Mortgage backed securities, which include Ginnie Mae Securities (GNMA) and Collatoralized Debt Instruments (CDO), are among the most complex securities in the fixed income asset class. Vanguard provides a basic description of mortgage backed securities in the prospectus to its bond funds:
Mortgage-backed securities represent interests in underlying pools of mortgages. Unlike ordinary bonds, which generally pay a fixed rate of interest at regular intervals and then repay principal upon maturity, mortgage-backed securities pass through both interest and principal from underlying mortgages as part of their regular payments. Because the mortgages underlying the securities can be prepaid at any time by homeowners or by corporate borrowers, mortgage-backed securities are subject to prepayment risk. These types of securities are issued by a number of government agencies, including the GNMA, the FHLMC, and the FNMA, [as well as by private issuers].
As a rule, when interest rates rise, bond prices fall. The opposite is also true: Bond prices go up when interest rates fall. Why do bond prices and interest rates move in opposite directions? Let’s assume that you hold a bond offering a 5% yield. A year later, interest rates are on the rise and bonds of comparable quality and maturity are offered with a 6% yield. With higher-yielding bonds available, you would have trouble selling your 5% bond for the price you paid—you would probably have to lower your asking price. On the other hand, if interest rates were falling and 4% bonds were being offered, you should be able to sell your 5% bond for more than you paid.
How mortgage-backed securities are different: In general, declining interest rates will not lift the prices of mortgage-backed securities—such as GNMAs—as much as the prices of comparable bonds. Why? Because when interest rates fall, the bond market tends to discount the prices of mortgage-backed securities for prepayment risk—the possibility that homeowners will refinance their mortgages at lower rates and cause the bonds to be paid off prior to maturity. In part to compensate for this prepayment possibility, mortgage-backed securities tend to offer higher yields than other bonds of comparable credit quality and maturity. [A lucid discussion of prepayment risks, including contraction risk, extension risk, and negative convexity, can be found at InvestinginBonds.com]
Some definitions and papers follow:
Mortgage Backed Security (MBS)
Collateralized Mortgage Obligation (CMO}
Ginnie Mae - Government National Mortgage Association (GNMA)
Pass Through Security
Real Estate Mortgage Investment Conduits (REMIC)
1. Solving The Mortgage Mystery by Barclays Global Investors, Investment Insights, 11.05
Mortgage-backed securities represent a major segment of the investment-grade fixed income universe in the United States and, therefore, a considerable portion of most investors’ fixed income portfolios. Despite their significant role in institutional portfolios, the complexities of mortgages have made it difficult for many investors to fully understand the idiosyncrasies associated with this asset class.
This paper sets out to help investors gain a better understanding of mortgages so they can effectively manage value and risk within the asset class and separate beta risk from alpha opportunities.
2. Analysis of Mortgage Backed Securities by Stein, Harvey J., Belikoff, Alexander L., Levin, Kirill and Tian, Xusheng, (January 5, 2007).
Valuation of mortgage backed securities (MBSs) and collateralized mortgage obligations (CMOs) is the big science of the financial world. There are many moving parts, each one drawing on expertise in a different field. Prepayment modeling draws on statistical modeling of economic behavior. Data selection draws on risk analysis. Interest rate modeling draws on classic arbitrage pricing theory applied to the fixed income market. Index projection draws on statistical analysis. Making the Monte Carlo analysis tractable requires working with numerical methods and investigation of a variety of variance reduction techniques. Tractability also requires parallelization, which draws on computer science in building computation clusters and analysis and optimization of parallel algorithms.
Here we detail the different components, describing the approach we have taken at Bloomberg in each area. Our particular emphasis is on the new interest rate modeling component we introduced for computing OAS, and the methods used to calibrate it accurately. We discuss the methods used to enable real time analysis of CMOs, analyzing the impact of various Monte Carlo variance reduction techniques as well as the technology used for parallelization of the computations. We also detail the validation of these components, showing that everything works well together, and yields good MBS and CMO valuation.
3. How Resilient are Mortgage Backed Securities to Collateralized Debt Obligation Market Disruptions? by Mason, Joseph R. and Rosner, Josh, (February 13, 2007)
The mortgage-backed securities (MBS) market has experienced significant changes over the past couple of years. Non-agency ("private label") securities, which are not guaranteed by the government or the government sponsored enterprises, now account for the majority of MBS issued. In this report, we review the rise of collateralized debt obligations (CDOs), the relaxation of lending standards, and the implementation of loan mitigation practices. We analyze whether these structural changes have created an environment of understated risk to investors of MBS. We also measure the efficacy of ratings agencies when it comes to assessing market risk rather than credit risk. Our findings imply that even investment grade rated CDOs will experience significant losses if home prices depreciate. We conclude by providing several policy implications of our findings.
4. Where Did the Risk Go? How Misapplied Bond Ratings Cause Mortgage Backed Securities and Collateralized Debt Obligation Market Disruptions by Mason, Joseph R. and Rosner, Josh, (May 3, 2007)
Many of the current difficulties in residential mortgage-backed securities (RMBS) and collateralized debt obligations (CDOs) can be attributed to a misapplication of agency ratings. Changes in mortgage origination and servicing make it difficult to evaluate the risk of RMBS and CDOs. We show that the big three ratings agencies are often confronted with an array of conflicting incentives, which can affect choices in subjective measurements of risk. Of even greater concern, however, is the fact that the process of creating RMBS and CDOs requires the ratings agencies to arguably become part of the underwriting team, leading to legal risks and even more conflicts. We analyze the fundamental differences between rating structured finance products like RMBS and CDOs and traditional products like corporate debt. We show that the inefficiencies of rating RMBS and CDOs are leading investors to discount U.S. markets. We conclude by providing several policy implications of our findings.
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