This thesis deals with credit risk modeling and related mathematical issues. In particular we study first-passage models for credit risk, where obligors default upon first passage of a ``credit quality" process to zero. The first passage problem for correlated Brownian motion is a mathematical structure which arises quite naturally in such models, in particular the seminal multivariate Black-Cox model. In general this problem is analytically intractable, however in two dimensions analytic results are available. In addition to correcting mistakes in several published formulae, we derive an exact simulation scheme for sampling the passage times. Our algorithm exploits several interesting properties of planar Brownian motion and conformal local martingales. The main contribution of this thesis is the development of a novel multivariate framework for credit risk. We allow for both stochastic trend and volatility in credit qualities, with dependence introduced by letting these quantities be driven by systematic factors common to all obligors. Exploiting a conditional independence structure we are able to express the proportion of defaults in an asymptotically large portfolio as a path functional of the systematic factors. The functional in question returns crossing probabilities of time-changed Brownian motion to continuous barriers, and is typically not available in closed form. As such the distribution of portfolio losses is in general analytically intractable. As such we devise a scheme for simulating approximate losses and demonstrate almost sure convergence of this approximation. We show that the model calibrates well, across both tranches and maturities, to market quotes for CDX index tranches. In particular we are able to calibrate to data from 2006, as well as more recent ``distressed" data from 2008.

This thesis deals with credit risk modeling and related mathematical issues. In particular we study first-passage models for credit risk, where obligors default upon first passage of a ``credit quality" process to zero. The first passage problem for correlated Brownian motion is a mathematical structure which arises quite naturally in such models, in particular the seminal multivariate Black-Cox model. In general this problem is analytically intractable, however in two dimensions analytic results are available. In addition to correcting mistakes in several published formulae, we derive an exact simulation scheme for sampling the passage times. Our algorithm exploits several interesting properties of planar Brownian motion and conformal local martingales. The main contribution of this thesis is the development of a novel multivariate framework for credit risk. We allow for both stochastic trend and volatility in credit qualities, with dependence introduced by letting these quantities be driven by systematic factors common to all obligors. Exploiting a conditional independence structure we are able to express the proportion of defaults in an asymptotically large portfolio as a path functional of the systematic factors. The functional in question returns crossing probabilities of time-changed Brownian motion to continuous barriers, and is typically not available in closed form. As such the distribution of portfolio losses is in general analytically intractable. As such we devise a scheme for simulating approximate losses and demonstrate almost sure convergence of this approximation. We show that the model calibrates well, across both tranches and maturities, to market quotes for CDX index tranches. In particular we are able to calibrate to data from 2006, as well as more recent ``distressed" data from 2008.

Credit derivative has become an important financial instrument in global financial market, it plays significant role in transferring credit risk. During the latest financial crisis, collapse of credit derivative market was a main reason led to this worldwide turmoil. In this thesis, I try to investigate this adverse performance through a case study of Goldman Sach's ABACUS 2007-AC1. I conclude three major findings. First, severe interest conflicts and asymmetric information existed between counterparties in credit derivative market in U.S.. Second, the securities‘ credit ratings provided a downward-biased view of their actual default risks, the yields failed to account for the extreme exposure of structured products to declines in aggregate economic conditions. Third, credit derivatives do not eliminate systematic risk, they just shift the risk, CDOs exchanged diversifiable risk for systematic risk during the structuring process, which was difficult to understand for most of investors, we see risk accumulation rather than spreading risk,

1990年代中期信用衍生信商品開始發展，隨著時代變遷，演化出信用違約交換(Credit Default Swaps, CDS)、擔保債權憑證(Collateralized Debt Obligation, CDO)、合成型擔保債權憑證(Synthetic CDO)等商品，其可以分散風險的特性廣受歡迎，並且成為完備金融市場中重要的一環。在2007年金融海嘯中，信用衍生性商品扮演相當關鍵的角色，所以如何合理定價各類信用衍生性商品就變成相當重要的議題 以往在定價合成型擔保債權憑證時，多採取單因子結構模型來做為報酬函數的主要架構，並假設模型分配為常態分配、t分配、NIG分配等，但單因子結構模型的隱含相關係數具有波動性微笑現象，所以容易造成定價偏誤。 為了解決此問題，本文將引用常態分配假設與NIG分配假設下的隨機風險因子負荷模型(Random Factor Loading Model)，觀察隨機風險因子負荷模型是否對於定價偏誤較其他模型有所改善，並且比較各模型在最佳化參數與定價時的效率，藉此歸納出較佳的合成型擔保債權憑證定價模型。 / During the mid-1990s, credit-derivatives began to be popular and evolved into credit default swaps (CDS), collateralized debt obligation (CDO), and synthetic collateralized debt obligation (Synthetic CDO). Because of the feature of risk sharing, credit-derivatives became an important part of financial market and played the key role in the financial crisis of 2007. So how to price credit-derivatives is a very important issue. When pricing Synthetic CDO, most people use the one-factor coupla model as the structure of reward function, and suppose the distribution of model is Normal distribution, t- distribution or Normal Inverse Gaussian distribution(NIG). But the volatility smile of implied volatility always causes the pricing inaccurate. For solving the problem, I use the random factor loading model under Normal distribution and NIG distribution in this study to test whether the random factor loading model is better than one-factor coupla model in pricing, and compare the efficience of optimization parameters. In conclusion, I will induct the best model of Synthetic CDO pricing.

根據以往探討評價合成型抵押擔保債務憑證之文獻研究，最廣泛使用的方法應為大樣本一致性資產組合(large homogeneous portfolio portfolio；LHP)假設之單因子常態關聯結構模型來評價，但會因為常態分配的厚尾度及偏斜性造成與市場報價間的差異過大，且會造成相關性微笑曲線現象。故像是Kalemanova et al.在2007年提出之應用LHP假設的單因子Normal Inverse Gaussian(NIG)關聯結構模型以及邱嬿燁(2007)提出NIG及Closed Skew Normal(CSN)複合分配之單因子關聯結構模型(MIX模型)皆是為了改善其在各分劵評價時能達到更佳的評價結果 ，然而過去的文獻在評價合成型抵押擔保債務憑證時，需要將CDS價差、各分劵真實報價之資訊導入模型，並藉由此兩種資訊進而得到相關係數及報價，故靜態模型大多為事後之驗證，在靜態模型方面，我們嘗試使用不同概念之CDS取法以及相對到期日期數遞減之概念來比較此兩種不同方法與原始的關聯結構模型進行比較分析，在動態模型方面，我們應用與時間序列相關之方法套入以往的評價模型，針對不同商品結構的合成型抵押擔保債券評價，並由實證分析來比較此兩種模型，而在最後，我們利用時間序列模型來對各分劵進行預測。

根據以往探討評價合成型抵押擔保債券之文獻研究，最廣為使用的方法應用大樣本一致性資產組合(large homogeneous portfolio portfolio ; LHP)假設之單因子常態關聯結構模型來評價，但會造成合成型抵押擔保債券憑證與市場報價間的差異過大，且會造成相關性微笑曲線現象。由文獻顯示，單因子關聯結構模型若能加入厚尾度或偏斜性能夠改善以上問題，且對於分券評價時也會有較好的效果，像是Kalemanova et al. (2007) 提出應用LHP假設之單因子Normal Inverse Gaussian(NIG)關聯結構模型以及邱嬿燁(2007)提出NIG及Closed Skew Normal(CSN)複合分配之單因子關聯結構模型(MIX模型)在實證分析中得到極佳的評價結果。自2008年起，合成型抵押擔保債券商品結構開始出現變化，而以往評價合成型抵押擔保債券價格時，商品結構皆為同一種型式。本文將利用常態分配、NIG分配、CSN分配以及NIG與CSN複合分配作為不同的單因子關聯結構模型，藉由絕對誤差極小化方法，針對不同商品結構的合成型抵押擔保債券評價，並進行模型比較分析。由最後實證分析結果顯示，單因子NIG(2)關聯結構模型優於其他模型，也證明NIG分配的第二個參數 β 能夠帶來改善的評價效果，此項證明與過去文獻結論有所不同，但 MIX模型則為唯一一個符合LHP假設的模型。 / Based on the literature of discussing the approach for pricing synthetic CDOs, the most widely used methods used application of Large Homogeneous Portfolio (LHP) assumption of the one factor Gaussian copula model, however , it fails to fit the prices of synthetic CDOs tranches and leads to the implied correlation smile. The literature shows that one factor copula model adding the heavy-tail or skew can improve the above problem, and also has a good effect for pricing tranches such as Kalemanova et al (2007) proposed the application of LHP assumption of one factor NIG copula model and Qiu Yan Ye (2007) proposed the application of LHP assumption of one factor NIG and CSN copula model. This article found that the structure of synthetic CDOs began to change since 2008. The past of pricing synthetic CDOs, the structure of synthetic CDOs are the same type, so this article will use different one factor copula model for pricing different structure of synthetic CDOs by using the absolute error minimization. This article will observe whether the above model can be applied in the new synthetic CDOs and implement of different type model for comparative analysis. The last empirical analysis shows that one factor NIG (2) copula model is superior to other models, more meeting the actual market demand, also proving the second parameter β of the NIG distribution able to bring about improvements in pricing results. This proving is different for the past literature conclusions. However, the MIX model is the only one in line with the LHP assumptions.

Many analysts believe that problems in the U.S. housing market initiated the 2008–2010 global financial crisis. In this regard, the subprime mortgage crisis (SMC) shook the foundations of the financial industry by causing the failure of many iconic Wall Street investment banks and prominent depository institutions. This crisis stymied credit extension to households and businesses thus creating credit crunches and, ultimately, a global recession. This thesis specifically discusses the SMC and its components, causes, consequences and cures in relation to subprime mortgages, securitization, as well as data. In particular, the SMC has highlighted the fact that risk, credit ratings, profit and valuation as well as capital regulation are important banking considerations. With regard to risk, the thesis discusses credit (including counterparty), market (including interest rate, basis, prepayment, liquidity and price), tranching (including maturity mismatch and synthetic), operational (including house appraisal, valuation and compensation) and systemic (including maturity transformation) risks. The thesis introduces the IDIOM hypothesis that postulates that the SMC was largely caused by the intricacy and design of subprime agents, mortgage origination and securitization that led to information problems (loss, asymmetry and contagion), valuation opaqueness and ineffective risk mitigation. It also contains appropriate examples, discussions, timelines as well as appendices about the main results on the aforementioned topics. Numerous references point to the material not covered in the thesis, and indicate some avenues for further research. In the thesis, the primary subprime agents that we consider are house appraisers (HAs), mortgage brokers (MBs), mortgagors (MRs), servicers (SRs), SOR mortgage insurers (SOMIs), trustees, underwriters, credit rating agencies (CRAs), credit enhancement providers (CEPs) and monoline insurers (MLIs). Furthermore, the banks that we study are subprime interbank lenders (SILs), subprime originators (SORs), subprime dealer banks (SDBs) and their special purpose vehicles (SPVs) such as Wall Street investment banks and their special structures as well as subprime investing banks (SIBs). The main components of the SMC are MRs, the housing market, SDBs/hedge funds/money market funds/SIBs, the economy as well as the government (G) and central banks. Here, G either plays a regulatory or policymaking role. Most of the aforementioned agents and banks are assumed to be risk neutral with SOR being the exception since it can be risk (and regret) averse on occasion. The main aspects of the SMC - subprime mortgages, securitization, as well as data - that we cover in this thesis and the chapters in which they are found are outlined below. In Chapter 2, we discuss the dynamics of subprime SORs' risk and profit as well as their valuation under mortgage origination. In particular, we model subprime mortgages that are able to fully amortize, voluntarily prepay or default and construct a discrete–time model for SOR risk and profit incorporating costs of funds and mortgage insurance as well as mortgage losses. In addition, we show how high loan–to–value ratios due to declining housing prices curtailed the refinancing of subprime mortgages, while low ratios imply favorable house equity for subprime MRs. Chapter 3 investigates the securitization of subprime mortgages into structured mortgage products such as subprime residential mortgage–backed securities (RMBSs) and collateralized debt obligations (CDOs). In this regard, our discussions focus on information, risk and valuation as well as the role of capital under RMBSs and RMBS CDOs. Our research supports the view that incentives to monitor mortgages has been all but removed when changing from a traditional mortgage model to a subprime mortgage model. In the latter context, we provide formulas for IB's profit and valuation under RMBSs and RMBS CDOs. This is illustrated via several examples. Chapter 3 also explores the relationship between mortgage securitization and capital under Basel regulation and the SMC. This involves studying bank credit and capital under the Basel II paradigm where risk–weights vary. Further issues dealt with are the quantity and pricing of RMBSs, RMBS CDOs as well as capital under Basel regulation. Furthermore, we investigate subprime RMBSs and their rates with slack and holding constraints. Also, we examine the effect of SMC–induced credit rating shocks in future periods on subprime RMBSs and RMBS payout rates. A key problem is whether Basel capital regulation exacerbated the SMC. Very importantly, the thesis answers this question in the affirmative. Chapter 4 explores issues related to subprime data. In particular, we present mortgage and securitization level data and forge connections with the results presented in Chapters 2 and 3. The work presented in this thesis is based on 2 peer–reviewed chapters in books (see [99] and [104]), 2 peer–reviewed international journal articles (see [48] and [101]), and 2 peer–reviewed conference proceeding papers (see [102] and [103]). / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2011.

Many analysts believe that problems in the U.S. housing market initiated the 2008–2010 global financial crisis. In this regard, the subprime mortgage crisis (SMC) shook the foundations of the financial industry by causing the failure of many iconic Wall Street investment banks and prominent depository institutions. This crisis stymied credit extension to households and businesses thus creating credit crunches and, ultimately, a global recession. This thesis specifically discusses the SMC and its components, causes, consequences and cures in relation to subprime mortgages, securitization, as well as data. In particular, the SMC has highlighted the fact that risk, credit ratings, profit and valuation as well as capital regulation are important banking considerations. With regard to risk, the thesis discusses credit (including counterparty), market (including interest rate, basis, prepayment, liquidity and price), tranching (including maturity mismatch and synthetic), operational (including house appraisal, valuation and compensation) and systemic (including maturity transformation) risks. The thesis introduces the IDIOM hypothesis that postulates that the SMC was largely caused by the intricacy and design of subprime agents, mortgage origination and securitization that led to information problems (loss, asymmetry and contagion), valuation opaqueness and ineffective risk mitigation. It also contains appropriate examples, discussions, timelines as well as appendices about the main results on the aforementioned topics. Numerous references point to the material not covered in the thesis, and indicate some avenues for further research. In the thesis, the primary subprime agents that we consider are house appraisers (HAs), mortgage brokers (MBs), mortgagors (MRs), servicers (SRs), SOR mortgage insurers (SOMIs), trustees, underwriters, credit rating agencies (CRAs), credit enhancement providers (CEPs) and monoline insurers (MLIs). Furthermore, the banks that we study are subprime interbank lenders (SILs), subprime originators (SORs), subprime dealer banks (SDBs) and their special purpose vehicles (SPVs) such as Wall Street investment banks and their special structures as well as subprime investing banks (SIBs). The main components of the SMC are MRs, the housing market, SDBs/hedge funds/money market funds/SIBs, the economy as well as the government (G) and central banks. Here, G either plays a regulatory or policymaking role. Most of the aforementioned agents and banks are assumed to be risk neutral with SOR being the exception since it can be risk (and regret) averse on occasion. The main aspects of the SMC - subprime mortgages, securitization, as well as data - that we cover in this thesis and the chapters in which they are found are outlined below. In Chapter 2, we discuss the dynamics of subprime SORs' risk and profit as well as their valuation under mortgage origination. In particular, we model subprime mortgages that are able to fully amortize, voluntarily prepay or default and construct a discrete–time model for SOR risk and profit incorporating costs of funds and mortgage insurance as well as mortgage losses. In addition, we show how high loan–to–value ratios due to declining housing prices curtailed the refinancing of subprime mortgages, while low ratios imply favorable house equity for subprime MRs. Chapter 3 investigates the securitization of subprime mortgages into structured mortgage products such as subprime residential mortgage–backed securities (RMBSs) and collateralized debt obligations (CDOs). In this regard, our discussions focus on information, risk and valuation as well as the role of capital under RMBSs and RMBS CDOs. Our research supports the view that incentives to monitor mortgages has been all but removed when changing from a traditional mortgage model to a subprime mortgage model. In the latter context, we provide formulas for IB's profit and valuation under RMBSs and RMBS CDOs. This is illustrated via several examples. Chapter 3 also explores the relationship between mortgage securitization and capital under Basel regulation and the SMC. This involves studying bank credit and capital under the Basel II paradigm where risk–weights vary. Further issues dealt with are the quantity and pricing of RMBSs, RMBS CDOs as well as capital under Basel regulation. Furthermore, we investigate subprime RMBSs and their rates with slack and holding constraints. Also, we examine the effect of SMC–induced credit rating shocks in future periods on subprime RMBSs and RMBS payout rates. A key problem is whether Basel capital regulation exacerbated the SMC. Very importantly, the thesis answers this question in the affirmative. Chapter 4 explores issues related to subprime data. In particular, we present mortgage and securitization level data and forge connections with the results presented in Chapters 2 and 3. The work presented in this thesis is based on 2 peer–reviewed chapters in books (see [99] and [104]), 2 peer–reviewed international journal articles (see [48] and [101]), and 2 peer–reviewed conference proceeding papers (see [102] and [103]). / Thesis (Ph.D. (Applied Mathematics))--North-West University, Potchefstroom Campus, 2011.