Asset-backed Securities Definition
An asset-backed security (ABS) refers to a security that is collateralized by a pool of financial assets. This asset-backed security derives its income payment and values from the pool of assets and serves as its collateral. An ABS derives collateralization from royalties, credit card debts, receivables, loans and leases. The specified pool of assets that collateralize an ABS cannot be traded individually since it is a pool.
A Little More on What is an Asset-backed Security
The cash generated through ABS provides more funding for issuers which they package as loans. Companies that issue asset-backed securities package these securities as a pool of loans sold as securities. The process of packaging pool of loans issued and sold as securities is called securitization. ABS are packaged as a pool because they cannot be sold separately.
Investors of asset-backed securities are also exposed to an avenue to invest in a diversified and revenue-generating assets. The poll of assets that back up these securities include equity loans, credit card debts, student loans, receivables, loans, among others.
There are multiple benefits of Asset-Backed (AB) Securities. Mainly, they provide a way for lenders to obtain funds to lend. These securities provide traders an investment opportunity in a wide-ranging group of income-generating assets.
In comparison to other income generating securities, for example Treasuries and corporate bonds, the market for asset-backed Securities market is less developed and can be more volatile. It is important because cash flows back the AB security, rather than physical assets. For example student loans, home capital loans, car loans, and credit card receivables are commonly securities into ABSs.
Example of Asset-Backed Security
This illustration is important for a clearer understanding of how asset-backed security work;
Company XYZ issues automobile loans to borrowers, this company has issued loans to the point that there is no more cash left to facilitate other loans. Once Company XYZ sees that it has no more cash for loans, it packages all the loans it has currently issued (including the expected interest payment) and sells to an investmnet bank who pays Company XYZ cash with which it makes more loans.
The Investmnet bank that has purchased the loans categorize them in line with their interest rates, maturity dates and delinquency rate. The different groups created are called tranches. The investmnet bank will proceed by issuing securities similar to what the tranches represents, these securities are sold to investors who receive income payments from the underlying assets such as the auto loan.
There are three tranches which are peculiar to asset-backed securities, these tranches are called;
- Class A tranche: This is the senior tranche and the most attractive to individual investors. It is the largest of all.
- Class B tranche: This is lower in credit quality when compared to the Class A tranche but has a higher yield.
- Class C tranche: this class of tranches cannot be issued or sold to investors because it has the lowest credit rating as well as a poor credit quality. Issuers accrue and absorb the losses associated with the Class C tranche.
References for Asset-backed Securities
Academic Research on Assset-backed Securities
Ali, R., Ismail, S., & Bakri, M. H. (2015). Procedia-Social and Behavioral Sciences, 201, 85-92. In this research, the author investigates a structure to provide loan securitization to the students. It also identifies the purpose of AB securities and it has proposed an Islamic structure of securitization. In this way, the students would be able to get enough funds for their studies. After completing their graduation they would be able to pay back their monthly subsidized borrowed money. Doing so, the Malaysian government will provide a continuous source of educational funds to the graduates of Malaysian university.
Term Asset-Backed Securities Loan Facility, Rhee, J. (2016). In this paper, the author explains the concept of TALF debt facility, i.e. Term Asset-Backed Securities Loan Facility. This is a special loan facility that assists the contributors of the market in meeting the household necessities as well as small business concerns using AB Securities.
Private Student Loan Asset Backed Securities: A Default Curve Analysis. Gentile, N. (2013). Mainstream media and companies pay great attention to the student borrowing industry that can cause threaten the economy. Students who get private loan components may not be the biggest part of the industry with 1 trillion USD. This paper evaluates the change in cumulative default percentage for personal student loan ABS issued in the time span of 2001 to 2007. This is extensive research and analysis that increases the conception of a minor understood place of the equity markets.
Securitization markets and central banking: An evaluation of the term asset-backed securities loan facility. Campbell, S., Covitz, D., Nelson, W., & Pence, K. (2011). Journal of Monetary Economics, 58(5), 518-531. In 2008, the Federal Reserve originated the term ABS Loan Facility in reply to the collapse of US securitization. This program decreased the interest rate for some types of ABS. But it caused a small impact on the cost of individual securities. It improved conditions in the securitization markets but did not support the individual securities. It is observed that there was a very little risk of loss to the United States government.
Prepayment and the valuation of mortgage‐backed securities. Schwartz, E. S., & Torous, W. N. (1989). The Journal of Finance, 44(2), 375-392. This research considers a framework for MBS ( Mortgage Backed Securities). Instead of forcing the most favourable call condition, it is supposed that there is a possibility of prepaying. It totally depends upon the current condition of the economy. The best possible techniques are used to estimate a prepayment function by using the recent aggregate GNMA prepayment experience. In this way, mortgage-backed securities are valued.
Valuation of GNMA mortgage‐backed securities. Dunn, K. B., & McConnell, J. J. (1981). The Journal of Finance, 36(3), 599-616. The amortising and callable debts pools support GNMA mortgage-backed securities. Most of the times, mortgagers pay loans in advance, in case, the interest rate in the market is more than the coupon rate of debts. This research analyses the effects of amortisation, prepayment and call characteristics on the prices using the GNMA securities model. These factors have a positive influence on the price whereas the call characteristic has a negative effect.
Rational prepayment and the valuation of mortgage-backed securities, Stanton, R. (1995). The Review of financial studies, 8(3), 677-708. This paper offers a new mortgage advance payments model. It depends on the rational decision of the mortgage owners. They bear costa of heterogeneous transactions. The authors use Hansen’s model of moments. They show statistical characteristics of mortgage advance payment. The mortgage holders have to wait for a year or more before they refinance, even in optimal conditions. So, the model discusses the statistical model presented by Torous and Schwartz in 1989.
Commercial mortgage-backed securities: prepayment and default, Ambrose, B. W., & Sanders, A. B. (2003). The Journal of Real Estate Finance and Economics, 26(2-3), 179-196. In the 1990s era, the main development in real estate loan was an introduction to the viable market for trading MBS (Mortgage Backed Securities). Now, the researchers are much interested in the statistical and theoretical research on the trading mortgage and advance payment. The authors use a risk model to inspect the advance payment and default behaviour of trading loans. Finally, the variations in the yield curve have an effect on the probability of mortgage dismissal. There is no empirical relationship in default or advance payment and LTV.
The Federal Reserve’s Term Asset-Backed Securities Loan Facility, Ashcraft, A., Malz, A., & Pozsar, Z. (2012). Federal Reserve Bank of New York Economic Policy Review, 18(3), 29-66. In 2008, the securitisation markets for ABS and CMBS had to face a barrier, because the traders reacted to a drastic decrease in funding liquidity. As a response, the Federal Reserve brought forth the TALF program. It provided term loans using securities as collateral to a specific class of CMBS and ABS buyers. This paper explains the TALF program, its activities, terms, and risk of loss. Ultimately, it is not easy to isolate the impacts of TALF. It has had great participation in 2009 to 2010 to restore liquidity.
Estimated impact of the Fed’s mortgage-backed securities purchase program (No. w15626). Stroebel, J. C., & Taylor, J. B. (2009). National Bureau of Economic Research. The authors check the quantitative aspects of the MBS purchase program. Their major concern is to look into the recent fall in mortgage interest rate spreads. It has become more complex because of the frequent changes made in the prepayments and risks. When they try to lower the risks, they get the proofs of statistically small effects of the program. Where there are lower spreads in the program, they notice that there is no effect of the size of the stock of MBS bought by the Fed.
How resilient are mortgage backed securities to collateralized debt obligation market disruptions?, Mason, J. R., & Rosner, J. (2007). In the last few years, there has been a fairly large change in the market of Mortgage Backed (MB) Securities. The government or its sponsored enterprise does not guarantee Non-Agency Securities. The author examines the flexibility in debt standards, the application of debt mitigation strives and the increase in CDOs (Collateralized Debt Obligations. The authors measure the efficiency of rating agents and analyses of market risk. Consequently, there is a huge loss to CDOs, if the home prices decrease.
Determinants of asset–backed security prices in crisis periods, Perraudin, W., & Wu, S. (2008). Determinants of asset-backed security prices in crisis periods. This paper investigates factors that contribute to the cross-sectional pattern of spreads in Asset-Backed Security (ABS) prices in times of crisis. The periods include the crisis in the Manufactured Housing sector in 2004 and the turmoil in mortgage-backed ABS in 2007. The cross-section of prices for a given rating category appear to be poorly explained by liquidity and risk and there is evidence of a collapse in market confidence in the ratings agency classifications.
Asset correlation in residential mortgage-backed security reference portfolios, Geidosch, M. (2014). Asset correlation in residential mortgage-backed security reference portfolios. Journal of Credit Risk, 10(2). This paper contributes to the literature about estimating asset correlation in two ways. First, we compare the performance of different estimation approaches in a simulation study. By doing so, we provide knowledge about the behavior of the applied estimators, which is an important precondition for the interpretation and robustness of the estimation results. Second, we present a novel data set from which to estimate asset correlation: the loss data of residential mortgage backed security (RMBS) deals. Our data set is largely made up of the most toxic RMBS deals that sparked the subprime crisis. Contrary to the widely held view, our analysis reveals that asset correlation in the subprime market is surprisingly low (roughly 6%). By giving an intuitive and straightforward explanation for these low values, we provide valuable insight into the mechanism and evolution of the subprime crisis in general, and into the risk characteristics of a credit portfolio in particular.
Deriving Credit Portfolio Diversification Properties from Large Asset–backed Security Pools, Higgins, E., & Mason, J. (2005). Deriving Credit Portfolio Diversification Properties from Large Asset-backed Security Pools. Working Papers: Financial Institutions Center at the Wharton Scholl. Studies of bank diversification, as well as Basel II regulatory framework, use indirect methods of characterizing the sources of diversification in bank portfolios. The present paper more directly estimates the sources of diversification in thirteen retail credit categories from asset-backed security performance measures that are highly correlated with (unobservable) loan value. Classical Markowitz correlations are derived from almost $1 trillion of asset backed security pools originated by more than five hundred issuers between January 2000 and September 2003. The analysis demonstrates that the performance of many different loan types is weakly correlated, and is sometimes even negatively correlated. Hence, even narrowly focused bank portfolios consisting only of standard retail credits can be constructed to obtain a great deal of diversification. That potential, however, is still not acknowledged in the Basel II regulatory framework.
Japanese and Korean Practices of Asset–backed Security and their Enlightenment [J], HE, X. N., & JING, J. (2008). Japanese and Korean Practices of Asset-backed Security and their Enlightenment [J]. International Economics and Trade Research, 8. Japan and Korea are the top two ABS (asset-backed security) countries in Asia in terms of both ABS values and types they issue. This paper indicates some features of their ABS markets,such as various kinds of assets for backing and complicated designs of securities in Japan,and strong support from governments on both credit and laws in Korea,as well as active participation of international investment banks and talents in the whole process. Therefore,it is suggested that to develop the ABS market of our country,we should perfect our laws,improve the related markets,learn experiences from other countries,and cultivate knowledge-intensive talents with relevant discipline.
Sense and sensitivity: An input space odyssey for asset–backed security ratings, Di Girolamo, F., Jonsson, H., Campolongo, F., & Schoutens, W. (2012). Sense and sensitivity: An input space odyssey for asset-backed security ratings. International Journal of Financial Research, 3(4), 46-68. The rating of asset-backed securities is partly based on quantitative models for the defaults and prepayments of the assets in the pool. This quantitative approach contains a number of assumptions and estimations of input variables whose values are affected by uncertainty. The uncertainty in these variables propagates through the model and produces uncertainty in the ratings. The objectives of this paper are twofold. Firstly, we advocate the use of uncertainty and sensitivity analysis techniques to enhance the understanding of the variability of the ratings due to the uncertainty in the inputs used in the model. Secondly, we propose a novel rating approach called global rating, that takes this uncertainty in the output into account when assigning ratings to tranches.