Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 99-104).

Thesis (M. Econ.)--University of Hong Kong, 2000. / Includes bibliographical references.

Thesis (M.Econ.)--University of Hong Kong, 2000. / Includes bibliographical references. Also available in print.

abstract: While credit rating agencies use both forward-looking and historical information in evaluating a firm's credit risk, the role of forward-looking information in their rating decisions is not well understood. In this study, I examine the association between management earnings guidance news and future credit rating changes. While upward earnings guidance is not informative for credit rating changes, downward earnings guidance is significantly and positively associated with both the likelihood and speed of rating downgrades. In cross-sectional analyses, I find that downward guidance is especially informative in two important circumstances: (i) when a firm's current credit rating is overly optimistic compared to a model predicted rating, and (ii) when the relevance or reliability of alternative information sources is lower. In addition, I find that downward guidance is associated with lower future cash flows, as well as a higher volatility of future cash flows. Overall, the results are consistent with credit rating agencies incorporating voluntary bad news disclosures into their decisions about whether and when to downgrade a firm. / Dissertation/Thesis / Doctoral Dissertation Accountancy 2015

This dissertation introduces a general framework modeling common rating processes in order to aggregate rating information stemming from a variety of raters or rating sources. Ratings play an increasingly important role in our life. They are used to evaluate a variety of objects and activities all over the world. Here we apply our model framework to two different ratings, the credit ratings and the bookmakers odds. Whereas credit ratings represent the evaluation of credit customers or firms by banks or external rating agencies, bookmakers odds are prospective ratings of the performance of the participating players or teams in a sports competition. Despite the fact that these ratings are used in different kind of areas, both rating systems have a very similar underlying rating process. In both rating processes each rater estimates an underlying numerical variable which represent a probability or is directly related to a probability. In the case of credit ratings this probability is the probability of default (PD) of a credit customer or a firm and in the case of bookmakers odds this probability is the probability of winning a specifc sports competition. The proposed model framework is then used to solve the aggregation problem of the two rating processes for different applications yielding different model specifcations. Finally, the model results are used to validate the different underlying rating systems as well as for forecasting. (author's abstract)

The thesis studies the factors which underpin the allocation of credit ratings by the two major credit rating agencies (CRAs) namely Moody’s and S&P. CRAs make regular headlines, and their rating’s judgements are closely followed and debated by the financial community. Indeed, criticism of these agencies emerged, both in this community and the popular press, following the 2007-2008 financial crisis. This thesis examines several aspects of the allocation of credit ratings by the major agencies, particularly in relation to (i) their revealed “loss function” preference structure, (ii) the determinants underpinning the allocation of credit ratings and (iii) the reasons determining the circumstances when the two agencies appear to differ in their opinions, and we witness a split credit rating allocation. The first essay empirically estimates the loss function preferences of two agencies by analyzing instances of split credit ratings assigned to corporate issuers. Our dataset utilises a time series of nineteen years (1991-2009) of historical credit ratings data from corporate issuers. The methodology consists of estimating rating judgment differences by deducting the rating implied probability of default from the estimated market implied probability of default. Then, utilising judgment differences, we adapt the GMM estimation following Elliott et al. (2005), to extract the loss function preferences of the two agencies. The estimated preferences show a higher degree of asymmetry in the case of Moody’s, and we find strong evidence of conservatism (relative to the market) in industry sectors other than financials and utilities. S&P exhibits loss function asymmetry in both the utility and financial sectors, whereas in other sectors we find strong evidence of symmetric preferences relative to those of the market. The second essay compares the impact of financial, governance and other variables (in an attempt to capture various subjective elements) in determining issuer credit ratings between the two major CRAs. Utilising a sample of 5192 firm-year observations from S&P400, S&P500 and S&P600 index constituent issuer firms, we employ an ordered probit model on a panel dataset spanning 1995 through 2009. The empirical results suggest that the agencies indeed differ on the level of importance they attach to each variable. We conclude that financial information remains the most significant factor in the attribution of credit ratings for both the agencies. We find no significant improvement in the predictive power of credit rating when we incorporate governance related variables. Our other factors show strong evidence of continuing stringent standards, reputational concerns, and differences in standards during economic crises by the two rating agencies. The third essay investigates the factors determining the allocation of different (split) credit ratings to the same firm by the two agencies. We use financial, governance and other factors in an attempt to capture various subjective elements to explain split credit ratings. The study uses a two-stage bivariate probit estimation method. We use a sample of 5238 firm-year observations from S&P 500, S&P 400, and S&P 600 index constituent firms. Our results indicate that a firm having greater size, favourable coverage and higher profitability are less likely to have a split. However, smaller firms with unfavourable coverage and lower profitability appear to be rated lower by Moody’s in comparison to S&P. Our findings suggest that the stage of the business cycle plays no significant role in deciding splits, but rating shopping and the introduction of regulation FD increase the likelihood of splits arising.

Investment in hospitality firms is perceived to be riskier than investments in other types of industries. Based on literature linking good corporate governance to lower default risks and higher credit ratings, this quantitative study is designed to identify the effects of corporate governance on credit ratings in the hospitality industry. After exploring the various factors influencing the characteristics of corporate governance, as well as the specific risks for capital financing in hospitality firms, this research provides empirical evidence to show that hospitality firms with stronger shareholder influence tend to have higher credit ratings. In a related finding, this investigation confirms that hospitality stakeholders are able to evaluate their potential risks by determining a firm's credit ratings and can protect their long-term interest by increasing their power versus management in the corporate governance of the firm. / Master of Science

This write-up is submitted in partial fulfillment of the Master of Management Degree in Finance and Investment / Through the use of an EGARCH model and a fixed effects panel regression, the reaction of emerging market stock and bond volatility to sovereign credit ratings changes is examined. The daily data covers the period of 1990 to 2016 and emerging market crises, such as the 1994 Mexican peso crisis, 1997 Asian financial crises and the global 2008 financial crises. The estimations provide evidence of an asymmetric effect of rating changes on stock volatilities, whereby downgrades have a significant impact, while upgrades have no such effect. For bonds the effect is ambiguous with both upgrades and downgrades having an effect. Downgrades are found to increase both stock and bond market volatility. On aggregate, contagion effects amongst stocks are found for emerging markets, as well as for the continents of Asia and Europe. No such evidence is found for bonds. / MT2017