its credit risk, may introduce a dependence on equity infusions for continued operations, and in some cases require a robust growth of the portfolio. These requirements increase the risk to a lender in case of a severe downturn in the mortgage market.

The risk to ABS investors is the ability of

a REIT to navigate through a downturn in the mortgage market.



Appendix B — The Available Funds Cap25

➤ We evaluate the cost of the available funds cap (AFC) for senior and subordinate HEL bonds under several interest rate, volatility, and prepayment scenarios.

➤ Using a 12-month average of implied volatilities, the cost of the AFC on recently issued securities is low, ranging from 0bp on short and intermediate triple-As to 4bp on the double-Bs. In a 100bp parallel shift of the forward curve, the cost of the AFC increases to a range of 0bp to 11bp.

➤ The cost of the AFC is higher on moderately seasoned deals, because of less effective corridors and a higher proportion of fixed-rate loans in the pool. For a typical early 2004 deal, the cost of the AFC is in the range of 7bp to 13bp. A 200bp interest rate stress can lift the cost of the AFC to over 70bp on the double-Bs.

➤ The failure of stepdown triggers increases the cost of the AFC on bonds rated single-A and lower. However, the effect is small (4bp for a triple-B) and would likely be overshadowed by credit issues.

Cost of the Available Funds Cap — Effect of Interest Rates, Volatilities, Speeds, and Seasoning Floating-rate bonds backed by first-lien subprime mortgages, or home equity loans (HELs), are subject to an available funds cap (AFC). Several developments over the past 12 months have placed the AFC in the spotlight. These include a rise in short-term interest rates, a decrease in excess spread on new deals, a decrease in discount margins (DMs) on HEL securities, and a steep rise in interest in HELs by overseas investors, many of whom are mindful of the cost of the AFC. In this article we calculate the option-theoretic cost of the AFC for a variety of securities and pricing scenarios. Under current interest rates and implied volatilities, the cost of the cap is virtually negligible on recently issued securities. The cost is higher for seasoned deals, because their corridors have lower ceilings and they generally carry a higher load of fixed-rate loans. The cost of the AFC also increases under higher volatility and interest rate scenarios.

AMSI 2005-R1 has a separate corridor for triple-As in each collateral group and for the subordinates. The corridors lower the risk that the interest rate payments on the bonds will be capped out. The net WAC caps with the maximum corridor payments are shown in Figure 76. For the first two years, the net WAC cap on the triple-As is 9.75% and the net WAC cap on the subordinates is 10.0%. The duration of the corridor is 33 months for seniors and 35 months for subordinates.

25

This is a reprint of the article that was originally published in Bond Market Roundup: Strategy, Dennis Adler et al, Citigroup, March 18, 2005.

The cost of the AFC is low on new issues, but it

increases with rising rates and volatilities.

We calculate the cost of the AFC for bonds rated triple-A through double-

B from AMSI 2005-R1.



Figure 76. Net WAC Cap With Maximum Corridor Payments for Triple-As and Mezzanines in AMSI 2005-R1

9.5

10.0

10.5

11.0

11.5

12.0

12.5

0 10 20 30 40 50 60 70 80 90

Group 3 Triple-A M

Source: Citigroup.

For bonds that form a typical HEL deal, the cost of the AFC depends on several factors, which include the following:

1 Level of interest rates. An increase in one-month LIBOR boosts the coupons on the bonds, bringing them closer to the net WAC cap. The result is an increase in the cost of the AFC.

2 Level of volatilities. Higher volatilities imply a greater risk of extreme interest rate scenarios where the bonds are capped out. We calculate the cost of the AFC by projecting the cash flows along 200 interest rate paths generated by Citigroup’s term structure model. The model is calibrated daily to the market-implied volatilities of various caps and swaptions. The most relevant volatility for HEL bonds is the five-year cap volatility.

3 Weighted average life (WAL) and payment window of the bond. WAL or window extensions due to slower speed, failure to exercise the cleanup call, and trigger failure (on subordinates) increase the cost of the AFC.

4 Discount margin of the bond. For a fixed net WAC cap, bonds with higher coupons are capped out first.

5 Details of the structure. This includes the length and levels of protective corridors, whether the protection is provided by a corridor or a swap agreement, and position in the waterfall of the payback of basis risk shortfall (whether it is higher or lower in priority to loss paybacks).

6 Percentage of fixed-rate loans in the pool.

Cost of AFC Evaluated

We evaluate the cost of the AFC under several combinations of interest rate, volatility, and prepayment scenarios. The current value of five-year cap volatility (as of the market close on March 14, 2005) is 20.2%. This volatility reached its highest value in the past 12 months on March 16, 2004, at 40.8%. The 12-month average is 27.1%. For the calculation with average volatilities, we average all volatilities used in the term structure model (seven cap volatilities, seven swaption volatilities, and

We evaluate the cost of the AFC under several

combinations of interest rate, volatility, and

prepayment scenarios.



the short-rate volatility), and recalibrate the model using the current forward curve. The results are shown in Figure 77. All bonds were priced at current market spreads.

Figure 77. Cost of the AFC for Senior and Subordinate Bonds From AMSI 2005-R1 Under Different Prepayment, Volatility, and Interest Rate Scenarios

100PPV 75PPV 125PPV

WAL (Yr) Credit Ratings Current Vol Average Vol High Vol Curr Vol Avg Vol High Vol Curr Vol Avg Vol High VolSecurity Call/Mat S&P/Moody's/Fitch Fwd +100bp +200bp Fwd +100bp +200bp Fwd +100bp +200bp Fwd Fwd Fwd Fwd Fwd Fwd

AMSI 2005-R1 Call/Maturity

A-3A 1.0/1.0 AAA/Aaa/AAA 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0A-3B 3.0/3.0 AAA/Aaa/AAA 0/0 0/0 0/0 0/0 0/0 1/1 0/0 2/2 5/5 0/0 0/0 1/1 0/0 0/0 0/0A-3C 7.0/9.4 AAA/Aaa/AAA 1/1 2/3 6/8 1/1 5/5 11/13 6/8 14/19 26/35 1/1 1/1 9/13 0/0 0/1 4/5A-3D 2.4/2.6 NR/Aaa/AAA 0/0 0/0 2/2 0/0 1/1 3/4 0/1 4/6 9/12 0/0 0/0 2/3 0/0 0/0 0/0M-1 4.9/5.4 AA/Aa2/AA 0/1 2/3 5/8 1/2 6/7 13/16 7/10 17/22 33/40 0/1 1/2 10/13 0/0 1/1 5/7M-5 4.7/5.1 A-/A2/A 0/1 2/4 6/9 2/2 6/8 16/19 8/11 20/24 36/41 1/1 2/3 11/14 0/0 1/1 6/8M-8 4.7/4.9 BBB-/Baa2/BBB 0/1 3/4 9/11 3/3 9/9 21/23 11/12 25/27 44/47 1/2 4/4 14/17 0/0 2/2 9/9M-9 4.6/4.6 BB/Ba1/BB+ 0/0 4/4 11/11 4/4 11/10 26/26 13/13 31/30 52/52 2/1 5/5 17/17 0/0 3/3 11/10

Closing curve from March 14, 2005. Source: Citigroup.

Volatilities are a key determinant of the cost of the AFC. On the seven-year triple-A for example, the difference between the high-volatility and low-volatility scenario is 7bp. On the triple-B, the difference is 11bp; on the double-B, the difference is 13bp. We view the high-volatility scenario as an extreme case. For example, the five-year high of the five-year cap volatility is 44.3%, only 3.5% higher than the one-year high. Yet, the current value of the volatility, which is directly relevant for hedging, is subject to large fluctuations from month to month. We suggest that in the absence of daily hedging, the best way to estimate the cost of the AFC is by using average volatilities. Assuming average volatilities and the current forward curve, the cost of the AFC on all the bonds is very low, ranging from 0bp to 4bp. The basis point cost is higher for subordinate bonds, but as a percentage of the bond’s discount margin, the cost of the AFC decreases with the decreasing rating of the bond.

The prepayment pricing speed of 100PPV is conservative. For fixed-rate collateral in AMSI 2005-R1, the pricing speed is 20HEP, which is lower than the industry average prepayment speed over any three-month interval since 1998. For floating-rate collateral, 100PPV corresponds to a prepayment ramp, which is lower than historical prepayments. Figure 78 shows this prepayment ramp along with the historical industry average prepayments for floating-rate subprime mortgages.26 With the exception of the 1999 vintage, whose speeds approximately matched the prepayment ramp prior to the first reset and were lower at the reset, all the other vintages prepaid much faster than the ramp. The 2003 originations, for example, prepaid about 75% faster that the ramp prior to the first reset, and about 15% faster than the ramp at the reset.

26

The industry average is taken from Citigroup’s HELLO Report, January 21, 2005. The report tracks the prepayment and credit performance of 12 large HEL issuers from 1997 to the present.

Volatilities are a key determinant of the cost

of the AFC. We recommend using

average volatilities.

The prepayment pricing speed of 100PPV

is conservative.



Figure 78. Historical Prepayments and the AMSI 2005-R1 Prepayment Pricing Ramp for Floating-Rate HELs

0

10

20

30

40

50

60

70

80

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70Deal Age

One-

Mon

th C

PR (%

)

1997 19981999 20002001 20022003 100% PPV

Source: Citigroup.

Because the 100PPV prepayment speed is used to determine the notional balance on the corridors protecting the triple-As, an actual prepayment speed that exceeds 100PPV automatically increases the available protection. Therefore, a conservative prepayment ramp objectively lowers the cost of the AFC, in addition to providing a conservative estimate of the cost in Figure 77.

Cost of AFC for Seasoned Deals

Although one might expect that the approach of the first reset on hybrids would decrease the cost of the AFC, the cost of the AFC is currently higher on moderately seasoned HEL deals than on new-issue deals. Several factors are responsible for this relationship, including the following:

➤ Short-term interest rates have risen, leaving the older corridors less effective at protecting bonds.

➤ The initial proportion of fixed-rate collateral in deals issued in 2003 and the beginning of 2004 was much higher than it is today.

Because the prepayments on hybrids in the past several years have been higher than prepayments on fixed-rate loans, the fraction of fixed-rate loans in seasoned deals is often higher than at origination. However, the sharp dropoff of floating-rate collateral typically occurs only after the first reset.

We compare the cost of the AFC on AMSI 2005-R1 and AMSI 2004-R1. The net WAC cap with the maximum corridor payments for the two deals is shown in Figure 79. For the first 24 months, the net WAC cap on triple-As is 7.5% on AMSI 2004-R1, which is 225bp lower than the corresponding net WAC cap in AMSI 2005-R1. The difference on the net WAC caps on mezzanines is 150bp (8.5% on AMSI 2004-R1 versus 10.0% on AMSI 2005-R1). The increase in the net WAC caps on AMSI 2005-R1 is in part a reflection of the jump in one-month LIBOR. Between the issuance dates of the 2004 and 2005 deals, one-month LIBOR rose from 1.10% to 2.65%. However, this 155bp jump in one-month LIBOR is still 70bp short of the increase in the net WAC cap on the triple-As, indicating better initial protection on AMSI 2005-R1.

The cost of the AFC is higher on moderately seasoned HEL deals.

We compare the cost of the AFC on AMSI 2005-R1 and AMSI 2004-R1.



Figure 79. Net WAC Cap With Maximum Corridor Payments for Triple-As and Mezzanines From AMSI 2004-R1 and AMSI 2005-R1 AMSI 2004-R1 AMSI 2005-R1

7

8

9

10

11

12

13

0 10 20 30 40 50 60 70 80 90

Pay Period (Months)

WAC

(%)

Group 2 Triple-A Mezzanine

7

8

9

10

11

12

13

0 10 20 30 40 50 60 70 80 90Pay Period (Months)

WAC

(%)

Group 3 Triple-A Mezzanine

Source: Citigroup.

Another difference between AMSI 2004-R1 and AMSI 2005-R1 is the proportion of fixed-rate collateral. Initially, group 2 in AMSI 2004-R1 and the whole deal contained 35% fixed-rate loans. This proportion is much lower for AMSI 2005-R1, at 15% for group 3 and 19% for the collateral groups combined. A sharp drop in the proportion of fixed-rate collateral backing floating-rate bonds is a hallmark of the HEL market. Twelve months ago it was common to include 35%–40% of fixed-rate loans in the collateral pool. In the past six months, that proportion has generally been under 20%. The balance of fixed-rate loans in AMSI 2004-R1 has not grown significantly since deal issuance and still stands at 35%.

We perform all calculations on AMSI 2004-R1 using the same prepayment vector that we use on AMSI 2005-R1. The floating-rate portion of this vector is different than the one used to price AMSI 2004-R1 in February 2004. At issuance, the floating-rate collateral was assumed to prepay at 27% CPR, which is much slower and much less realistic than the prepayment ramp shown in Figure 78.

The cost of the AFC is materially higher for all credit ratings in AMSI 2004-R1. Figure 80 compares the costs. At the 12-month average volatility and 100PPV, the cost of the AFC to call on the triple-A pass-through is 7bp in AMSI 2004-R1, compared to 0bp in AMSI 2005-R1. When considering a pricing spread in the low-20bp range, the cost of the AFC of 7bp is significant. On the single-As, the difference between AMSI 2004-R1 and AMSI 2005-R1 is 9bp, and on the triple-Bs the difference is 10bp. The differences on all bonds become more pronounced under stresses to the forward curve. In summary, while the cost of the AFC is not a key determinant of relative value for AMSI 2005-R1, it is a key determinant for the 2004 deal.

The proportion of fixed-rate loans backing the bonds is different for AMSI 2004-R1

and AMSI 2005-R1.

For the triple-A pass-through the cost of the

AFC is 7bp higher in AMSI 2004-R1.



Figure 80. Comparison of Cost of the AFC for Senior and Subordinate Bonds from AMSI 2005-R1 and AMSI 2004-R1 Percent Duration of 100PPV 75PPV 125PPVSecurity WAL (Yr) Credit Ratings Fixed-Rate Corridor Average Vol. Average Vol. Average Vol. Call/Mat S&P/Moody's/Fitch Collateral (%) (Months) Fwd Fwd+100bp Fwd+200bp Fwd FwdAMSI 2005-R1 Call/Maturity

A-3A 1.0/1.0 AAA/Aaa/AAA 15 33 0/0 0/0 0/0 0/0 0/0A-3B 3.0/3.0 AAA/Aaa/AAA 0/0 0/0 1/1 0/0 0/0A-3C 7.0/9.4 AAA/Aaa/AAA 1/1 5/5 11/13 1/1 0/1A-3D 2.4/2.6 NR/Aaa/AAA 0/0 1/1 3/4 0/0 0/0M-1 4.9/5.4 AA/Aa2/AA 19 35 1/2 6/7 13/16 1/2 1/1M-5 4.7/5.1 A-/A2/A 2/2 6/8 16/19 2/3 1/1M-8 4.7/4.9 BBB-/Baa2/BBB 3/3 9/9 21/23 4/4 2/2M-9 4.6/4.6 BB/Ba1/BB+ 4/4 11/10 26/26 5/5 3/3

AMSI 2004-R1 A-2 2.3/2.9 AAA/Aaa/AAA 35 23 7/8 16/19 35/39 8/8 6/8M-2 3.6/4.1 AA/Aa2/AA 35 39 8/12 20/25 44/50 9/12 9/12M-5 3.5/3.9 A/A2/A 11/15 26/32 54/61 13/16 11/14M-8 3.4/3.5 BBB/Baa2/BBB 13/15 33/34 63/66 16/16 14/14M-10 2.4 BB+/Ba1/BB+ 13 35 74 13 16


Interestingly enough, in the high-prepayment scenario the cost of the AFC on the double-B is higher than in the baseline prepayment scenario. The likely reason for this inversion is that the shortening of the bond limits the paybacks of basis point shortfall on some interest rate paths.

Effect of Stepdown Triggers

The failure of stepdown triggers extends subordinate bonds and increases the cost of the AFC. In many cases of trigger failure, the credit issues associated with the thinning of excess spread are likely to be a greater contributor to the option cost of the bonds than the available funds cap.27 This is especially true for bonds rated below triple-B. Therefore, the cost of the AFC should be viewed as a minimum adjustment to the discount margin on bonds where the trigger is likely to fail for an extended number of payment periods. For the calculation, we run the stress scenario where the trigger fails for the life of the deal, and the bonds pay to maturity, rather than to call. The results are shown in Figure 81.

Figure 81. Effect of Trigger Failure on the Cost of AFC 100PPV 75PPV 125PPV WAL (Yr) Credit Ratings Average Volatility Average Volatility Average VolatilitySecurity Call/ Mat S&P/Moody's/Fitch Fwd Fwd+100bp Fwd+200bp Fwd FwdAMSI 2005-R1 Maturity

A-3A 0.9 AAA/Aaa/AAA 0 0 0 0 0A-3B 2.5 AAA/Aaa/AAA 0 0 0 0 0A-3C 4.4 AAA/Aaa/AAA 0 2 5 0 0A-3D 2.0 NR/Aaa/AAA 0 0 1 0 0M-1 5.6 AA/Aa2/AA 1 5 14 2 1M-5 7.9 A-/A2/A 3 10 21 3 3M-8 10.1 BBB-/Baa2/BBB 7 17 36 8 7M-9 11.4 BB/Ba1/BB+ 13 29 55 13 12


27

See Compression of Excess Spread in Rate Selloffs — An Update, Citigroup, January 16, 2004.

The failure of stepdown triggers increases the

cost of the AFC on bonds rated single-A

and below.



Comparing the same prepayment, volatility, and interest rate scenarios in Figure 81 and Figure 77, it follows that the cost of the AFC on the A-3C class drops by 1bp in the forward curve scenario and by 3bp in the forward + 100bp scenario. The cost of the AFC on the double-A is virtually unchanged when triggers fail (the shortening of the principal payment window offsets a modest WAL extension), while the cost of the AFC on lower-rated bonds increases in proportion to the WAL extension. On the triple-B at 100PPV and the forward curve, the cost of the AFC increases by 4bp, while for the double-B the cost increases by 9bp. However, these increases in the cost of the AFC are relatively small compared to the credit issues that would likely arise if the triple-B bond extended to ten years and the double-B bond extended to 11 years.

The effect is modest for triple-As and

subordinates and would likely be overshadowed

by credit issues.

Disclosure Appendix A1 ANALYST CERTIFICATION

We, Ivan Gjaja, Mary Kane, and Marc Carnahan, hereby certify that all of the views expressed in this report accurately reflect our personal views about any and all of the subject securities, issuers, currencies, commodities, futures, options, economies or strategies. We also certify that no part of our compensation was, is, or will be directly or indirectly related to the specific recommendation(s) or view(s) expressed in this report.

Other Disclosures ADDITIONAL INFORMATION AVAILABLE UPON REQUEST

Citibank, N.A., London Branch and Citigroup Global Markets Inc, including its parent, subsidiaries, divisions and/or affiliates (“the Firm”), may make a market in the securities discussed in this report and may sell to or buy from customers, as principal, securities recommended in this report. The Firm may have a position in securities or options of any issuer recommended in this report. The Firm may be regular issuers of, and trade in (including position taking), financial instruments linked to securities, which may have been reported on in this research report. The Firm may perform or solicit investment banking or other services from any issuer recommended in this report. An employee of the Firm may be a director of an issuer recommended in this report. Within the past three years, the Firm may have acted as manager or co-manager of a public offering of the securities of any issuer recommended in this report. Securities recommended, offered, or sold by the Firm : (i) are not insured by the Federal Deposit Insurance Corporation; (ii) are not deposits or other obligations of any insured depository institution (including Citibank); and (iii) are subject to investment risks, including the possible loss of the principal amount invested. Past performance is not a guarantee of future results. This report does not take into account the investment objectives, financial situation or particular needs of any particular person. Investors should obtain advice based on their own individual circumstances before making an investment decision. Investing in non-U.S. securities, including ADR’s entails certain risks. The securities of non-U.S. issuers may not be registered with, nor be subject to the reporting requirements of, the U.S. Securities and Exchange Commission. There may be limited information available on foreign securities. 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Intro to HEQ Market

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Transcript of Intro to HEQ Market