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Development and structuring of commercial mortgage-backed securities in Australia

Chikolwa, Bwembya (2008) Development and structuring of commercial mortgage-backed securities in Australia. PhD thesis, Curtin University of Technology.

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Abstract

According to the Reserve Bank of Australia (2006) the increased supply of Commercial Mortgage-Backed Securities (CMBS), with a range of subordination, has broadened the investor base in real estate debt markets and reduced the commercial property sector’s dependence on bank financing The CMBS market has been one of the most dynamic and fastest-growing sectors in the capital markets, for a market which was virtually nonexistent prior to 1990. The global CMBS market issuance which stood at AU$5.1 billion (US$4 billion) in 1990 had grown to AU$380 billion (US$299 billion) by the end of 2006. In Australia, a total of over 60 CMBSs with nearly 180 tranches totalling over AU$17.4 billion had been issued to December 2006 from when they were first introduced in 1999. To date few studies have been done on Australian CMBSs outside the credit rating agency circles. These studies are predominantly practitioner focused (Jones Lang LaSalle 2001; Richardson 2003; Roche 2000, 2002). O’Sullivan (1998) and Simonovski (2003) are the only academic studies on CMBSs. As such, this thesis examines issues relating to the development of Australian CMBSs and quantitatively and qualitatively analyses the structuring of Australian CMBSs. In assessing the growth of the Australian CMBS market, an interpretive historical approach (Baumgarter & Hensley 2005) is adopted to provide a cogent review and explanation of features of international and Australian CMBSs. This helps to understand the changing nature of the market and provides better understanding of the present and suggests possible future directions. The Australian CMBS market is matured in comparison with the larger US and EU CMBS markets as seen by the diversity of asset classes backing the issues and transaction types, tightening spreads, and record issuance volumes. High property market transparency (Jones Lang LaSalle 2006b) and predominance of Listed Property Trusts (LPT) as CMBS issuers (Standard & Poor’s 2005b), who legally have to report their activities and underlying collateral performance to regulatory regimes such as Australian Stock Exchange (ASX)/Australian Securities and Investment Commission (ASIC) and their equity partners, have contributed to the success of the Australian CMBS market. Furthermore, the positive commercial real estate market outlook should support future CMBS issuance, with LPTs continuing their dominance as issuers. In investigating property risk assessment in Australian CMBSs, all the CMBSs issued over a six year period of 2000 to 2005 were obtained from Standard and Poor’s presale reports as found in their Ratings Direct database to identify and review how property risk factors were addressed in all issues and within specific property asset classes following the delineation of property risk by Adair and Hutchinson (2005). Adequate assessment of property risk and its reporting is critical to the success of CMBS issues. The proposed framework shows that assessing and reporting property risk in Australian CMBSs, which are primarily backed by direct property assets, under the headings of investment quality risk, covenant strength risk, and depreciation and obsolescence risk can easily be done. The proposed framework should prove useful to rating agencies, bond issuers and institutional investors. Rating agencies can adopt a more systematic and consistent approach towards reporting of assessed property risk in CMBSs. Issuers and institutional investors can examine the perceived consistency and appropriateness of the rating assigned to a CMBS issue by providing inferences concerning property risk assessment. High property market transparency (Jones Lang LaSalle 2006b) and predominance of Listed Property Trusts (LPT) as CMBS issuers (Standard & Poor’s 2005b), who legally have to report their activities and underlying collateral performance to regulatory regimes such as Australian Stock Exchange (ASX)/Australian Securities and Investment Commission (ASIC) and their equity partners, have contributed to the success of the Australian CMBS market. Furthermore, the positive commercial real estate market outlook should support future CMBS issuance, with LPTs continuing their dominance as issuers. In investigating property risk assessment in Australian CMBSs, all the CMBSs issued over a six year period of 2000 to 2005 were obtained from Standard and Poor’s presale reports as found in their Ratings Direct database to identify and review how property risk factors were addressed in all issues and within specific property asset classes following the delineation of property risk by Adair and Hutchinson (2005). Adequate assessment of property risk and its reporting is critical to the success of CMBS issues. The proposed framework shows that assessing and reporting property risk in Australian CMBSs, which are primarily backed by direct property assets, under the headings of investment quality risk, covenant strength risk, and depreciation and obsolescence risk can easily be done. The proposed framework should prove useful to rating agencies, bond issuers and institutional investors. Rating agencies can adopt a more systematic and consistent approach towards reporting of assessed property risk in CMBSs. Issuers and institutional investors can examine the perceived consistency and appropriateness of the rating assigned to a CMBS issue by providing inferences concerning property risk assessment. The ultimate goal of structuring CMBS transactions is to obtain a high credit rating as this has an impact on the yield obtainable and the success of the issue. The credit rating process involves highly subjective assessment of both qualitative and quantitative factors of a particular company as well as pertinent industry level or market level variables (Huang et al. 2004), with the final rating assigned by a credit committee via voting (Kwon et al. 1997). As such, credit rating agencies state that researchers cannot replicate their ratings quantitatively since their ratings reflect each agency’s opinion about an issue’s potential default risk and relies heavily on a committee’s analysis of the issuer’s ability and willingness to repay its debt. However, researchers have replicated bond ratings on the premise that financial ratios contain a large amount of information about a company’s credit risk. In this study, quantitative analysis of determinants of CMBS credit ratings issued by Standard and Poor’s from 2000 – 2006 using ANNs and OR and qualitative analysis of factors considered necessary to obtain a high credit rating and pricing issues necessary for the success of an issue through mail surveys of arrangers and issuers are undertaken. Of the quantitative variables propagated by credit rating agencies as being important to CMBS rating, only loan-to-value ratio (LTV) is found to be statistically significant, with the other variables being statistically insignificant using OR. This leads to the conclusion that statistical approaches used in corporate bond rating studies have limited replication capabilities in CMBS rating and that the endogeneity arguments raise significant questions about LTV and debt service coverage ratio (DSCR) as convenient, short-cut measures of CMBS default risk. The ultimate goal of structuring CMBS transactions is to obtain a high credit rating as this has an impact on the yield obtainable and the success of the issue. The credit rating process involves highly subjective assessment of both qualitative and quantitative factors of a particular company as well as pertinent industry level or market level variables (Huang et al. 2004), with the final rating assigned by a credit committee via voting (Kwon et al. 1997). As such, credit rating agencies state that researchers cannot replicate their ratings quantitatively since their ratings reflect each agency’s opinion about an issue’s potential default risk and relies heavily on a committee’s analysis of the issuer’s ability and willingness to repay its debt. However, researchers have replicated bond ratings on the premise that financial ratios contain a large amount of information about a company’s credit risk. In this study, quantitative analysis of determinants of CMBS credit ratings issued by Standard and Poor’s from 2000 – 2006 using ANNs and OR and qualitative analysis of factors considered necessary to obtain a high credit rating and pricing issues necessary for the success of an issue through mail surveys of arrangers and issuers are undertaken. Of the quantitative variables propagated by credit rating agencies as being important to CMBS rating, only loan-to-value ratio (LTV) is found to be statistically significant, with the other variables being statistically insignificant using OR. This leads to the conclusion that statistical approaches used in corporate bond rating studies have limited replication capabilities in CMBS rating and that the endogeneity arguments raise significant questions about LTV and debt service coverage ratio (DSCR) as convenient, short-cut measures of CMBS default risk. However, ANNs do offer promising predictive results and can be used to facilitate implementation of survey-based CMBS rating systems. This should contribute to making the CMBS rating methodology become more explicit which is advantageous in that both CMBS investors and issuers are provided with greater information and faith in the investment. ANN results show that 62.0% of CMBS rating is attributable to LTV (38.2%) and DSCR (23.6%); supporting earlier studies which have listed the two as being the most important variables in CMBS rating. The other variables’ contributions are: CMBS issue size (10.1%), CMBS tenure (6.7%), geographical diversity (13.5%) and property diversity (7.9%) respectively. The methodology used to obtain these results is validated when applied to predict LPT bond ratings. Both OR and ANN produce provide robust alternatives to rating LPT bonds, with no significant differences in results between the full models of the two methods. Qualitative analysis of surveys on arrangers and issuers provides insights into structuring issues they consider necessary to obtain a high credit rating and pricing issues necessary for the success of an issue. Rating of issues was found to be the main reason why investors invest in CMBSs and provision of funds at attractive rates as the main motivation behind CMBS issuance. Furthermore, asset quality was found to be the most important factor necessary to obtain a high credit rating supporting the view by Henderson and ING Barings (1997) that assets backing securitisation are its fundamental credit strength. However, ANNs do offer promising predictive results and can be used to facilitate implementation of survey-based CMBS rating systems. This should contribute to making the CMBS rating methodology become more explicit which is advantageous in that both CMBS investors and issuers are provided with greater information and faith in the investment. ANN results show that 62.0% of CMBS rating is attributable to LTV (38.2%) and DSCR (23.6%); supporting earlier studies which have listed the two as being the most important variables in CMBS rating. The other variables’ contributions are: CMBS issue size (10.1%), CMBS tenure (6.7%), geographical diversity (13.5%) and property diversity (7.9%) respectively. The methodology used to obtain these results is validated when applied to predict LPT bond ratings. Both OR and ANN produce provide robust alternatives to rating LPT bonds, with no significant differences in results between the full models of the two methods. Qualitative analysis of surveys on arrangers and issuers provides insights into structuring issues they consider necessary to obtain a high credit rating and pricing issues necessary for the success of an issue. Rating of issues was found to be the main reason why investors invest in CMBSs and provision of funds at attractive rates as the main motivation behind CMBS issuance. Furthermore, asset quality was found to be the most important factor necessary to obtain a high credit rating supporting the view by Henderson and ING Barings (1997) that assets backing securitisation are its fundamental credit strength. In addition, analyses of the surveys reveal the following: • The choice of which debt funding option to use depends on market conditions. • Credit tranching, over-collateralisation and cross-collateralisation are the main forms of credit enhancement in use. • On average, the AAA note tranche needs to be above AU$100 million and have 60 - 85% subordination for the CMBS issue to be economically viable. • Structuring costs range between 0.1% – 1% of issue size and structuring duration ranges from 4 – 9 months. • Preferred refinancing options are further capital market issues and bank debt. • Pricing CMBSs is greatly influenced by factors in the broader capital markets. For instance, the market had literary shut down as a result of the “credit crunch” caused by the meltdown in the US sub-prime mortgage market. These findings can be useful to issuers as a guide on the cost of going to the bond market to raise capital, which can be useful in comparing with other sources of funds. The findings of this thesis address crucial research priorities of the property industry as CMBSs are seen as a major commercial real estate debt instrument. By looking at how property risk can be assessed and reported in a more systematic way, and investigating quantitative and qualitative factors considered in structuring CMBSs, investor confidence can be increased through the increased body of knowledge. Several published refereed journal articles in Appendix C further validate the stature and significance of this thesis. It is evident that the property research in this thesis can lead aid in the revitalisation of the Australian CMBS market after the “shut down” caused by the melt-down in the US sub-prime mortgage market and can also be used to set up property-backed CMBSs in emerging countries where the CMBS market is immature or non-existent. In addition, analyses of the surveys reveal the following: • The choice of which debt funding option to use depends on market conditions. • Credit tranching, over-collateralisation and cross-collateralisation are the main forms of credit enhancement in use. • On average, the AAA note tranche needs to be above AU$100 million and have 60 - 85% subordination for the CMBS issue to be economically viable. • Structuring costs range between 0.1% – 1% of issue size and structuring duration ranges from 4 – 9 months. • Preferred refinancing options are further capital market issues and bank debt. • Pricing CMBSs is greatly influenced by factors in the broader capital markets. For instance, the market had literary shut down as a result of the “credit crunch” caused by the meltdown in the US sub-prime mortgage market. These findings can be useful to issuers as a guide on the cost of going to the bond market to raise capital, which can be useful in comparing with other sources of funds. The findings of this thesis address crucial research priorities of the property industry as CMBSs are seen as a major commercial real estate debt instrument. By looking at how property risk can be assessed and reported in a more systematic way, and investigating quantitative and qualitative factors considered in structuring CMBSs, investor confidence can be increased through the increased body of knowledge. Several published refereed journal articles in Appendix C further validate the stature and significance of this thesis. It is evident that the property research in this thesis can lead aid in the revitalisation of the Australian CMBS market after the “shut down” caused by the melt-down in the US sub-prime mortgage market and can also be used to set up property-backed CMBSs in emerging countries where the CMBS market is immature or non-existent.

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ID Code: 19171
Item Type: Thesis (PhD)
Keywords: commercial mortgage-backed securities, artificial neural networks, credit ratings, ordinal regression
Subjects: Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > BANKING FINANCE AND INVESTMENT (150200) > Finance (150201)
Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > BANKING FINANCE AND INVESTMENT (150200) > Financial Econometrics (150202)
Australian and New Zealand Standard Research Classification > COMMERCE MANAGEMENT TOURISM AND SERVICES (150000) > COMMERCIAL SERVICES (150400) > Real Estate and Valuation Services (150403)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Urban Development
Institution: Curtin University of Technology
Deposited On: 26 Mar 2009 13:22
Last Modified: 09 Jun 2010 23:32

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