Lau, Ka Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 46-48). / Abstract also in Chinese. / Chapter 1 --- Introduction to Global Credit Risk Management Standard --- p.1 / Chapter 1.1 --- Background --- p.2 / Chapter 1.2 --- Basel Accords --- p.2 / Chapter 1.3 --- Risk Bucketing --- p.7 / Chapter 2 --- Current Practices of Risk Bucketing and PD Estimation --- p.10 / Chapter 2.1 --- Credit Scoring --- p.10 / Chapter 2.2 --- Risk Bucketing after Credit Scoring --- p.12 / Chapter 2.3 --- Related Literature Review --- p.14 / Chapter 2.4 --- Objective --- p.16 / Chapter 3 --- Bayesian Model for risk bucketing --- p.17 / Chapter 3.1 --- The Model --- p.17 / Chapter 3.2 --- Posterior Distribution --- p.19 / Chapter 3.3 --- Gibbs Sampler for the Posterior Distribution --- p.22 / Chapter 3.3.1 --- General Gibbs Sampler Theory --- p.22 / Chapter 3.3.2 --- The Gibbs Sampler for the Proposed Model --- p.23 / Chapter 3.4 --- Monitoring Convergence of the Gibbs Sampler --- p.26 / Chapter 3.5 --- "Estimation, Bucketing and Prediction" --- p.28 / Chapter 3.5.1 --- Estimation --- p.28 / Chapter 3.5.2 --- Bucketing --- p.28 / Chapter 3.5.3 --- Prediction --- p.29 / Appendix --- p.29 / Chapter 4 --- Simulation Studies and Real Data Analysis --- p.32 / Chapter 4.1 --- Simulation Studies --- p.32 / Chapter 4.1.1 --- Details of Simulation --- p.32 / Chapter 4.1.2 --- Simulation Procedures --- p.34 / Chapter 4.1.3 --- Predictive Performance --- p.35 / Chapter 4.1.4 --- Summary of Simulation Results --- p.36 / Chapter 4.2 --- Real Data Analysis --- p.37 / Chapter 5 --- Conclusion and Discussion --- p.44 / Bibliography --- p.46

In this dissertation, I focus my research on some of the economically significant and current open problems in international finance, specifically the relationship between Credit Default Swaps (CDS) on sovereign debt, the importance of fundamental dyadic distances on the initiation and completion of cross-border mergers and acquisitions, and the impact of domestic and transnational terrorism on cross-border mergers and acquisitions. In the first essay, we study the relationship between sovereign debt ratings and the information contained in CDS spreads regarding the credit risk of the reference entity. Using data for 54 countries over a twelve-year period, we find that the variation in average sovereign ratings in a given year can be explained by average CDS spreads over the previous three years. In a horse race between CDS spreads and sovereign ratings, we find that CDS spread changes can predict sovereign events while rating changes cannot. In the second essay, we study how dyadic distance influences the initiation, completion, and duration of cross-border mergers and acquisitions. Using a sample of 173,616 cross-border deals announced between 1970 and 2016, we find evidence that cross-country cultural, institutional, geographical, religious, and language differences, all play a deciding role in the initiation of mergers and acquisitions. The completion of acquisitions is independent of cultural factors, but largely depends on differences in economy size, language, religion, and bureaucracy of the acquiring and target countries. Finally, the duration of deals is influenced by idiosyncratic factors only. In the third essay, we study whether incidents of domestic and transnational terrorism impact the propensity of firms to acquire cross-border firms. We adopt a theoretical model to show that high levels of terrorism in the target countries are associated with lower cross-border acquisition flows. Empirically, we exploit the exogenous variation induced by differences in genetic diversity, ethnic fractionalization, and religious fractionalization between acquirer and target countries. Our results show that an target from a country with lower terrorist incidents than the acquirer country are associated with more cross-border mergers and acquisitions.

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. / 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. / 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.

Despite the recognized importance of the bond rating industry, little academic work has been done to investigate the determinants of the standards these firms employ to assign credit ratings to individual firms. There is an ongoing debate in the literature arguing whether the decline in the percentage of highly rated firms is because rating standards have become more stringent over time or whether the credit quality of firms in the economy has declined. We investigate this question in this dissertation. Our first contribution is to address several empirical problems in prior literature. This study uses a combination of structural models of default and econometric model of ratings to study the determinants of rating standards and, by doing so, overcome the earlier methodological shortcomings. Our second contribution is to test new theory which hypothesizes that the standards of a rating agency are conditional upon the distribution of default risk in the economy at the time. The results are robust no matter which structural models of default we employ. The evidence suggests the standards are relative to the default risk distribution and there has been a secular increase in the stringency in the assignment of ratings over time. A third way we extend the literature is by examining the accuracy of the assignment of ratings. Theoretical models suggest rating agencies have incentives to purposefully add noise to the assignment of ratings. We conduct an empirical analysis of the classification errors using receiver operating characteristic analysis. The results suggest that error rates have decreased at the extreme ends of the rating spectrum (AAA vs. AA and below; B and below vs. BB and above) over time while it has increased in the middle rating categories. This error rate is directly related to the distribution of default risk across firms at any point in time. These findings not only strengthen our result that standards are relative and time varying, but also suggest there is more noise in the assignment of ratings at exactly the time when there is more uncertainty regarding the credit risk of firms in the economy – i.e., during a credit crisis.

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In order to reduce default risk, financial institutions have been investigating into credit ratings of companies, which they want to give credit to. This research tries to give a method for financial institutions to differentiate between default and normal company with financial ratios, which is already announced in their seasonal financial reports. The samples are abstracted from security markets, and restricted to building companies. With Discriminant analysis and Logistic regression models, financial institutions can estimate what company may become into default situation and others stay in good condition. According to this research, financial ratios that can be used to discriminate between default and normal companies are: net worth ratio and short-turn borrowing/liquid asset and asset turnover and gross profit margin. It can also be described with asset turnover and gross profit margin if default risk is been estimated.

Taiwanese enterprises in Taiwan, China, and Hong Kong operate under division of labor through perpendicular and level integration and strategic alliances. As Mainland China has becoming a mature economic entity, the strategy has changed from the previous ¡§Soliciting Business and Introducing Investment¡¨ to ¡§Soliciting Business and Selecting Investment¡¨. In 2007, China announced the foreign enterprises investment and industry directives, and revoked tax incentives. In 2008, due to the levy of corporate income tax and the execution of the Labor Contract Law, the operating cost for businesses has increased, and the competitiveness of Chinese labors has diminished. Thus, Taiwanese enterprises have to find cheap resources elsewhere, and Vietnam is then recognized as a popular major investment location by Taiwanese enterprises. According to the Financial Supervisory Commission, Executive Yuan, the pre-tax profit for the Taiwan domestic banks in 2007 was NT $38.9 billion. Among which, overseas bank branches (including Offshore Banking Unit) had NT $31.1 billion, accounting for 79.9% of the total profit. It shows that overseas bank branches are a major source of profit for domestic banks, and the profit is growing rapidly year after year. Hence, domestic banks have actively established overseas offices and branches for business development, and followed the steps of Taiwanese enterprises to provide loans services and create higher profits for the banks. This study adopted a qualitative research method and designed an in-depth interview with 30 enterprise owners and senior financial supervisors. Questionnaire survey was conducted to analyze bank loans strategy, competitive strategy SWOT analysis, and AHP analysis. Research results showed that the most important factor of an ideal Taiwan-based bank to Taiwanese enterprises is the interest of loan. Besides being a reliable long-term partner with Taiwanese enterprises, banks should pay more attention to their enterprise credit ratings and strengthen risk management. To help banks achieving the win-win situation by optimizing the operating performance and maximizing the profits for banks, this study proposed several suggestions concerning loans strategy for Taiwan-based bank.

In this dissertation, I explore the ability of financial institutions to impact firm behavior. The first essay examines whether relationships between venture capital owners (VCs) and investment banking underwriters affect a firm’s ability to issue equity. I find that past interactions between VC owners and underwriters in the form of previously underwritten initial public offerings (IPOs) significantly increase the likelihood that an IPO firm chooses a specific underwriter. In terms of how VCs and underwriters associate with each other, older VCs partner with more reputable underwriters. Despite paying higher fees, issuing firms benefit from stronger VC-Underwriter relationships through upward offer price revisions and higher valuations. VC-Underwriter relationships also predict underwriter choice in subsequent equity offerings. This essay provides empirical evidence that suggests VCs use their relationships with investment banks to enable their portfolio firms access to high quality underwriters and better underwriting services. The second essay investigates whether credit rating concerns affect capital investment decisions. Using ex-ante measures of proximity to a rating change, I find that firms that are near a credit rating downgrade spend significantly less on capital expenditures relative to those not near a rating change. The response of firms to credit rating upgrades is not symmetric: firms do not seem to adopt significantly different investment policies when near an upgrade. This effect of lowering investment when near a credit downgrade is stronger for firms that face financial constraints, experience greater adverse selection and are more active in debt markets. Related to reductions in investment, firms near rating changes also spend less on research and development expenses and pay lower dividends. My findings are consistent with firms conserving financial resources to prevent adverse credit rating changes that could increase their cost of capital. / text

This paper introduces a model framework for dynamic credit rating processes. Our framework aggregates ordinal rating information stemming from a variety of rating sources. The dynamic of the consensus rating captures systematic as well as idiosyncratic changes. In addition, our framework allows to validate the different rating sources by analyzing the mean/variance structure of the rating errors. In an empirical study for the iTraxx Europe companies rated by the big three external rating agencies we use Bayesian techniques to estimate the consensus ratings for these companies. The advantages are illustrated by comparing our dynamic rating model to a benchmark model. (author´s abstract) / Series: Research Report Series / Department of Statistics and Mathematics

This paper looks at whether firms’ credit ratings are negatively affected by litigation risk after controlling for known factors that affect credit ratings. The conventional wisdom is that litigation risk and credit ratings have an inverse relationship. However, my hypothesis is that the inverse relationship will not be stable if the model of credit ratings has taken other factors into account. The methodology first constructs a model of litigation risk, and then regress the credit ratings on the measurement of litigation risk. Previous empirical research on litigation risk measurement uses industry proxies as indicators for litigation risk. In this paper, I include firm characteristics and the Beneish M-score (a determinant for earnings manipulation) in addition to the industry proxy to construct an alternative model measuring litigation risk. I find that supplementing the Francis, Philbrick and Schipper (1994a, b; hereafter FPS) industry proxy with measures of firm characteristics improves predictive ability. In the model of credit ratings, I find that the change of litigation risk has a negative correlation with the credit ratings. However, the negative coefficient on the change of litigation risk changes to a positive one after controlling for other variables such as firm size, return on asset, and interest coverage ratio. This finding provides support for the hypothesis that the negative correlation between the credit ratings and litigation risk is not stable. This suggests that credit ratings may not incorporate litigation risk specifically although litigation can lead to firms’ financial damage and reputation crisis. However, the negative coefficient on the change of litigation risk remains unchanged when I control for the year fixed effects. I also find a negative correlation between the year 2007 and credit ratings due to financial crisis. The results are not conclusive given the likely simultaneous determination of litigation risk and credit ratings.