Valuation Methods of Collateral Mortgage Obligations - Dissertation Example

?COLLATERALIZED MORTGAGE OBLIGATION VALUATION METHODS By Brian George A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Business Administration University of Phoenix November 2012 © 2012 by BRIAN GEORGE ALL RIGHTS RESERVED COLLATERALIZED MORTGAGE OBLIGATION VALUATION METHODS by Brian George November 2012 Approved:   Mohammad Sharifzadeh, PhD, Chair Lewis Termares, PhD, Committee Member Barry Spiker, PhD, Committee Member Accepted and Signed:                                                                                                             Mohammad Sharifzadeh Date    Accepted and Signed:                                                                                                             Lewis Termares Date    Accepted and Signed:                                                                                                             Barry Spiker Date                                                                                                                                       __________________ Jeremy Moreland, PhD Date    Dean, School of Advanced Studies University of Phoenix Abstract Begin Dedication Begin Acknowledgments Begin Table of Contents COLLATERALIZED MORTGAGE OBLIGATION VALUATION METHODS i COLLATERALIZED MORTGAGE OBLIGATION VALUATION METHODS iii Abstract iv Dedication v Acknowledgments vi Table of Contents vii List of Tables x List of Figures xi Chapter 1: Introduction 1 Background of the Problem 2 Statement of the Problem 3 Purpose of the Study 5 Significance of the Problem 6 Nature of the Study 8 Research Questions 10 Hypotheses 10 Theoretical Framework 11 Definition of Terms 14 Assumptions 14 Scope, Limitations, and Delimitations 15 Summary 15 Chapter 2: Review of the Literature 18 Historical Overview 18 Literature Review 27 Securitization and the Mortgage Market 31 The Evolution of Financial Exploitation 32 From the Margins of the City to the Core of Global Finance 33 Balanced Discussions and Alternative Viewpoints 34 Identified Research Gaps 35 Conclusion 38 Summary 40 Chapter 3: Method 1 Research Method and Design Appropriateness 1 Population, Sampling, and Data Collection Procedures and Rationale 4 Informed Consent, Confidentiality, and Geographic Location 5 Data Collection 5 Appropriateness, and Reliability and Validity of the Instruments 6 Internal Validity and External Validity 8 Data Analysis 8 Hypotheses 11 Description of Questionnaire Formulation 11 Findings of the Research (CMO Valuation Model) 13 Summary 13 14 References 14 Appendix A: Title 21 List of Tables List of Figures Chapter 1: Introduction The proposed quantitative descriptive research study involves the various valuation methodologies of prepayment speeds within collateralized mortgage obligation (CMO) tranches. The study involves analyzing how the prevalent valuation methods are useful in current complex economic scenarios. The objective of the proposed study is primarily to examine the applicability of various methods of valuation for pricing the CMOs so as to determine their validity in the present economic conditions. Collateralized mortgage obligations are derivative debt instruments that can be aptly defined as the claim that arises out of cash flows from large pools of home mortgages. The advantages of the CMO structure is that once mortgage holders receive principal and interest, the principal and interest is distributed to tranches. The principal amount, the coupon rate, the prepayment risk, and the maturity date differ among the tranches (Economy Watch, n. d.). Collateralized mortgage obligations can provide within specific tranches to both retail and institutional investors the possibility of higher yields in comparison to other government instruments with a Standard & Poor’s (S&P) AA or AAA ratings. Bartlett (1989) stated, “Mortgage Backed Securities (MBS) out performed 10 year Treasury bonds by 304 basis points in yield each during the six year period 1982-1988” (p. 59). More recently, as indicated by Double Line Capital, during the period of April 2010 through March 2012, MBS out performed the Barclays U.S. aggregate index by 8.21%. Of disadvantage to the investors is that CMOs are sensitive to exposure to the interest rate risk and prepayment risk. The first major exception to the record of consistent superior performance by MBS sector was in the spring of 1986, “when more than 50 percent of all MBSs were premium-priced coupons, and market yields fell by some 400 basis points. The resulting sudden explosion in prepayment rates caused a devaluation of the premium-priced MBS sector during that period” (Bartlett, 1989, p. 61). The proposed study will therefore involve determining a standardized valuation model for CMOs by considering the factor of risk. The proposed study will focus mainly on risk factors associated with valuation methods because the current risk has evolved as an important factor in the present uncertain environment, inclusive of the economic condition of the country (Johnston, Greer, Biermacher, & Hummel. 2008). Chapter 1 is an introduction to the dissertation study. Background information, research questions, hypotheses, limitations, are presented to provide understanding of the problem and purpose for the study. The conclusion of Chapter 1 includes a summary of key points presented, including key definitions, transitioning into the literature review in Chapter 2. Background of the Problem One of the reasons behind the decline of CMO valuations was the U.S. Subprime crisis that occurred in the middle of the year 2007 and 2008 (U.S. Securities and Exchange Commission, 2008). During the crisis, stock markets fell, large financial institutions collapsed, and returns of the debt instruments declined. These events became a social concern as they affected society by eroding away investments in various financial instruments, including CMOs. The global financial meltdown affected the livelihoods of a number of people. The subprime crisis arose because of several factors including the enormous securitization due to bank pooling their various loans into sellable assets and thus transferring risky loans onto others. According to a report of British Broadcasting System’s former presenter and Editor Evan Davies, the rating agencies were unethically paid to rate the less productive securitized products for personal interests. Banks borrowed large amount of money to lend so they could create more securitization. For example, Lehman Brothers bought large numbers of mortgages, mixing collateral pools during securitization and selling to other institutions and investors. Commercial banks mimicked the internal investment and operations investment banks, who are not authorized to buy, sell, and trade risk by jumping into selling home loan products and mortgages without the right control and management strategy. The banks increased their exposure to problems when risk concerns were subordinated to keeping up with the success of competitors (Shah, 2010). Since 2008, more than 200 banks have failed. The Federal Reserve and other bank regulators embarked on a comprehensive assessment of the capital held by the 19 largest U.S. banks, and ordered 10 of them to raise a total of $75 billion in extra capital (Bandic, 2009). One of the reasons behind the great financial turmoil is the valuation models of asset backed securities. Increasing credit securitization is responsible for the ill effect on society and economy (European Central Bank, 2008). The bank failures may have been totally or partially avoided with an adequate level of stress testing or pricing models that enabled a better understanding of the risk exposure.  Statement of the Problem The general problem is that the complexity of CMOs requires institutional and retail investors to have accurate reporting of the status of the underlying collateral and how collateral is likely to perform in varying interest-rate environments. This pipeline management, as described by the Federal National Mortgage Association, requires managers to make a series of choices, such as how much risk to take in the view of the outlook for interest rates and how much to pay to hedge against interest-rate risk. Hedging requires familiarity with several hedging strategies, many of which introduce risks of their own. The challenge of managing CMOs is twofold: knowing how to hedge and making the decision of when to hedge. The specific problem examined in the proposed study is that current-pricing models cannot quantify risk (Klapper, Byron, & Nadler, 2005). Current research in the field of repayment modeling has resulted in two commonly used repayment models. The rational prepayment survey model is where mortgagers pay for the value of the mortgage that exceeds the remaining principal balance of costs incurred as a result of refinancing plus the principal balance (Bandic, 2009). The rationale prepayment approach is resilient to the structural changes that occur in the economic environment, but the approach does not perform well when valuating CMO tranches. The other approach is the estimation technique. The prepayment models used are developed using mathematical equations that relate environmental assumptions to rates of repayments that can actually vary from time to time. Computation problems within mortgage pricing are based on three factors. First, that mortgages allow the prepayment option, possibilities. Mortgages often pay adjustable rates that are indexed to some market indicators that do not have any specified term structure. Second, mortgages are path-dependent instruments--mathematically meaning that aside from the interest rate factors, the value of the same may depend on some set of additional variables. Levin (1998) stated, “The list includes coupon, current ARM index, current collateral balances on every CMO tranche” (p. 266). Lastly, mortgages are multifactor instruments as their value depends on inaccurate modeling parameters that causes volatility within pricing factor. Prepayment speeds can be structured with certain accuracy and tend to deviate from the structured model. The structured modeling error can be treated as a factor not correlated with the interest rates. Interest rates, which are not related the mortgage market, do not provide efficient trade factors and bears some systematic risk in addition (Levin, 1998). Problems regarding the present valuation methods of CMOs are the basis for conducting the present research. Gaining insights from the generic problem, the specific problem is ascertaining a standardized valuation model for CMO retail custodian platforms that considers the factor of risk in valuation process. The problem will be addressed using a quantitative descriptive approach to reviewing the techniques are currently following. Historical data related to CMOs will be collected to help determine the relationship between assumption of CMO prepayment speed and actual maturity dates of Federal National Mortgage Association (FNMA) supported tranches model values versus listed sale price and executed trades. The general population for the proposed study will be all the CMOs underwritten by the member firms of the Financial Industry Regulatory Authority (FINRA). The sample will consist of those CMOs underwritten by former Merrill Lynch, Pierce, Fenner and Smith Inc. Purpose of the Study The purpose of the proposed quantitative descriptive research study is to establish a standardized valuation model for CMO retail custodian platforms. The CMO model is founded on a two-factor model of term formation of interest rates, and also presents an estimated mortgage pre-payment purpose. Bloomberg Analytics use the CMO model to examine diverse CMO tranches, standard sequential pay fixed-rate tranches, planned amortization class (PAC) tranches, targeted amortization class (TAC) tranches, floating-rate tranches, interest only (IO) and principal only (PO) tranches, Z-bonds and the residuals (McConnell & Singh, 1993). The proposed quantitative descriptive study determines a standard valuation model for CMOs by considering the historical factor of risk. The study also determines the extent to which CMO prepayment speed assumptions and actual maturity dates of FNMA supported tranches relate to another debt instrument valuation method, such as U.S. treasury Bonds. Finally the proposed quantitative study projects a standardized valuation model for CMO retail custodian platforms. The independent variable will be the FNMA supported tranches and the dependent variable will be the U.S. treasury Bonds. The general population will be National Association of Security Dealers (NASD) member firms, and the sample will be CMOs underwritten by Merrill Lynch, Pierce, Fenner and Smith. Secondary data analysis entails creating a research question for transposing existing historical data (Kelman, 2002) for research purposes. Significance of the Problem Importance and contribution to current and future research thoughts. With the evolution of the secondary mortgage market, CMOs have shown their importance and growth potential. When initially developed, CMOs were very simple instruments; however, with changes in credit lending needs, the structures of CMOs and the CMO tranches have increased in complexity. The significance of the proposed study is that it will help in the analysis of the most efficient valuation methods of CMOs. Independent auditors and researchers testified, “Because CMOs were illiquid, they could not be valued based on contemporaneous market transactions. The valuations utilized were based instead on sophisticated valuation models” (Cornerstone Research, n.d., p. 3). The proposed research study could potentially help to find the various methodologies that are being followed in valuing and calculating the prepayment speeds of CMO tranches and the suitable method of its valuation in adverse situations of an economy. The proposed research study could potentially show that the desired accuracy of a CMO model used for any cash flow projection needs to rely mostly on relative importance of CMO holdings in a portfolio and the relative instability of the CMOs held. Cash flows of tranches depend on the cash flows of the other tranches and the dynamic prepayment rates of over period of time as the rate of interest changes. The findings could also include whether individuals can use grouping methods for modeling CMOs, as well as what prepayment rate assumptions are required to consider the CMOs and to how to find suitable ways to identify the market value of CMOs at future points of time. Significance of the study to the field of leadership, knowledge, and literature. As the proposed research study is about the valuation methods of CMOs, the proposed study will help to develop knowledge of prevalent models of different securitization products that are available. The mortgage world is commingled with many elements of human behavior, making mortgage analytics very challenging, but also highly useful to institutional and retail investors.  Individuals use models to forecast defaults, estimate counterparty risk, value complex derivatives, and analyze a variety of risks.  Models are critical in the decision-making and risk assumption processes inherent in our financial system. Testing valuation models will help in the management of financial assets and assist in decision-making processes.  Nature of the Study The proposed study involves examining and determining a standardized valuation model for CMOs by considering the risk factors, taking into consideration the effect of independent variables of prepayment speeds, issuer, and interest rates. The results of the study could be useful in understanding the views of the larger population on the problem being studied (Creswell, 2008). The research method chosen for the proposed study is quantitative. The quantitative method is best when the problem stated is very specific, stipulations are fixed, and the dependent and independent variables are clearly and precisely specified. Under the quantitative method, the research goals are followed firmly. Conclusions arrived at are more objectively specific, and hypothesis are tested and some designs are determined. Quantitative research is generally approached by collecting empirical data, carrying out measurements, and developing models. Results are explained with spreadsheets, percentages, and statistics. Structured interviews can be conducted to produce exact answers entered into a spreadsheet. Surveys with multiple choice questions or phone interviews and direct mail initiatives to consumers can also solicit specific and exact answers. Qualitative research is conducted using “participant observation, direct observation, unstructured interviewing, and case studies” (Creative, 2007, p. 11) The qualitative research method is not appropriate because of shortcomings to the proposed study. Bias may exist, as qualitative methods depend on the personal judgment of the researcher. The researcher needs to be highly experienced in order to derive valid conclusions from participants. Causality cannot be determined or explained by qualitative research. A research design is good only when selected by considering the nature of the research study. The appropriateness ought to be based on the certain basic features. If the research study is exploratory-- focused on discovery of certain traits--then the research design should be flexible with the intention that various phenomena can be attributed. However, if the purpose of the study is to arrive at an accurate description of a situation or relation between variables, the research design must be one that is absolutely free from biases and one that enhances the reliability of evidences presented. The proposed study purpose is to project a valuation method for the CMO retail custodian platforms requires a descriptive research design to measure the required outcome. The descriptive research design follows the scientific method, which involves observing and describing the behavior of a participant without influencing the participant in any way (Glatthorn & Joyner, 2005). The descriptive research design is an effective method for researching specific participants and is a precursor to additional quantitative studies. The disadvantage to a descriptive design is some valid concerns exist about the statistical validity since there are no variables manipulated. The proposed study could have used a correlational research design to investigate how variations in independent variables correspond with CMO valuations models. A correlational research design is appropriate when a study has one or more predictor variables (Salkind, 2006). The correlational design was not selected based on the known fact that CMO income streams are formula driven and are designed to react to changes in prepayments and interest rates; the proposed study is only addressing possible valuation methods. Research Questions The importance of research question is to define the focus of a particular study. The focus of the proposed research study is on the following research questions: RQ1: What, if any, is the degree of relationship between the yield of FNMA-supported tranches and return on the U.S. treasury bonds? RQ2: What, if any, is the degree of relationship between the yields of FNMA-supported tranches and the assumption of the prepayment speed? RQ3: What, if any, is the degree of relationship between the average life of investments through CMOs and the prepayment speed? RQ4: How does the degree of relationship provide the basis of determining a standard pricing model for valuing CMOs? Hypotheses Four null will be tested in the study. The null and alternative hypotheses are below. H10: There is no statistically significant difference between the yield of FNMA supported tranches and return on U.S. treasury bonds. H1A: There is a statistically significant difference between the yield of FNMA supported tranches and return on U.S. treasury bonds. H20: There is no statistically significant difference between the yield of FNMA supported tranches and prepayment speed assumptions. H2A: There is a statistically significant difference between the yield of FNMA supported tranches and prepayment speed assumptions. H30: There is no statistically significant difference between average life of investments through CMOs and prepayment speed. H3A: There is a statistically significant difference between average life of investments through CMOs and prepayment speed. H4o: There is no statistically significant difference between the traditional and derived pricing model for valuing CMOs. H4A: There is a statistically significant difference between the traditional and derived pricing model for valuing CMOs. Theoretical Framework Significant literature is available on the valuation of mortgage-backed securities. Kenneth Dunn introduced the first model for a mortgage-backed security, which was followed in 1981 by a number of papers prepared in cooperation with McConnell. In the first introduced model, prepayment was treated as a call option and the model was developed basing the decisions on optimal financing. Although the model was concerned with connecting prepayment and valuation, the assumption for prepayment was based on immediate action of prepayments by the mortgagors during the period when rate of interests become excessively high. Thus, the model was improved further by incorporating transaction cost and other related costs to explain decisions related to refinancing. Observing that investors might not choose to exercise their options during the period when the rate of interest is low, during the next few years, the model was improved by adding an option probability model. The structural model was founded upon the general idea of public-believed fluctuations based on variables such the value of houses and rate of interests (Dunn & McConnell, 1981). The structural model was dependent upon excessively complex calculations, leading other practitioners to develop an easier and more convenient model--the reduced form model. The reduced form model is based on the assumption that exercise of options is established on a prepayment model. In the reduced form model, evaluation of mortgage prices are undertaken through following the technique of discounted case flows to present value. The basic thought behind the reduced form model is that the prices of the mortgage backed securities at the present time period has to be the total cash inflow’s present value that has the potential to be earned during the future (Huamg, 2004). Despite the prevalence of a number of valuation models for mortgage-backed securities, the characteristics of cash flows had not been able to satisfy demands of various investors. Investors needed such an instrument to provide options for a number of profiles, with respect to maturity and periods of prepayment associated with their investments. For satisfying the demands of the investors, during 1983, individuals introduced the CMO. In CMOs, the investors enjoy the privilege of choosing from a number of tranches with varied period of maturity and profiles of prepayment. Currently, a wide variety of instruments of mortgages backed securities are available to the investors in the form of CMOs. Collateralized mortgage obligation valuation models are formed using a two-factor model based on term structure of the interest rates. The interest rates consist of sequential pay bond series or mortgage-backed securities, and the structure of the two-factor model has become more complex over time. Collateralized mortgage obligations are amalgamations of tranches--of planned amortization class (PAC) and targeted amortization class. The mortgage prepayments and variability of interest rates will affect different CMO tranches. The model to be formulated in the proposed study will vary from earlier models by defining the stochastic cash flows and the terminal condition for all the CMO tranches concerned in the mortgage issuance. The resultant effects of the model are that the tranches are quite sensitive to alterations in interest rates, CMO structure, and the nature of mortgage structure and collaterals. Collateralized mortgage obligations should be structured so that even when unfavorable circumstances exist, apt cash flows is available pay for the interest due and the entire principal. The CMO structuring is done using two methods, including ensuring that total sum of all principals scheduled for the bonds are always equal to the total principal of the collateral (Davidson & Ho, 2002). The second method requires the total yield CMO bonds to not be more than or equal to the purchase yield when it is added to profit and issuance expenses (McConnell & Singh, 1993). The models present for valuating of CMOs do not incorporate the level of risk associated with the CMOs that are sometimes held for a very long period of time. The risks include prepayment risk, interest rate risk, re-investment risk, and default risk. An analysis of past literature about the valuation models indicates a comprehensive evaluation of the models is lacking. Therefore, the proposed focused on generating a specific valuation model for CMOs was identified. The future model will be formulated on the basis of various dynamics of the CMOs’ features associated with the different uncertainties within the present financial market, giving rise to excessive prevalence of risk. Definition of Terms Actual maturity. The actual maturity of a bond determines the real date where the bond has been cashed out and when the investor has received the face value of the bond (Fabozzi, 2001). Planned amortization tranches. Planned amortization tranches is the measure of prepayment risk that include both extension and contraction of risk, which are limited by the size and limited payment of bonds (Fabozzi, 2001). Prepayment speed. Prepayment speed is how quickly mortgage borrowers in a securitized pool of mortgage loans will refinance or repay their mortgages (Fabozzi, 2001). Securitization. Securitization is the process of converting the illiquid assets or group of assets into security through the process of financial engineering (Fabozzi, 2001). Tranches. Tranches are the pieces or portions of deals consisting of a number of correlated securities. The principal amount, coupon rate, prepayment risk and maturity date differs among the tranches (Fabozzi, 2001). Assumptions Building models in the social sciences to simulate an experiment is challenging. Over time, human beings will not necessarily act in the same manner.  As a result, modeling that involves elements of human behavior (such as prepayment and default) is quite difficult, and testing these models is even more difficult.  Despite these challenges, modeling and model testing have a prominent place in real world applications from measuring risk to asset valuation to financial forecasting. Within the proposed research study, the assumption is the markets are uncontrolled and the mortgager exercises a call option as soon as the value of the mortgage uncalled exceeds the face value of the loan. In all mortgage valuation models, the value of the generic mortgage backed securities is the sum of value of the individual mortgages that support the tranche after deducting the fees associated with insurance and service of the mortgaged assets. The outcome of the model is the mortgage-backed securities never sell at prices above the original face value (McConnell, 1994). Scope, Limitations, and Delimitations The scope of the proposed research study is to gather data on one type of CMO tranche. To make the study precise and accurate, the scope is narrowed to include only those CMO support tranches underwritten by FINRA. Collecting past CMO data FNMA has underwritten by selected banks, in a wide manner, is complex as valid data sources are hard to find. Collecting primary research data also limits the scope of the proposed study as participants might be reluctant to provide past records. The scope of the research is confined to collecting data related to CMOs underwritten by Merrill Lynch, Pierce, Fenner and Smith and Goldman Sachs over a 14-year period. By setting up the boundary in the proposed study, the complexity of wide reach of data will be reduced—also limiting the external validity of the study’s findings. Summary The proposed quantitative descriptive research study focuses on various valuation methodologies of prepayment speeds with CMO tranches and analyzing how the prevalent valuation methods are useful in current complex economic scenarios. The objective of the proposed study is primarily to examine the applicability of various methods of valuation for pricing the CMOs and determine their validity in the present economic conditions that are surrounded with uncertainties. Models are used everywhere from forecasting defaults to estimating counterparty risk, valuing complex derivatives, and analyzing a variety of risks.  Models are critical in the decision-making and risk assumption processes inherent in the financial system. Testing valuation models may help the management of financial assets and assist in decision-making processes.  Since 2008, more than 200 banks have failed. These misfortunes may have been avoided or partially avoided had there been an adequate level of stress testing or pricing models that enabled a better understanding of the risk exposure.  Chapter 1 was an overview of the valuation strategies in collateral mortgages. The chapter opened with discussion of the statement of problem under study. The scope of the research study was discussed, including the nature of the study, the theoretical framework, and definitions of important terms. Further, Chapter 1 also included the hypotheses and the research questions guiding the research. Furthermore, the chapter included discussion of the scope and potential limitations forming the boundaries of the research. Also included was discussion of assumptions. The chapter included a summary of methodologies that are generally followed in valuation of collateralized mortgage obligations. Also included was an overview of the CMOs, a description of different structures of CMOs, calculation of the prepayment speeds of CMO tranches, and the effect of variations in interest rates on the mortgage backed securities. The chapter also included discussion of the subprime crisis and the sharp decline of CMO products in market, the yield that can be obtained investing in CMOs, and the effective valuation methods of CMO like the Grouping Model, the Monte Carlo model and the Hull-White Model of calculation. Chapter 2 includes a review of literature. The chapter begins with a review of the title search process. Included is a theoretical review of literature detailing the construction of CMOs and the dynamic behaviors of mortgage-backed securities and models illustrating their volatility time-variance Chapter 2: Review of the Literature The problem examined in the proposed research is that the present valuation models of the CMOs fail to quantify risk. Considering the present financial conditions, quantifying risk in the CMO valuation model is of extreme importance. The proposed research study is a quantitative study with the objective of creating a standard method of valuation of prepayment speeds with CMO tranches. Chapter 2 includes a review of existing literature about the dissertation topic; for example, reviewed is literature on valuation methods of the collateral mortgage obligations. The chapter includes an evaluation of the findings of the past researches and incudes discussion of existing research gaps. The chapter concludes with precise determination of the identified research gaps and what can be done to bridge the gap. In the following sections of the literature review, the searched materials are discussed in-depth. The literature of the past was collected from various sources such as published journals, articles, and books. Libraries were thoroughly searched in order to identify relevant publications and form a thorough understanding of existing literature. Along with various reliable publications, the Internet was comprehensively searched. Various authenticated and reliable sources of the Internet were researched taking into account their importance in the present research. Historical Overview The literature review on collateral mortgages was first done by comparing and contrasting the findings of former researchers. The reviewed literature provided the researcher with a glimpse of the existing knowledge on the topic under investigation and helped to set the scope and limits of the research. According to Johnston et al. (2008), CMOs are very attractive derivative debt instruments because they draw investors by their high yield. Derivative debt instruments are very sensitive since they are exposed to the interest rate risk. Apart from the interest rate risk, investors of CMOs also face prepayment risk. The housing and financial bubbles that took place in late 2006 and 2007 resulted in a great crisis and resulted in a sharp decline in the demand for CMOs. The problem is that current-pricing models cannot quantify risk. The rate of repayment actually affects the risk, the profit, and the lifetime of the CMO (Johnston et al., 2008). The study of McConnell and Singh (1994) provided knowledge of a model for evaluation of CMO, based on the structure and underlying rate of interest, helping to achieve an experimental estimation of mortgage prepayment function. The two-factor model used is very helpful for analyzing various CMO tranches: bench-marked sequential pay fixed rate tranches, planned amortization class (PAC) tranches, targeted amortization class tranches (TAC), floating rate tranches, interest only tranches, principal only tranches, Z- bonds, and other residuals. McConnell and Singh’s analysis broadly illustrated the sensitivity of diverse tranches indifferent to CMO structures, interest rate, and types of underlying collateral and mortgage prepayments. Collateralized mortgage obligations generally reallocate the call risk of various mortgage collaterals among the investors holding differing in tranches. Many of the tranches consist of unequal share of the call risks that make the values very sensitive to the mortgage prepayment rates. The value of mortgage calls has an inverse relationship with the interest rates. When the rates rise, the value of the mortgage call falls; when the interest rate falls, the mortgage call rate rises (McConnell and Singh, 1994). With respect to the suggested models for valuation of CMOs, Kelman (2002), who published in the Journal of Index Investing, compared the effectiveness of low discrepancy methods with the Monte Carlo methods on the valuation of the financial derivatives. Findings from the CMO with ten bond tranches, provided by Goldman Sachs, indicated that the less discrepancy method was much more effective valuing a particular CMO, even though many use the Monte Carlo method to evaluate the complicated financial instrument (Paskov & Traub, 2010). Compared to the Monte Carlo methods of valuation methodology, the low discrepancy method takes into consideration the deterministic points. According to Paskov and Traub (2010), the deterministic method is superior to the Monte Carlo method because both the modified Sobol methods and the generalized Faure method are considerably quicker. The Monte Carlo method is much responsive to the initial seed (Silva, 2005; Papageorgious & Traub, n.d.). According to Dov (1992), in the past four years (1998-1992), Prudential Securities Inc. built a Mortgage Backed Securities (MBS) department. Dov (1992) stated that inadequate standard fixed income valuation tools exist to deal with the complexity of the financial securities. The growth and success of the department has been due to development of accurate and sound models. The models are based on and developed using variety of management sciences including probabilistic modeling, regression analysis, Monte Carlo simulation, and linear integer and nonlinear programming. The suggested models permit the firm to price and trade the complex MBS’s swiftly and correctly. The models also help to appropriately hedge MBS’s in inventory, and to structure a client’s portfolio with the purpose of attaining specified set of objectives although staying within particular constraints. Traders, sales personnel, and clients use the models several times each day to evaluate MBS’s and the models are the basic tools necessary for a firm to take part productively in the mortgage market (Dov, 1992). According to Dokko (2007), CMO is one type of debt instrument collateralized by mortgage pass through certificates or individual mortgage loans. The mortgage instrument that serves as collateral is generally a single-family Government National Mortgage Association (GNMA). The instrument passes through a security that has a proportional rate of interest along with principal each month to its owners. Because of pro rata distribution mechanism, the negative point of the traditional mortgage pass through securities is observed with doubtful cash flows associated with volatile prepayments on the underlying mortgages. Dokko (2007) stated that payments of CMO are divided into four categories, also called tranches. The former three tranches obtain scheduled interest payments. After the principal to the first class of the CMO is repaid, principal payments obtained from the underlying mortgages are distributed to leave the remaining classes. The interest from the second tranche is received up to the point when the principle from the first ranches is paid out. The third tranche will only receive interest when the first and second tranche principle sums are paid off. The fourth tranche is an accrual or a “Z” bond that obtains interest and principal until the principal owing to all previous tranches is paid off. The CMO is intended to change a long-term monthly payment instrument into a sequence of semi-annual payments, bond like securities with both short immediate and long maturities. According to Dokko, an important assumption in the theory is the investors have different preferred maturities; therefore, they are willing to pay different prices for their securities for different expected maturities. Further, CMOs entrance into the mortgage market attracted “non-traditional” investors, such as pension funds and insurance companies (Bandic, 2010). According to Ramm (2010), although many CMO issues emerged in the market and had flat or yield curves, a CMO needed a positively yield sloped curve. Yield on MBS’s rose, and spreads between regular MBS’s and treasuries broadened as thrifts liquidated MBS’s from their portfolios. The spreads were wider, although not for success of the derivative products in keeping the spreads stable. The stability of spreads is due to arbitrage opportunity. The performance of CMOs also depends on the classes of the issue. Ramm (2010), stated there may be planned amortization class (PAC) bonds, whose investors do not absorb any share of early principal repayments within given PSA range. If alterations occur in the prepayments, the fluctuations have a negative effect on the non-PAC classes whose values may alter to a great amount. Ramm also added that the residual or the CMO equity reduces prepayments. The residual supplies the dealer’s profit on a CMO; no profits are recognized until the residual is disposed off (Dokko, 2007). The Securities Industry and Financial Markets Association (SIFMA) provided an overview of the lowest amount of investment costs related to transaction and liquidity of CMOs. According to SIFMA (2006), the least amount invested for a CMO differs per the structure of the offering, but nearly all of the tranches are being sold to the separate investors, demand a minimum investment of $1000. The CMO investments are also available in the form of mutual funds or units of trust that usually have the same investment amount. These transactions are passed out over-the-counter, directly from the dealer-to-dealer, and not through any exchange. The trading of CMO in the market is similar to any other debt instruments. Compared to the CMOs, the treasury security dealings have a wide and deep secondary market and are therefore much more liquid. The interest portion of payments to CMO investors follows the federal, state, and local income tax regulations. SIFMA (2003) commented that while comparing the treasury yields to the CMO yields, the investors should know the interest income from the treasury securities is absolved from state and local income tax. According to Lore & Borodovsky (2000), the U.S. mortgage backed securities market has grown extensively in the last 20 years. Much of the growth has been in the form of the CMOs and the real estate mortgage investments conduits. According to SIFMA (2010), CMOs account almost 40% of the entire fixed rate mortgage backed securities outstanding. These securities primarily appeal to the investors who are eager to accept long and uncertain investment horizons in exchange for comparatively high yields and the credit quality. The markets for CMOs developed fast, rising in size and difficulty. But, CMO issuance declined between 1994 and 1996 for a variety of reasons. Higher mortgage rates reduced the refinancing activities and resulted in the lower MBS collateral issuance. With the lower prepayment volatility and mortgage securities, the investors chose to hold the pass through instead of the CMOs. At the same time, bank demand for CMOs softened, as lending activity finally began to rise after the credit crunch years of 1991-1993(Standard and Poor’s Financial Services, 2010). Many of the hedge funds that had been buyers of more high risk and high yielding tranches turned to other investments. According Lore & Borodovsky (2000), probable prepayment behavior is a critical factor in evaluating CMO collateral. The three collateral features are essential for evaluating collateral from a prepayment viewpoint--namely issuer or guarantor gross weighted average coupon (WAC), and weighted average loan age (WALA) or weighted average maturity (WAM). The issuer or the guarantor is vital since the detail is known about the borrowers within the different programs (Kolev, 2004). In the CMO cash flows, one or more mortgages pass through or pools of the mortgages are reallocated to a multiple classes with different priority claims. According to Fabozzi (2001), the CMO creation process is dynamic and sufficiently self-sustaining (with cash flows from collateral managers) to meet the cash flow requirements of CMO classes (Fabozzi, 2001). Major approaches to CMO evaluation. Johnston et al. (2008) illustrated that the CMO is exposed to interest rate risk and prepayment risk—a main concern of establishing an appropriate model for evaluating a CMO. Prepayment risk has a negative effect on the lender’s management of interest rate risk. Banks often target specific durations on debt instruments, with the intent of matching the interest rate and the risk of exposing their assets and liabilities (The Bond Market Association, 2003). The matching is endangered if prepayment risk changes the duration on some of the lender’s callable assets (Francois, 2003). Interest rates have the prime effect on prepayment rates. If interest rates go up, then prepayments will fall, and lifetimes of the majority tranches will grow longer. Growing interest rates will help to enlarge the life of the tranche past what was anticipated. If the interest rates plunge, the prepayments will increase as the homeowners refinance to acquire a lower interest rate, thereby cutting the life of the tranche. Therefore, the financier earns less return than anticipated. McConnell & Singh (1993) developed a model intended to evaluate a CMO. The model is based on two factors of term structure of interest rates and implants an empirically estimated mortgage prepayment function. The model is used to analyze various CMO tranches. McConnell & Singh (1993) too believed prepayment risk and interest rate risk are the major concern that affects a CMO and its valuation methodologies. The illustration gives general knowledge about the sensitivity of various tranches that varies with CMO structures, rate of interest, types of underlying collateral, and mortgage prepayments (McConnell & Singh, 1993). Usually, the pricing and the risk management of complicated financial instruments use Monte Carlo simulations. However, recently quasi-Monte Carlo means have came into existence, which are much more deterministic ways as they are based on the low discrepancy series. Quasi-Monte Carlo methods are much more superior to Monte Carlo pricing of derivatives in conditions of both speeds along with accuracy. McConnell & Singh (1993) further explained broadly about comparing deterministic simulation that uses low discrepancy series with the Monte Carlo method for computing the value at risk (Papageorgious & Paskov, 1998). Papageorgios & Paskov, (1998) further explained the problems that lie in valuation of a CMO in the current complex scenario of evaluating a financial derivative. The requirement for the standard fixed income valuation tools often affects the evaluation of financial derivatives. McConnell & Singh (1993) suggested that some models are primarily based on the management science: probabilistic modeling, regression analysis, Monte Carlo simulation, and linear and nonlinear programming and integer. Following these models, a firm could easily value and trade the complex MBS’s--quickly and more accurately. Dokko (2007) explained the major drawback of pro rata allotment mechanism. The traditional mortgages pass through payment of share of interest and principal each month on a pro rata basis to its share holders. The security represents ownership of a small interest in a number of mortgages. The CMO structure completely changes the pro rata distribution procedure and replaces a sequential retirement bonds. Following this mechanism, cash flows that are associated with the volatile prepayments on the underlying mortgages cannot be relied upon (McConnell & Singh, 1993); the unreliability of cash flow volatile prepayments is a major hindrance for valuing a CMO correctly (Jaffee & Rosen, n.d.). All though many CMO issues flat or yield curves are available in the market, a CMO needs a positively yield sloped curve. The rise of yield on mortgage backed securities (MBS’s) and spreads between regular MBS’s and treasuries broadened because the thrifts liquidated MBS’s from their portfolios. The spread’s stability is due to the arbitrage opportunities (Cheyette, 1994). SIFMA commented on minimum investments, transaction costs, and liquidity of CMOs, which are related to the cash flow projection and their value by evaluating a CMO (Bond Class, 2006). Nadler (1992) explained the minimum amount to be invested for a CMO depends on the format of the offering. However, most of the tranches that are sold to the single investors should have an investment of not less than $1000. The CMO investments are also proposed as mutual funds. The CMOs are not as much liquid as other debt instruments especially the treasury security which is much more liquid. Compared the CMOs, the treasury security dealings have a wider and deeper secondary market, accounting for the latter being comparatively liquid. The yields thus obtained from the treasury securities are removed from state and local income tax, but the CMO is taxable (McLeish, 2005). Higher mortgage rates curtailed the refinancing activities and resulted in the lower MBS’s collateral issuance by paying off an existing loan with the proceeds from a new loan. The new loan was usually the same size and used the same property as collateral. With the lower prepayment, volatility, and mortgage securities, investors choose to hold the pass through instead of the CMOs. The three collateral properties that are necessary for evaluating collateral from a prepayment view are issuer, WALA, WAC, and WAM (Fabozzi, 2001). Literature Review The swift growth of CMOs with low interest rates has amplified the volume of associated principal, as well as the income payment dispensation handled by The Depository Trust & Clearing Corporation’s (DTCC) depository. The inconsistency in the procedures for handling such payments, collectively with the tremendously tight time frames for processing them, has worsened existing problems. The elevated volume of late notifications on pay downs held through partial calls and the consequential post-payment adjustments have adversely affected the depository and the industry. Background and recent trends. The CMO is a multiclass bond identified as a pool of mortgage pass-through securities or mortgage loans (Kim, 2004). The issuer of the pass-through securities usually accumulates the monthly payments from the house owners whose loans are managed in a certain pool; the issuer passes through cash flow to investors in the monthly payments that comprise both interest and repayment of principal. Once the payments due on the underlying mortgage loans are gathered by means of the paying agent, the CMO issuer disburses a coupon rate of interest to the bondholders together with all scheduled and unscheduled principal payments as produced by the collateral, since the loans are repaid or prepaid (Holmer, 1997). Practices and key issues in CMO processing. The key players in the CMO market are servicers, paying agents, DTCC’s depository, as well as brokers and dealers. Each plays a key role in the entire process. The role of the servicers is to collect and pool principal, interest, and due payments and pass the proceeds as well as the comprehensive payment information to the paying agents (Chaudhary, 2006). In addition, servicers also carry out follow-up of loan payments and analyze different loans. The paying agents, performing on behalf of issuers, pass the comprehensive payment information to the bondholders. On payment date, they allocate interest and principal to the same bondholders (Depository Trust & Clearing Corporation, 2003). The sub-prime crisis--the sudden melt down or liquidation of the global banking system along with the credit markets--became a threat not only to the value of assets and financial markets, but to the worldwide national economy as a whole. The reason identified was the collapse of the U.S. housing bubble that acted as an impulse to the fast increase of failure in payment of mortgage debts, especially in the range of sub-prime mortgages issued in the impassioned markets. The security mortgages held in worldwide portfolios have led to the difficulty in payments and thus created an overall financial market explosion (Dymski, 2007). The United States became a country with thousands of households who have lost their homes in the sudden collapse of mortgage markets. Dymski (2007) compared the economy with the submarine in the movie Das Boot. In the movie, the submarine submerged deep into the water and sank below where there was little oxygen. Also, the valves were exploding one after another under pressure. According to some analysts, the reason for such scenario was greed and overreach created by the global financial firms. The two main aspects as observed for the abnormal U.S. banking behavior are the strategic transformation of banking in the beginning of the neoliberal era and the racial exclusion in the U.S. markets of housing credits. Hyman Minsky used the balance sheet approach to understand strategic transformation of banking in the neoliberal era. Due to macro and micro harassments, the banks now have developed strategies to revenue generation with the beginning of the neoliberal age. The change in their strategies not only helped to change the structural relationship between procedures of loan making and risk taking, but helped banks manage and absorb risks. But after implementing the strategies, the banks stopped to play some of their key roles in the economy as a whole. Banks tend to move toward speculative and overly-risk lending when they produce default risks and liquidity risks through loan making, and cover for those risks on their balance sheets. The banks must consider both the default risk that might deteriorate marginal loans and the liquidity risks of funding their complete asset portfolio that are escalating. The reason for conversion of the landscape of racial and social exclusion in U.S. credit markets was the strategic re-orientation of banks together with reduced regulatory failure to notice, growth in financial technology, and the U.S.’s exclusive geo-economic conditions. The households who earlier refused to take mortgage credits now were honored high-cost, high-risk loans. The banks failed to control credit flows to minorities and inner-city residents and thus enabled high-risk, high-cost loans. In brief, the sub-prime crisis is an outcome of the wicked communication between America’s inheritance of racial discrimination, social dissimilarity, and hyper-competitive world straddled the financial sector. Dymski (2009a) observed that because of the interdependent of the core area of banking functions, banks maintain the provision of liquidity and creation of credit functions. During uncertainties, holding assets that can be easily converted into money is more desirable than holding assets that are non-monetary and may be unfeasible to sell willingly. Non-bank economic units can stay alive more efficiently during such periods provided banks assist them with fresh infusion of credit at affordable rates. To provide such credit, banks must give up their own liquidity (Dymski, 2009a). One of the exceptional characteristic of banking systems is that some of the institutional mechanisms that improve banks’ openness to the economic enlargement impulses in an expansion and build up level of total liquidity as well as default risk. Some analysts opine that if some part of a bank’s population is more hostile in loan-making than another part, then the more conservative banks along with the system as a whole will be dragged toward a more violent credit posture with elevated levels of default and liquidity risk. Transformation of U.S. banking and mortgage markets. In the 1960s and 1970s, some banks developed a tactic of liability management, where they supported lending more than the deposit bases that would have been allowed by borrowing methodically in the interbank (Federal Funds) market and accounting into other short-term borrowing sources. Savings and loan companies, as well as savings banks (or thrifts), offered housing credits initially, which attracted longer-term consumer savings. In the 1980s, the U.S. banks functioned in the ancient geographic area along with product-line prohibitions. Functioning in the ancient geographic area restricted their capability to react flexibly to credit demand. The smaller banks did not face any difficulties (Blake et al., 2006). Securitization and the Mortgage Market The housing mortgage market has always been volatile; however, in 1980 a drastic change in the housing finance market occurred; the housing market collapsed. The U.S. housing finance system was already in the center of an alteration from an intermediary-based to a securities-market-based system. Earlier lenders used to hold mortgages to maturity, and the same were exposed to default and liquidity risks. But, with the introduction of the new system, lenders started to sell mortgages. The commercial banks paid much attention to increasing their share of consumer-banking markets with the help of provided mechanisms for putting into operation securitization. For a flourishing securities-based system to occur, the housing finance system needed to modify risky mortgage assets. Two federally chartered agencies are FNMA and FHLMC. For many years, they have provided the secondary market with qualifying mortgages. The GNMA (also known as Ginnie Mae) also offers a secondary market for Veterans Administration, Federal Housing Administration (FHA), and the Farmer’s Home Association mortgages. These agencies not only underwrite mortgage credits, but also hold a major share of U.S. mortgage debt. From the mid-1980s to the mid-1990s, most mortgages were conventional loans--loans underwritten by these agencies and either taken in custody of agency portfolios or disposed of. The remodeling of the U.S. housing finance did not call for the invention of new institutions; rather, the remodeling required a development in the scope of sharing in the secondary mortgage-debt market (Cowan, 2003). In 2012, the limit of FNMA is $ 417,000, resulting in more mortgages moving into jumbo loan category. The remodeling of U.S. housing finance did not call for creating innovative institutions; as an alternative, the remodeling required an extension in the scope of contribution in the secondary mortgage-debt market. The separation of risk bearing from loan-absorption was so absolute that thrifts were able to continue a big share of originations, despite their continued loss of their deposit share. The Evolution of Financial Exploitation Since 1930, the FHA has inculcated some guidelines for houses in the neighborhoods with the minority populations from participating and thus leading to reduction in the housing values. In 1960, due to passed legislation, countless organizations put pressure on the value of houses. Two sections of the legislation of the 1968 Fair Housing Act and 1974 Equal Credit Opportunity Act led to the understanding of principles of anti-discrimination of the civil rights law in the housing and credit markets respectively. Both The Home Mortgage Disclosure Act of 1975 and the Community Reinvestment Act of 1977 provided a mechanism for keeping an eye on bank loan-making, and prohibited redlining--the implicit or explicit rejection of lenders for making mortgage credit available to neighborhoods at large (Dymski, 2009c). The subprime loan practices greatly affected people. Most of the low-income and minority borrowers jumped at getting loans at higher rates of interest with very adverse terms from housing-related and payday lenders (Dymski, 2005). From the Margins of the City to the Core of Global Finance In the late 1990s, an asset-boom mania began among homeowners and potential homeowners. Those who possessed homes desired bigger ones (Dymski, 2009b). The acquisitions and the varied practices in the segment of consumer finance resulted in increased interpenetration among the large banking bodies and other finance companies, along with the subprime lenders. The structures of the subprime mortgage loans and the payday loans were almost same. The similarity helped to expose subprime lenders to the broader subprime markets. Once the securitization markets reached the level of accepting asset heterogeneity that was not supported by iron-clad underwriting, the door was open for the additional development of mortgages and securities. The financial markets were no new arrivals to non-homogeneous risks in securitized mortgage debt. Since the 1970s, real-estate investment trusts had been promoted and disposed off to investors. There was already an understanding of crisis; many metropolises, housing real estate started to take off in value in the late 1990s. A review of earlier literature revealed the CMO, the most demanded and lucrative debt instrument, is becoming more complex each day due to various reasons like difference in prepayment speeds, interest rate risk, and the structure of the CMO itself. Different scholars have suggested suitable methods, proposing a standard for its evaluation. The most appreciated method is the Quasi Monte Carlo method, a method based on the low discrepancy sequences. Collateralized mortgage obligations, one debt instrument, are collateralized by mortgage pass through certificates or individual mortgage loans. Thus, the CMO has a feature of both the mortgage pass through securities and a corporate bond. The main difference between a CMO and a mortgage pass through security is the mechanism by which interest and principal are paid to the holders of the securities. The traditional pass through is paid in the pro rata. The structure of a CMO fundamentally changes the pro rata distribution mechanism and substitutes a sequential retirement bond (Jaffee & Rosen, n.d.). Balanced Discussions and Alternative Viewpoints Discussions on various aspects of CMO valuations establish certain variations in viewpoints. As observed, CMOs being exposed to the interest rate risk and prepayment risk, has given rise to the requirement for an appropriate valuation methodology. Depending on basic characteristics, different analysts have cited different comparative and distinguished views. Since the pro rata distribution mechanism is a major drawback, some opine that adopting the Quasi-Monte Carlo method is better. While others opine that since the outcome of the sensitivity of various tranches differs with CMO structures, rate of interest and types of collateral, using two factor models is better. Again, the higher mortgage rates may cut down the refinancing activity, which may again result into lower MBS collateral issuance. Lower prepayment volatility results into preferring the holding pass through. Some hold the opinion that probability modeling, regression analysis, and Monte Carlo simulation non-linear programmings are some of the other suitable methods of valuing a CMO. The above opinion illustrates the scarcity of consistency in the process of handling the payments, along with the definite time frames of processing the CMO payments have worsen the existing problem. The maker of the pass through securities generally accumulates monthly payments from the property owners whose loans are offered in a pool and that pass through the cash flows to the real investors in the way of monthly payments. The monthly payments consist of both interest and repayment of principal. When the banks produce default risks and liquidity risks by means of loan-making, and soak up those risks on their balance sheets, there are built-in breaks that make the banks to move toward speculative and abnormal risk lending. In the later stages of a development, the default risks are produced (Freddie, 2003). Identified Research Gaps Researchers and authors of journal articles and other documents have discussed different aspects of a CMO, sharing their observations, assumptions, and perceptions. However, there are no strong determinations suggesting an appropriate model that is suitable for a CMO valuation. The existing literature does not indicate the preferred method for CMO valuation among different scholars and researchers. Availability of data about CMO valuation is the main concern of the study. As cited by different scholars, the prepayment volatility due to differences in maturity dates, variations in rate of interest, and over complex CMO structures, are the main reasons that are responsible for the complexities in valuation of a CMO. The CMOs were invented with the intention of broadening the appeal of mortgage-backed securities by creating an extensive range of duration and prepayment profiles out of fundamental mortgage pass through cash flows. The CMOs were created with the intention of reallocating cash flows that are produced from the underlying collateral, which are based on the predefined rules. Investors usually obtained the exposure to the mortgage market through which the investors divide the principal and interest on the payments of underlying loans on the pro-rata basis. Using pass-through securities is not appropriate for a number of institutional investors since an alteration in prepayments may result in a mismatch between their funding abilities (Hardmoneylist, 2010). Banks are mainly worried about the extension risk through which a mortgage passes. The CMO designs do not remove the call or extension risk of the base collateral. Despite having some good characteristics, certain challenges exist in projecting CMO cash flows. The key concern is the underlying driver of the cash flows of mortgage payments and the prepayment functions. The main problem is due to the tremendous complication of many CMO structures; the CMO structures vary among various CMOs, and the lack of readily available data on the CMO structures (Papageorgiou & Traub, 2010). The preferred sophistication and accuracy of a model used for a cash flow projection does not provide a clear model for valuation of the CMOs. The proposed research study is focused on developing an accurate model for valuatio Read More