Thesis (Ph. D.)--Columbia University, 1989. / Includes bibliographical references (leaves 128-134).

Thesis (M.B.A.)--University of Hong Kong, 1992. / Also available in print.

Inaug.--diss.--Halle. / Lebenslauf. "Literaturverzeichnis":1 p. from front.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1995. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 392-414).

Inaug.--diss.--Halle. / Lebenslauf. "Literaturverzeichnis":1 p. from front.

Thesis (Ph. D.)--University of Wisconsin, 1974. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 293-302).

Thesis (Ph. D.)--Dept. of Economics. University of Missouri--Kansas City, 2005. / "A dissertation in economics and social science consortium." Advisor: James I. Sturgeon. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed June 26, 2006. Includes bibliographical references (leaves 149-161 ). Online version of the print edition.

The Saudi Government’s 2030 Vision directs local banks to increase and improve credit for the Small and Medium Enterprises (SMEs) of the economy (Jadwa, 2017). Banks are, however, still finding it difficult to provide credit for small businesses that meet Basel’s capital requirements. Most of the current credit-risk models only apply to large corporations with little constructed for SMEs applications (Altman and Sabato, 2007). This study fills this gap by focusing on the Saudi SMEs perspective. My empirical work constructs a bankruptcy prediction model based on logistic regressions that cover 14,727 firm-year observations for an 11-year period between 2001 and 2011. I use the first eight years data (2001-2008) to build the model and use it to predict the last three years (2009-2011) of the sample, i.e. conducting an out-of-sample test. This approach yields a highly accurate model with great prediction power, though the results are partially influenced by the external economic and geopolitical volatilities that took place during the period of 2009-2010 (the world financial crisis). To avoid making predictions in such a volatile period, I rebuild the model based on 2003-2010 data, and use it to predict the default events for 2011. The new model is highly consistent and accurate. My model suggests that, from an academic perspective, some key quantitative variables, such as gross profit margin, days inventory, revenues, days payable and age of the entity, have a significant power in predicting the default probability of an entity. I further price the risks of the SMEs by using a credit-risk pricing model similar to Bauer and Agarwal (2014), which enables us to determine the risk-return tradeoffs on Saudi’s SMEs.

>Magister Scientiae - MSc / The first two chapters give the background, history and overview of the dissertation, together with the necessary mathematical preliminaries. Thereafter, the next four chapters deal with credit risk and credit derivatives.The final part of the dissertation is devoted to the Basel II bank regulatory framework and the mathematical modeling of asset allocation in bank management, pertaining to credit risk.Credit risk models can be categorized into two groups known as structural models and reduced form models. These models are used in pricing and hedging credit risk. In this thesis we review a variety of credit risk instruments described by models of the said types. One of the strategies utilized by companies to mitigate credit risk is by using credit derivatives.In this thesis, five main types of risk derivatives have been considered: credit swaps, credit linked notes, credit spreads, total return swaps and collaterized debt obligations. Valuation models for the first three derivatives that are mentioned above, are also presented in this dissertation.The material presented include some of the most recent developments in the literature. Our methods range from single-period modeling to application of stochastic optimal control theory. We expand on the material presented from the literature by way of simplifying or clarifying proofs, and by adding illustrative examples in the form of calculations, tables and simulations.Also, the entire Chapter 6 is a new original contribution to the existing literature on mathematical modeling of credit risk. Key words: credit risk; default risk; structural approach; reduced form approach; incomplete information approach; investment strategy; Basel II regulatory framework

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