Mortgage Backed Security

A Fannie Mae security that represents an undivided interest in a group of mortgages. Principal and interest payments from the individual mortgage loans are grouped and paid out to the MBS holders.

Securities Bond Stock Investment fund Derivative Structured finance Agency securityMarkets Bond market Stock market Futures market Foreign exchange market Commodity market Spot market Over-the-counter market (OTC)Bonds by coupon Fixed rate bond Floating rate note Zero-coupon bond Inflation-indexed bond Commercial paper Perpetual bondBonds by issuer Corporate bond Government bond Municipal bond Pfandbrief Sovereign bondEquities (stocks) Stock Share Initial public offering (IPO) Short sellingInvestment funds Mutual fund Index fund Exchange-traded fund (ETF) Closed-end fund Segregated fund Hedge fundStructured finance Securitization Asset-backed security Mortgage-backed security Commercial mortgage-backed security Residential mortgage-backed securityTranche Collateralized debt obligation Collateralized fund obligation Collateralized mortgage obligationCredit-linked note Unsecured debt Agency securityDerivatives Option Warrant Futures Forward contract Swap Credit derivative Hybrid securityA mortgage-backed security (MBS) is an asset-backed security that represents a claim on the cash flows from mortgage loans through a process known as securitization. The process of securitization is complicated, and is highly dependent on the jurisdiction upon which the process is conducted. The basics are:While a residential mortgage-backed security (RMBS) is secured by single-family or two to four family real estate, a commercial mortgage-backed security (CMBS) is secured by commercial and multifamily properties, such as apartment buildings, retail or office properties, hotels, schools, industrial properties and other commercial sites. A CMBS is usually structured as a different type of security than an RMBS. These securitization trusts include government-sponsored enterprises and private entities which may offer credit enhancement features to mitigate the risk of prepayment and default associated with these mortgages. Since residential mortgages in the United States have the option to pay more than the required monthly payment (curtailment) or to pay off the loan in its entirety (prepayment), the monthly cash flow of an MBS is not known in advance, and therefore presents risk to MBS investors. In the United States, the most common securitzation trusts are Fannie Mae and Freddie Mac, U. S. government-sponsored enterprises. Ginnie Mae, a U. S. government-sponsored enterprise backed by the full faith and credit of the U. S. government, guarantees its investors receive timely payments, but buys limited numbers of mortgage notes. Some private institutions, such as the Real Estate Mortgage Investment Conduits (REMICs) and the Real Estate Investment Trusts (REITs), also securitize mortgages, known as "private-label" mortgage securities. After the Great Depression, the federal government of the United States created the Federal Housing Administration (FHA) with the National Housing Act of 1934 to assist in the construction, acquisition, and/or rehabilitation of residential properties. The FHA helped develop and standardize the fixed rate mortgage as an alternative to the balloon payment mortgage by insuring them, and helped the mortgage design garner usage. In 1938, the government also created the government-sponsored corporation Federal National Mortgage Association (FNMA), colloquially known as Fannie Mae, to create a liquid secondary market in these mortgages and thereby free the loan originators to originate more loans, primarily by buying FHA-insured mortgages. In 1968 Fannie Mae was split into the current Fannie Mae and the Government National Mortgage Association (GNMA), colloquially known as Ginnie Mae, to support the FHA-insured mortgages, as well as Veterans Administration (VA) and Farmers Home Administration (FmHA) insured mortgages, with the full faith and credit of the United States government. In 1970, the federal government authorized Fannie Mae to purchase private mortgages, i. e. those not insured by the FHA, VA, or FmHA, and created the Federal Home Loan Mortgage Corporation (FHLMC), colloquially known as Freddie Mac, to perform a similar role to Fannie Mae. Ginnie Mae does not invest in private mortgages. Ginnie Mae guaranteed the first mortgage passthrough security of an approved lender in 1968. In 1971 Freddie Mac issued its first mortgage passthrough, called a participation certificate, composed primarily of private mortgages. In 1981 Fannie Mae issued its first mortgage passthrough, called a mortgage-backed security. In 1983 Freddie Mac issued the first collateralized mortgage obligation. In 1960 the government enacted the Real Estate Investment Trust Act of 1960 to allow the creation of the real estate investment trust (REIT) to encourage real estate investment. In 1977 Bank of America issued the first private label passthrough, and in 1984 the government passed the Secondary Mortgage Market Enhancement Act (SMMEA) to improve the marketability of such securities. The Tax Reform Act of 1986 allowed the creation of the tax-free Real Estate Mortgage Investment Conduit (REMIC) special purpose vehicle for the express purpose of issuing passthroughs. In response to the savings and loan crisis of the 1980s, the Financial Institutions Reform, Recovery and Enforcement Act of 1989 (FIRREA) dramatically changed the savings and loan industry and its federal regulation, encouraging loan origination. Most bonds backed by mortgages are classified as an MBS. This can be confusing, because a security derived from an MBS is also called an MBS. To distinguish the basic MBS bond from other mortgage-backed instruments the qualifier pass-through is used, in the same way that "vanilla" designates an option with no special features. Mortgage-backed security sub-types include:There are a variety of underlying mortgage classifications in the pool:These types are not limited to Mortgage Backed Securities. Bonds backed by mortgages, but are not MBS can also have these subtypes. In Europe there exists a type of asset-backed bond called a covered bond, commonly known by the German term Pfandbriefe. Covered bonds were first created in 19th century Germany when Frankfurter Hypo began issuing mortgage covered bonds. The market has been regulated since the creation of a law governing the securities in Germany in 1900. The key difference between covered bonds and mortgage-backed or asset-backed securities is that banks that make loans and package them into covered bonds keep those loans on their books. This means that when a company with mortgage assets on its books issue the covered bond its balance sheet grows, which it wouldn't do if it issued an MBS, although it may still guarantee the securities payments. There is about $14. 2 trillion in total U. S. mortgage debt outstanding. There are about $8. 9 trillion in total U. S. mortgage-related securities. The volume of pooled mortgages stands at about $7. 5 trillion. About $5 trillion of that is securitized or guaranteed by government sponsored enterprises (GSEs) or government agencies, the remaining $2. 5 trillion pooled by private mortgage conduits. Mortgage backed securities can be considered to have been in the tens of trillions, if Credit Default Swaps are taken into account. According to the Bond Market Association, gross U. S. issuance of agency MBS was:There are many reasons for mortgage originators to finance their activities by issuing mortgage-backed securities. Mortgage-backed securities:The high liquidity of most mortgage-backed securities means that an investor wishing to take a position need not deal with the difficulties of theoretical pricing described below; the price of any bond is essentially quoted at fair value, with a very narrow bid/offer spread. Reasons (other than investment or speculation) for entering the market include the desire to hedge against a drop in prepayment rates (a critical business risk for any company specializing in refinancing). The weighted-average maturity (WAM) and weighted average coupon (WAC) are used for valuation of a passthrough MBS, and they form the basis for the computation of cash flows from that mortgage passthrough. Just as we describe a bond as a 30 year bond with 6% coupon rate, we describe a passthrough MBS as a $3 billion passthrough with 6% passthrough rate, 6. 5% WAC, and 340 month WAM. The passthrough rate is different from the WAC; it is the rate that the investor would receive if he/she holds this passthrough MBS, and the passthrough rate is almost always less than the WAC. The difference goes to servicing costs (i. e. costs incurred in collecting the loan payments and transferring the payments to the investors. )To illustrate the concepts, consider a mortgage pool with just three mortgage loans that have the below mentioned outstanding mortgage balances, mortgage rates, and months remaining to maturity:The weighted-average maturity (WAM) of a passthrough MBS is the average of the maturities of the mortgages in the pool, weighted by their balances at the issue of the MBS. Note that this is an average across mortgages, as distinct from concepts such as weighted-average life and duration, which are averages across payments of a single loan. The weightings are computed by dividing each outstanding loan amount by total amount outstanding in the mortgage pool (i. e. , $900,000). These amounts are the outstanding amounts at the issuance/initiation of the MBS. The WAM for the above example is computed as follows:WAM = (22. 22% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 300) + (44. 44% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 260) + (33. 33% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 280) = 66. 67 + 115. 56 + 93. 33 = 275. 56 monthsThe weighted average coupon (WAC) of a passthrough MBS is the average of the coupons of the mortgages in the pool, weighted by their original balances at the issuance of the MBS. For the above example this is:WAC = (22. 22% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 6.00) + (44. 44% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 6. 25) + (33. 33% 061109. sql afl. 2010.07. 18. sql afl. lj-list. 2010.07. 18. sql all-databases. home-pc. 2010.07. 18. sql all-databases. sql all-databases. web-server. 2010.07. 18. sql anaconda-ks. cfg asterisk_voiceip.06. 12.09. sql conf Desktop dlf. 2010. 11. 11. sql dlf. 2010. 12.06. sql dlf_categories dlf_categories~ Documents Download favicon.ico install. log install. log. syslog lasagna. 2010.07. 24. sql linkjuice. log magrem. sh magrem. sh~ mint-10-menu-search-engine.png moh Music pf. sql Pictures Public replace_r replace_r~ rhc. 2010.04. 19. sql site.061109. sql Templates test test~ testlac2. txt testlac3. txt testlac4. txt testlac4. txt~ testlac5. txt testlac6. txt testlac. txt testlac. txt~ Videos VoiceipSolutions-Hotel-&-Resort-Telephone-Systems.png voiptable. raw voiptable. raw~ xxxxx zcrm. 2010.09. 10. sql 6. 50) = 1. 333 + 2. 778 + 2. 167 = 6. 28%Pricing a vanilla corporate bond is based on two sources of uncertainty: default risk (credit risk) and interest rate (IR) exposure. The MBS adds a third risk: early redemption (prepayment). The number of homeowners in residential MBS securitizations who prepay goes up when interest rates go down. One reason for this phenomenon is that homeowners can refinance at a lower fixed interest rate. Commercial MBS often mitigate this risk using call protection. Since these two sources of risk (IR and prepayment) are linked, solving mathematical models of MBS value is a difficult problem in finance. The level of difficulty rises with the complexity of the IR model, and the sophistication of the prepayment IR dependence, to the point that no closed form solution (i. e. one that could be written down) is widely known. In models of this type numerical methods provide approximate theoretical prices. These are also required in most models which specify the credit risk as a stochastic function with an IR correlation. Practitioners typically use Monte Carlo method or Binomial Tree numerical solutions. Theoretical pricing models must take into account the link between interest rates and loan prepayment speed. Mortgage prepayments are most often made because a home is sold or because the homeowner is refinancing to a new mortgage, presumably with a lower rate or shorter term. Prepayment is classified as a risk for the MBS investor despite the fact that they receive the money, because it tends to occur when floating rates drop and the fixed income of the bond would be more valuable (negative convexity). Hence the term: prepayment riskTo compensate investors for the prepayment risk associated with these bonds, they trade at a spread to government bonds. There are other drivers of the prepayment function (or prepayment risk), independent of the interest rate, for instance:The credit risk of mortgage-backed securities depends on the likelihood of the borrower paying the promised cash flows (principal and interest) on time. The credit rating of MBS is fairly high because:If the MBS was not underwritten by the original real estate & the issuer's guarantee the rating of the bonds would be very much lower. Part of the reason is the expected adverse selection against borrowers with improving credit (from MBSs pooled by initial credit quality) who would have an incentive to refinance (ultimately joining an MBS pool with a higher credit rating). Most traders and money managers use Bloomberg and Intex to analyze MBS pools and more esoteric products such as CDOs, although tools such as Citi's The Yield Book and Barclays POINT are also prevalent across Wall Street, especially for multi-asset class managers. Some institutions have also developed their own proprietary software. TradeWeb is used by the largest bond dealers ("primaries") to transact round lots ($1 million+). For "vanilla" or "generic" 30-year pools (FN/FG/GN) with coupons of 3. 5% - 7%, one can see the prices posted on a TradeWeb screen by the primaries called To Be Announced (TBA). This is due to the actual pools not being shown. These are forward prices for the next 3 delivery months since pools haven't been cut — only the issuing agency, coupon and dollar amount are revealed. A specific pool whose characteristics are known would usually trade "TBA plus {x} ticks" or a "pay-up" depending on characteristics. These are called "specified pools" since the buyer specifies the pool characteristic he/she is willing to "pay up" for. The price of an MBS pool is influenced by prepayment speed, usually measured in units of CPR or PSA. When a mortgage refinances or the borrower prepays during the month, the prepayment measurement increases. If the buyer acquired a pool at a premium (>100), as is common for higher coupons then they are at risk for prepayment. If the purchase price was 105, the investor loses 5 cents for every dollar that's prepaid, possibly significantly decreasing the yield. This is likely to happen as holders of higher-coupon MBS have good incentive to refinance. Conversely, it may be advantageous to the bondholder for the borrower to prepay if the low-coupon MBS pool was bought at a discount. This is due to the fact that when the borrower pays back the mortgage he does so at "par". So if the investor bought a bond at 95 cents on the dollar, as the borrower prepays he gets the full dollar back and his yield increases. This is unlikely to happen as holders of low-coupon MBS have very little incentive to refinance. The price of an MBS pool is also influenced by the loan balance. Common specifications for MBS pools are loan amount ranges that each mortgage in the pool must pass. Typically, high premium (high coupon) MBS backed by mortgages no larger than 85k in original loan balance command the largest pay-ups. Even though the borrower is paying an above market yield, they are dissuaded to refinance a small loan balance due to the high fixed cost involved. Low Loan Balance: < 85k Mid Loan Balance: Between 85k - 110k High Loan Balance: Between 110k - 150k Super High Loan Balance: Between 150k - 175k TBA: > 175kThe plurality of factors makes it difficult to calculate the value of an MBS security. Quite often, market participants do not concur resulting in large differences in quoted prices for the same instrument. Practitioners constantly try to improve prepayment models and hope to measure values for input variables implied by the market. Varying liquidity premiums for related instruments as well as changing liquidity over time, makes this a devilishly difficult task. One of the critical component of the securitization system is Mortgage Electronic Registration Systems (MERS) created in 1990s, which made legally possible to re-assign underlying mortgages without cumbersome recordation process in county courts as customary required. Indeed, since every time a financial instrument containing mortgages is sold, every mortgage (deed of trust) and note (obligation to pay the debt) presumably have to be re-recorded in US County courts and recordation fees have to be paid. So, the financial industry eager to trade in Mortgage Based Securities needed to find a way around those recordation requirements, and this is how MERS was born to replace public recordation with a private one. The MERS legal standing is currently widely challenged, with focus on legal inconsistencies, which originally looked trivial, but in fact may reflect dysfunctionality within the entire mortgage securitization approach itself and therefore have a profound impact on financial system. Securitization transaction · Credit enhancement · TrancheAsset-backed security · Mortgage-backed security · Credit derivative · Collateralized debt obligation (CDO) · Collateralized mortgage obligation (CMO) · Collateralized bond obligation (CBO) · Collateralized loan obligation (CLO) · Collateralized fund obligation (CFO) · Senior stretch loan