Thesis (MBA (Business Management))--University of Stellenbosch, 2008. / ENGLISH ABSTRACT: To date, there has been significant research completed on the topic of corporate financial distress. Two pioneering researchers in the field of predicting financial distress was Beaver in 1966 and Altman in 1968. More recent research, based on companies listed on the JSE has been that of Steyn-Bruwer and Hamman (2006). This project, based on the latter authors’ work, has been formulated with one main research objective and two subordinate research objectives. The main research objective is to prove that different modelling techniques provide better prediction accuracies than others. The two subordinate research objectives are firstly to prove that there is a difference in the overall predictive accuracy if the data (provided by Steyn-Bruwer and Hamman) is subdivided according to “year before failure” and not according to economic period and secondly to prove that more optimised, independent variables would provide a better overall predictive accuracy. This research report summarises several significant papers on the topic; and draws the conclusion that research on financial distress is fragmented with very little consensus on any of the major definitions, assumptions and findings. In order to contextualise these differences; this research report defines and discusses corporate financial distress and considers the major issues associated with the field of research. An interesting observation from the literature survey was the fact that existing literature does not readily take consideration of the number of Type I and Type II errors made. As such, this research report introduces a novel concept (not seen in other research) called the “Normalised Cost of Failure” (NCF) which takes cognisance of the fact that a Type I error typically costs 20 to 38 times that of a Type II error. In order to satisfy the main research objective several different modelling techniques were selected based on their popularity in the literature surveyed. They are: Multiple Discriminant Analysis (MDA), Recursive Partitioning (RP), Logit Analysis (LA) and Neural Networks (NN). A summary of each of the different techniques is provided in Chapter 4 of this research report. The research by Steyn-Bruwer and Hamman forms the departure point for this research and their work is summarised in Chapter 5 of this report. Chapters 6, 7 and 8 use the data from Steyn-Bruwer and Hamman along with the above mentioned modelling techniques to verify the main and subordinate objectives. In terms of the main research objective, the results of these chapters show that the different analysis techniques definitely produce different predictive accuracies. Here, the MDA and RP techniques correctly predict the most “failed” companies; and consequently have the lowest NCF. This research report also shows that LA and NN provide the best overall predictive accuracy. In terms of the first subordinate research objective; this research shows that using the year before failure rather than the economic period as a subdivision provides superior predictive accuracy. With regard to the second subordinate research objective: there is no difference in the predictive accuracies if the independent variables are further optimised. These results were disappointing and consequently disprove the second subordinate objective that widening the number of input variables actually improves the predictive accuracy. In fact, the results indicate that the information contained in the independent variables seems to saturate after the most important (key predictor) independent variables have been included in the model. It is important to take cognisance of the fact that each predictive technique has its own strength and weakness. It is proposed by the author that the strengths and weaknesses of these predictive techniques be combined to provide a better overall predictive methodology. / AFRIKAANSE OPSOMMING: Heelwat betekenisvolle navorsing oor die onderwerp van maatskappye se finansiële verknorsing is tot op hede voltooi. Twee baanbreker-navorsers op die gebied van vooruitskatting van finansiële verknorsing was Beaver in 1966 en Altman in 1968. Meer onlangse navorsing, gebaseer op maatskappye wat op die JSE genoteer is, was dié van Steyn-Bruwer en Hamman (2006). Hierdie navorsingsverslag, gebaseer op die voorgenoemde outeurs se werk, is geformuleer met een hoofnavorsingsdoelwit en twee ondergeskikte navorsingsdoelwitte. Die hoofnavorsingsdoelwit is om te bewys dat verskillende modelleringstegnieke beter voorspellingsakkuraatheid as andere het. Die twee ondergeskikte navorsingsdoelwitte is, eerstens, dat daar ʼn verskil is in die oorhoofse voorspellingsakkuraatheid as die data (verskaf deur Steyn-Bruwer en Hamman) onderverdeel word volgens die “jaar voor mislukking” eerder as volgens die ekonomiese tydperk; en tweedens, om te bewys dat meer geoptimiseerde, onafhanklike veranderlikes kan lei tot ʼn beter oorhoofse voorspellingsakkuraatheid. Ten einde hierdie verskille te konseptualiseer, het hierdie navorsingsverslag finansiële mislukkings van maatskappye bespreek en gedefinieer en aandag geskenk aan die belangrikste aspekte geassosieer met die navorsingsveld. ʼn Interessante waarneming uit die literatuurstudie was die feit dat die huidige literatuur selde indien enige, oorweging skenk aan die aantal Tipe I- en Tipe II-foute wat gemaak word. As sulks het hierdie navorsingsprojek ʼn nuwe begrip (nog nie in ander navorsing gesien nie) ontwikkel, wat beskryf word as die “Genormaliseerde Kostefaktor”; wat die feit dat ʼn Tipe I-fout tipies 20 tot 38 maal die koste van ʼn Tipe II-fout beloop, in ag neem. Ten einde te voldoen aan die hoofnavorsingsdoelwit is verskillende modelleringstegnieke wat op grond van hul gewildheid in die literatuur voorgekom het, gekies. Hulle is: Meervoudige Diskriminantanalise (MDA), Herhalende Verdeling (RP), Logit-Analise (LA) en Neurale Netwerke (NN). ʼn Opsomming van elk van hierdie verskillende tegnieke word in Hoofstuk 4 van hierdie navorsingsverslag verskaf. Die navorsing wat deur Steyn-Bruwer en Hamman gedoen is, vorm die vertrekpunt van hierdie navorsing en hulle werk is gevolglik in Hoofstuk 5 van hierdie verslag opgesom. Hoofstukke 6, 7 en 8 gebruik die data van Steyn-Bruwer en Hamman tesame met die bovermelde modelleringstegnieke ten einde die hoof- en ondergeskikte doelwitte te bewys. In terme van die hoofnavorsingsdoelwit, het die resultate van hierdie hoofstukke getoon dat die verskillende analitiese tegnieke definitief verskillende voorspellingsakkuraatheid oplewer. Hier het die MDA- en RP-tegnieke die grootste aantal mislukte maatskappye korrek voorspel, en gevolglik die laagste Genormaliseerde Kostefaktor gehad. Die navorsingsverslag toon ook dat LA en NN die beste oorhoofse akkuraatheid van voorspelling het. In terme van die eerste ondergeskikte navorsingsprobleem het hierdie navorsing getoon dat, om die jaar voor mislukking te gebruik as onderverdeling, eerder as die ekonomiese tydperk, beter voorspellingsakkuraatheid het. Wat die tweede ondergeskikte navorsingsdoelwit betref, is daar bevind dat daar geen verskille in die voorspellingsakkuraatheid bestaan as die individuele veranderlikes verder geoptimaliseer word nie. Hierdie resultate was teleurstellend en het gevolglik die tweede ondergeskikte probleem, naamlik dat as die aantal inset-veranderlikes sou vergroot word, dit die vooruitskattingsakkuraatheid behoort te kan verhoog, verkeerd bewys. Tewens, die resultate het getoon dat die inligting soos vervat in die onafhanklike veranderlikes klaarblyklik versadiging bereik nadat die belangrikste (hoof-vooruitskatter) onafhanklike veranderlikes in die model opgeneem is. Dit is belangrik om kennis te neem van die feit dat elke vooruitskattingstegniek sy eie sterk en swak punte het. Die skrywer stel dus voor dat hierdie sterk- en swakpunte gekombineerd gebruik word om ʼn beter oorhoofse vooruitskattingsmetodologie daar te stel.

1997年爆發亞洲金融風暴，隔年（1998年）起公司發生財務危機事件層出不窮，1998年至2005年間最為嚴重；2007年全球金融海嘯至今，投資人擔心買到地雷股，對於投資股票市場仍採觀望態度。在經過層層把關的財報背後究竟隱藏多少危機？這些危機難道是不可預測的嗎？其實，公司爆發財務危機並非一夕之間產生的問題，就如同人類的慢性病不是一天造成的，是長期忽略身體健康警訊造成的結果，事出必有因，因此許多學者便開始探究財務危機背後的成因，試圖找出一些指標供投資人作為投資前之考量因素。 本研究主要之目的在於探究財務危機之預測指標，分別探討Beta、公司規模、淨值市價比以及前一年平均報酬（負的動能效果）是否可作為財務危機之預測指標。本研究之樣本公司為1983年至2007年之台灣上市公司，利用Altman提出之Z-score模型將公司區分為危機公司以及正常公司，再將樣本公司依Beta、公司規模、淨值市價比以及前一年平均報酬分別分組，探討這些變數是否可作為財務危機之預測指標。實證結果指出Beta及淨值市價比無法作為財務危機之預測指標，但公司規模及前一年平均報酬（負的動能效果）可以作為財務危機之預測指標。 / With the Asian financial crisis breaking out in 1997, many companies began to suffer financial distress in the following year, and the situations were getting even worse during 1998 and 2005. Faced the new waves of financial tsunami across the world starting from 2007, the investor, therefore, have been adopting a wait-and-see attitudes towards the stock market, fearing of being hit by the “tank stocks”。How many financial problems hidden behind the carefully prepared financial statements? Are they unpredictable? As a matter of fact, just like the human chronic diseases which actually caused by long-term ignorance of health warning, corporate financial distress never happens suddenly. Thus a number of scholars are dedicated to study the reasons for financial problems, attempting to figure out certain indicators capable of being prior reference for investment decision-making. This paper aims to study the predictors of financial distress. Beta, firm size, book-to-market ratio and average monthly prior-year return (negative momentum effect) are to be considered respectively to determine their possibilities of being predictors. The sample companies discussed in this paper are chosen among the listed companies during 1983 and 2007 in Taiwan. They are grouped into two categories of crisis company and normal company by using the Z-score model developed by Altman. Then the sample companies are divided in terms of Beta, firm size, book-to-market ratio and average monthly prior-year return so as to trace these variables’ likelihood to predict bankruptcy. It eventually turns out that firm size and average monthly prior-year return could serve as predictors of financial distress, other than Beta and book-to-market ratio.

本研究延續Shumway (2001) 從存活分析(Survival Analysis)觀點切入，利用離散型風險模型(Discrete-time Hazard Model)──亦即Shumway 所稱之多期邏輯斯迴歸模型(Multi-period Logistic Regression Model)，建立企業財務危機預警模型。研究選取1986 年至2008 年間718 家上市公司，其中110 家發生財務危機事件，共計6,782 公司/年資料 (firm-year)。有別於Shumway 提出的Log 基期風險型式，本文根據事件發生率圖提出Quadratic 基期風險型式，接著利用4組（或基於會計測量，或基於市場測量）時間相依共變量 (Time-dependent Covariate)建立2 組離散型風險模型(Log 與Quadratic)，並與傳統僅考量單期資料的邏輯斯迴歸模型比較。實證結果顯示，離散型風險模型的解釋變數與破產機率皆符合預期關係，而傳統邏輯斯迴歸模型則有時會出現不符合預期關係的情況；研究亦顯示離散型風險模型預測能力絕大多數情況下優於傳統邏輯斯迴歸模型，在所有模型組合中，以Quadratic 基期風險型式搭配財務變數、市場變數的解釋變數組合而成的離散型風險模型，擁有最佳預測能力。 / Based on the viewpoint of survival analysis from Shumway (2001), the presentthesis utilizes discrete-time hazard model, also called multi-period logistic regression model, to forecast corporate financial distress. From 1986 to 2008, this research chooses 718 listed companies within, which includes 110 failures, as the subjects, summing to 6,782 firm-year data. Being different from Shumway’s log baseline hazard form,we proposed to use quadratic baseline hazard form according to empirical evidence. Then, four groups of time-dependent covariates, which are accounting-based measure or market-based measure, are applied to build two sets of discrete-time hazard model, which is compared with the single-period logistic regression model. The results show that there exists the expected relationship between covariates and predict probability in discrete-time hazard model, while there sometimes lacks it in single-period logistic regression model. The results also show that discrete-time hazard model has better predictive capability than single-period logistic regression model. The model, which combines quadratic baseline hazard form with market and accounting variables, has the best predictive capability among all models.

Cette thèse examine les effets des imperfections des marchés financiers sur la macroéconomie. Plus particulièrement, elle se penche sur les conséquences de la faillite dans les contrats financiers dans une perspective d'équilibre général dynamique. Le premier papier construit un modèle qui utilise l'avantage comparatif des banques dans la gestion des situations de détresse financière pour expliquer le choix des firmes entre les prêts bancaires et les prêts du marché financier. Le modèle réussit à expliquer pourquoi les firmes plus petites préfèrent le financement bancaire et pourquoi les prêts bancaires sont plus répandus en Europe. Le premier fait est expliqué par le lien négatif entre la valeur nette de l'entreprise et la probabilité de faire faillite. Le deuxième fait s'explique par le coût fixe d'émission de bons plus élevé en Europe. Le deuxième papier examine l'interaction entre les contraintes de financement affectant les ménages et les firmes. Une interaction positive pourrait amplifier et augmenter la persistance de l'effet d'un choc agrégé sur l'économie. Je construis un nouveau modèle qui contient des primes de financement externes pour les firmes et les ménages. Dans le modèle de base avec prix et salaires flexibles, j'obtiens une faible interaction négative entre les coûts de financement des firmes et des ménages. Le facteur clé qui explique ce résultat est l'effet du changement contre cyclique du coût de financement des ménages sur leur offre de travail et leur demande de prêts. Dans une période d'expansion, cet effet augmente les taux d'intérêt, réduit l'investissement et augmente le coût de financement des entreprises. Le troisième papier ajoute les contraintes de financement des banques dans un modèle macroéconomiques avec des prêts hypothécaires et des fluctuations dans les prix de l'immobilier. Les banques dans le modèle ne peuvent pas complètement diversifier leurs prêts, ce qui génère un lien entre les risques de faillite des ménages et des banques. Il y a deux effets contraires des cycles économiques qui affectent la prime de financement externe de la banque. Premièrement, il y a un lien positif entre le risque de faillite des banques et des emprunteurs qui contribue à rendre le coût de financement externe des banques contre cyclique. Deuxiément, le lissage de la consommation par les ménages rend la proportion de financement externe des banques pro cyclique, ce qui tend à rendre le coût de financement bancaire pro cyclique. En combinant ces deux effets, le modèle peut reproduire des profits bancaires et des ratios d'endettement bancaires pro cycliques comme dans les données, mais pour des chocs non-financiers les frictions de financement bancaire dans le modèle n'ont pas un effet quantitativement significatif sur les principales variables agrégées comme la consommation ou l'investissement. / This Dissertation examines the effect of financial market imperfections on the Macroeconomy. More particularly, it focuses on the consequences of equilibrium default using a Dynamic General Equilibrium approach. The first paper builds a dynamic general equilibrium model that emphasizes banks' comparative advantage in monitoring financial distress in order to explain firms' choice between bank loans and market debt. Banks can deal with financial distress more cheaply than bond holders, but this requires a higher initial expenditure proportional to the loan size. In contrast, bond issues may involve a small fixed cost. Entrepreneurs' choice of bank or bond financing depends on their net worth. The model can explain why smaller firms tend to use more bank financing and why bank financing is more prevalent in Europe than in the US. The first fact can be explained by the negative link between the net worth of a business and its default probability. Explaining the second fact requires taking into account the higehr fixed cost of issuing market debt in Europe. The second paper examines the possibility of feedback effects between between the financing constraints of households and of firms. A positive interaction between the financial strength of household and firm balance sheets may amplify aggregate shocks and increase the persistence of aggregate fluctuations. I develop a new model that incorporates both firm and household external finance spreads and time varying leverage. Contrary to a common intuition, the baseline Real Business Cycle model with credit constraints produces a small negative interaction between the costs of external financing for firms and households. The key factor in this result is the effect of changes in the external finance premium on borrowers' labour supply and the demand for loans. The reduction in households' cost of borrowing in a boom decreases labour supply and raises houshold loan demand. This increases interest rates, crowds out investment, and raises borrowing costs for financially constrained firms. The third paper integrates household financing frictions with bank financing frictions and house price fluctuations in a dynamic general equilibrium model. The key assumption in the model is that a bank cannot fully diversify shocks, leading to a link between household and bank sectors' default risks. The cyclical behaviour of banks' external funding cost is determined by two main factors. On one hand, booms improve the financial health of the banks' borrowers which tends to reduce the cost of bank funding. On the other hand, consumption smoothing by savers and borrowers during booms increases the proportion of external financing in the banks' balance sheet which tends to increase the cost of bank funding. As a result of these opposing effects, the model matches procyclical profits and leverage in the financial sector, as observed in the data, but for non financial shocks the banking frictions in the model have an insignificant impact on the main macroeconomic aggregates such as output, consumption and investment.

Cette thèse porte sur la prédiction de la détresse financière et son impact sur le rendement des actions. L’objet principal de cette thèse est de : (i) prédire la détresse financière des petites et moyennes entreprises françaises en utilisant plusieurs spécifications économétriques tels que, le modèle Logit, les réseaux de neurones artificiels, la méthode SVM et la régression des moindres carrés partiels, et (ii) d’identifier les facteurs de risque de détresse financière à caractère systématique, explicatifs des rendements des actions, et additionnels au modèle de Fama et French (1993) tels que le momentum, la détresse relative, la liquidité et la Value-at-Risk, sur le marché boursier Français. Cette étude comporte deux parties. La première partie, composée de 2 chapitres, s’interroge sur les principaux indicateurs discriminants entre les petites et moyennes entreprises françaises saines et celles en détresse financière un an et deux ans avant la défaillance. Elle mobilise différentes approches de prédiction et aboutit à des résultats empiriques qui font l’objet d’analyse. La deuxième partie, composée aussi de 2 chapitres, étudie le pouvoir explicatif, du modèle de Fama et French (1993) augmenté de certains facteurs de risque, mais aussi des modèles alternatifs à cette approche dans le contexte français. Les tests portent aussi sur le caractère systématique des facteurs de risque additionnels ou alternatifs, explicatifs des rendements des actions. Les résultats empiriques obtenus font l’objet d’analyse et permettent de proposer des implications managériales aux décideurs. / This thesis focuses on financial distress and its impact on stock returns. The main goal of this dissertation is: (i) to predict the financial distress of French small and medium-sized firms using a number of techniques namely Logit model, Artificial Neural Networks, Support Vector Machine techniques, and Partial Least Squares, and (ii) to identify the systematic risk factors of financial distress that can explain stock returns, in addition to those of Fama and French (1993) such as the momentum, the relative distress, the liquidity, and the Value-at-Risk in the French stock market. This study has been concretized in two parts. The first part, composed of 2 chapters, wonders about the main indicators that can discriminate between distressed and non-distressed French small and medium-sized firms one and two years before default. It mobilizes different prediction techniques and leads to the empirical results that are the subject of the analysis. The second part, composed also of 2 chapters, investigates the explanatory power of Fama and French (1993) model augmented by a number of risk factors, as well as alternative models in the French context. The tests also focus on the systematic nature of the additional or alternative risk factors, explaining the stock returns. The obtained empirical results are analyzed and propose managerial implications to decision makers.

企業發生財務危機，不僅使其經營陷入生死關頭之掙扎，更影響眾多投資人、債權人的利益，對於整個經濟環境亦造成一定的衝擊。因此，如何提早察覺企業之危機，以減少社會成本，實值得我們深入研究。 本研究主要目的為評估現金流量表揭露之資訊，於預測企業財務危機的有用性。本研究欲探討現金流量資訊是否為預測企業財務危機的良好指標，於建構企業財務危機預警模式之際，加入現金流量的財務指標是否會比僅以傳統財務比率建立之預警模式，更具預測能力。 本研究採用配對樣本設計，在我國上市公司中共選取了35家危機公司與68家正常公司。並利用Logit迴歸分析分別建立現金流量模式、應計財務模式與綜合模式，得到以下結論： 一、在財務危機發生之前一至三年，本研究所使用的應計基礎財務比率並非皆適合用來區分危機公司與正常公司。 二、除了營業活動現金流量相關比率具有顯著的區別能力外，部分投資與融資活動現金流量相關比率亦提供額外的財務危機警訊。 三、現金流量比率預警模式之預測力表現不遜於應計基礎比率模式；但在應計基礎比率中加入現金流量比率，並未顯著提高模式的預測能力。 / The objective of this study is to assess the usefulness of cash flow disclosures in the prediction of financial distress. This study also determines whether cash flow ratios are good indicator of financial distress and whether adding cash flow ratios in prediction model can improve the predictive ability of the model employing conventional accrual-based ratios. Using a matched pair design, this study examines a sample of 35 distress firms along with 68 non-distress firms. Also, a logistic regression analysis is used to establish the financial distress model with and without cash flow variables respectively, in order to test the hypotheses developed by this study and to derive the conclusion. The findings of this study are as follows. 1. During the period between 3 years to 1 year before financial distress, the accrual-based ratios used in this study aren't all good predictor in financial distress model. 2. The discriminate ability of operating cash flow data is significant. Also, the investing and financing cash flow data provide additional information in the prediction of business distress. 3. Cash flow ratios provide a superior measure for the prediction of financial distress over accrual-based ratios. However, no significant evidence shows that using cash flow ratios in conjunction with accrual-based ratios can improve the overall predictive power of accrual-based ratios alone.

過去已有許多技術應用來建立預測財務危機的模型，如統計學的多變量分析或是類神經網路等分類技術。這些早期預測財務危機的模型大多以財務比率作為變數。然而歷經安隆（Enron）、世界通訊（WorldCom）等世紀騙局，顯示財務數字計算而成的財務比率有其天生的限制，無法在公司管理階層蓄意虛增盈餘時，及時給予警訊。因此，本論文初步探勘共同比分析、公司治理及傳統的Altman財務比率等研究方法，試圖突破財務比率在財務危機預測問題的限制，選出可能提高財務危機預測的特徵群。接著，我們進一步應用基因演算法篩選質性與非質性的特徵，期望藉由基因演算法裡子代獲得親代間最優基因的交配過程，可以讓子代的適應值最大化，找出最佳組合的特徵群，然後以此特徵群訓練支持向量機預測模型，以提高財務預測效果並降低公眾的損失。實驗結果顯示，共同比分析與公司治理等相關特徵確實能提升預測財務危機模型的預測效果，我們應當用基因演算法嘗試更多質性與非質性的特徵組合，及早預警財務危機公司以降低社會成本。

Cette thèse examine les effets des imperfections des marchés financiers sur la macroéconomie. Plus particulièrement, elle se penche sur les conséquences de la faillite dans les contrats financiers dans une perspective d'équilibre général dynamique. Le premier papier construit un modèle qui utilise l'avantage comparatif des banques dans la gestion des situations de détresse financière pour expliquer le choix des firmes entre les prêts bancaires et les prêts du marché financier. Le modèle réussit à expliquer pourquoi les firmes plus petites préfèrent le financement bancaire et pourquoi les prêts bancaires sont plus répandus en Europe. Le premier fait est expliqué par le lien négatif entre la valeur nette de l'entreprise et la probabilité de faire faillite. Le deuxième fait s'explique par le coût fixe d'émission de bons plus élevé en Europe. Le deuxième papier examine l'interaction entre les contraintes de financement affectant les ménages et les firmes. Une interaction positive pourrait amplifier et augmenter la persistance de l'effet d'un choc agrégé sur l'économie. Je construis un nouveau modèle qui contient des primes de financement externes pour les firmes et les ménages. Dans le modèle de base avec prix et salaires flexibles, j'obtiens une faible interaction négative entre les coûts de financement des firmes et des ménages. Le facteur clé qui explique ce résultat est l'effet du changement contre cyclique du coût de financement des ménages sur leur offre de travail et leur demande de prêts. Dans une période d'expansion, cet effet augmente les taux d'intérêt, réduit l'investissement et augmente le coût de financement des entreprises. Le troisième papier ajoute les contraintes de financement des banques dans un modèle macroéconomiques avec des prêts hypothécaires et des fluctuations dans les prix de l'immobilier. Les banques dans le modèle ne peuvent pas complètement diversifier leurs prêts, ce qui génère un lien entre les risques de faillite des ménages et des banques. Il y a deux effets contraires des cycles économiques qui affectent la prime de financement externe de la banque. Premièrement, il y a un lien positif entre le risque de faillite des banques et des emprunteurs qui contribue à rendre le coût de financement externe des banques contre cyclique. Deuxiément, le lissage de la consommation par les ménages rend la proportion de financement externe des banques pro cyclique, ce qui tend à rendre le coût de financement bancaire pro cyclique. En combinant ces deux effets, le modèle peut reproduire des profits bancaires et des ratios d'endettement bancaires pro cycliques comme dans les données, mais pour des chocs non-financiers les frictions de financement bancaire dans le modèle n'ont pas un effet quantitativement significatif sur les principales variables agrégées comme la consommation ou l'investissement. / This Dissertation examines the effect of financial market imperfections on the Macroeconomy. More particularly, it focuses on the consequences of equilibrium default using a Dynamic General Equilibrium approach. The first paper builds a dynamic general equilibrium model that emphasizes banks' comparative advantage in monitoring financial distress in order to explain firms' choice between bank loans and market debt. Banks can deal with financial distress more cheaply than bond holders, but this requires a higher initial expenditure proportional to the loan size. In contrast, bond issues may involve a small fixed cost. Entrepreneurs' choice of bank or bond financing depends on their net worth. The model can explain why smaller firms tend to use more bank financing and why bank financing is more prevalent in Europe than in the US. The first fact can be explained by the negative link between the net worth of a business and its default probability. Explaining the second fact requires taking into account the higehr fixed cost of issuing market debt in Europe. The second paper examines the possibility of feedback effects between between the financing constraints of households and of firms. A positive interaction between the financial strength of household and firm balance sheets may amplify aggregate shocks and increase the persistence of aggregate fluctuations. I develop a new model that incorporates both firm and household external finance spreads and time varying leverage. Contrary to a common intuition, the baseline Real Business Cycle model with credit constraints produces a small negative interaction between the costs of external financing for firms and households. The key factor in this result is the effect of changes in the external finance premium on borrowers' labour supply and the demand for loans. The reduction in households' cost of borrowing in a boom decreases labour supply and raises houshold loan demand. This increases interest rates, crowds out investment, and raises borrowing costs for financially constrained firms. The third paper integrates household financing frictions with bank financing frictions and house price fluctuations in a dynamic general equilibrium model. The key assumption in the model is that a bank cannot fully diversify shocks, leading to a link between household and bank sectors' default risks. The cyclical behaviour of banks' external funding cost is determined by two main factors. On one hand, booms improve the financial health of the banks' borrowers which tends to reduce the cost of bank funding. On the other hand, consumption smoothing by savers and borrowers during booms increases the proportion of external financing in the banks' balance sheet which tends to increase the cost of bank funding. As a result of these opposing effects, the model matches procyclical profits and leverage in the financial sector, as observed in the data, but for non financial shocks the banking frictions in the model have an insignificant impact on the main macroeconomic aggregates such as output, consumption and investment.

1999年新巴塞爾協定規定鼓勵銀行採用內部信用評等法(internal ratings based approach)，以衡量貸款者無法償還之風險以計提最低資本。為因應此一授信風險控管之需要，銀行亟需建立一套有效之財務危機預警系統，以判定銀行授信客戶發生財務危機之機率。 本研究運用羅吉斯迴歸分析(logistic regression analysis)與離散時間涉險分析(discrete-time survival analysis)分法於三種相互具有巢狀式關連性之財務危機預測模型，逐步加入財務、非財務及公司治理變數，以便在同一種分析方法下比較三種模型，以及在同一種模型下比較兩種分析方法。實證結果顯示，就樣本期間內而言，同一種分析方法下模型之財務危機預測能力，隨著不同種類解釋變數之加入而逐步提高。然而，就樣本期間外而言，同一種分析方法下模型之財務危機預測能力，並未隨著不同種類解釋變數之加入而逐步提高，但分類能力皆十分優良；而在同一種模型下離散時間涉險分析方法之整體分類能力皆高於羅吉斯迴歸分析方法。 / The 1999 Basel II Accord suggests banks measure the impossibility of reimbursement of debtors to calculate capital minimums by internal ratings-based approach. To reduce the credit risk, it is important that banks construct accurate financial distress prediction systems to determine the probability of financial distress of debtors. This study employs logistic regression and discrete-time hazard analysis to construct nested models to which the financial, non-financial, and corporate governance corporate variables are added step by step. I therefore make comparison of the performance of three models under logistic regression and discrete-time hazard analysis, respectively. Meanwhile, the comparison of the performance of logistic regression and discrete-time hazard analyses under each of three models is also made. The empirical results show that the in-sample predictive ability of financial distress is enhanced by gradually incorporating different kinds of variables in both analyses. Although the out-of-the-sample predictive ability of financial distress is not improved by gradually incorporating different kinds of variables in one analysis, the model performance is quite well overall. The entire discriminability of discrete-time hazard analysis is better than logistic regression under each model.

South African company law has provided for the rescue of financially distressed companies since 1926 when the statutory procedure of judicial management was introduced by the Companies Act 46 of 1926. Unfortunately, judicial management has never been regarded as a successful corporate rescue procedure and for most of its existence it has been severely criticised on many grounds. The Companies Act 61 of 1973 that replaced the Companies Act 46 of 1926 did very little to improve this situation and judicial management remained underutilised. As a result, the Companies Act 71 of 2008 now introduces two newly-created corporate rescue procedures in the form of business rescue proceedings and the compromise with creditors. This study analyses judicial management and the new corporate rescue procedures to establish whether the identified weaknesses of judicial management have been adequately and effectively addressed in the new procedures. A comparative study with similar procedures in England and Germany is undertaken to determine whether the South African legislature has delivered on its promise to create a system of corporate rescue that will meet the needs of a modern South African economy. Several weaknesses in the new procedures are identified and a number of recommendations are made to improve the relevant provisions and to assist in providing South African company law with an efficient and acceptable corporate rescue regime. / Mercentile Law / LLD (Mercentile Law)