Master-Arbeit Univ. St. Gallen, 2008.

University, Diss.--Tübingen, 2007.

Background: The financial crisis of 2007-2010 had a massive impact on the financial markets worldwide. The crisis was partly blamed on the credit derivatives collateralized debt obligations and credit default swaps. These instruments were used to create leverage and speculation, which led to uncertainty in the financial system worldwide. There has been no recent documentation of how credit derivatives are used in Swedish banks, and what risks and opportunities they bring along. Purpose: The purpose of this thesis is to describe the use of credit derivatives in Swedish banks, what benefits and risks they may generate and how the recent financial crisis has affected their use. Research Method: This is a qualitative multiple case study which uses an inductive approach. The study covers four cases, three of the largest Swedish commercial banks, and a bank that specializes on international financing. Seven people working in different fields in these banks have been interviewed. Conclusions: Credit derivatives are mostly used for hedging in Swedish banks, which mainly involves the use of credit default swaps, and sometimes iTraxx. Purely speculative trades are rare. The risks that arise are mainly due to lack of transparency in OTC trading, and abusive use of these instruments. Credit derivatives greatly facilitate risk management in banks. Regulations have increased since the financial crisis and the demand for more complex products greatly decreased.

Thesis (doctoral)--Universität St. Gallen, 2009.

Master-Arbeit Univ. St. Gallen, 2008.

在市場上最常被用來評價抵押債務債券(Collateralized Debt Obligation, CDO)的分析方法即為應用大樣本同質性資產組合(Large Homogeneous Portfolio, LHP)假設之單因子關聯結構模型(One Factor Copula Model)。由過去文獻指出，自2008年起，抵押債務債券的商品結構已漸漸出現改變，而目前所延伸之各種單因子關聯結構模型在新型商品的評價結果中皆仍有改善空間。 在本文中使用標準化偏斜Student-t分配(Standardized Skew Student-t distribution, SSTD)取代傳統的高斯分配進行抵押債務債券之分券的評價，此分配擁有控制分配偏態與峰態的參數。但是與Student-t分配相同，SSTD同樣不具備穩定的摺積(convolution)性質，因此在評價過程中會額外消耗部分時間。而在實證分析中，以單因子SSTD關聯結構模型評價擔保債務債券新型商品之分券時得到了較佳的結果，並且比單因子高斯關聯結構模型擁有更多參數以符合實際需求。 / The most widely used method for pricing collateralized debt obligation(CDO) is the one factor copula model with Large Homogeneous Portfolio assumption. Based on the literature of discussing, the structure of CDO had been changed gradually since 2008. The effects for pricing new type CDO tranches in the current extended one factor copula models are still improvable. In this article, we substitute the Gaussian distribution with the Standardized Skew Student-t distribution(SSTD) for pricing CDO tranches, and it has the features of heavy-tail and skewness. However, similar to the Student-t distribution, the SSTD is not stable under convolution as well. For this reason, it takes extra time in the pricing process. The empirical analysis shows that the one factor SSTD copula model has a good effect for pricing new type CDO tranches, and furthermore it brings more flexibility to the one factor Gaussian copula model.

This diploma work describes the financial and economical crisis that has emerged in the USA during the year 2007. In the work the preceding recessions and the flow of the current crisis are being analyzed. Attention is also given to a detailed study of the pre-crisis period in the USA economics and the identification of the root causes of the crisis and their interrelationship. The final part of the work is dedicated to the examination of the crisis consequences and the possible ways of its progress

The main task of the diploma thesis is an analysis of financial performance and position of Morgan Stanley during several successive periods before and during the subprime financial crisis. Through the analysis of trends in key items, it also demonstrates strong cyclicality of financial performance and position of the investment bank. The first chapter deals with history and key divisions of the Company. The following chapter generally discusses selected phenomena, which, as per the author's view, significantly influenced industry-wide record-breaking performance during the period before the subprime crisis, and which substantially determined Morgan Stanley's risk profile and performance's corrections later during the Crisis. The core part of the Thesis is conceived as an analysis of financial performance and position of Morgan Stanley during the selected periods. The analysis of pre-crisis period until 2006 in the third chapter demonstrates growth of activities lying behind the unprecedented profitability of the Institution. The following fourth chapter analyzes deteriorating financial performance during the subprime crisis and indicates crucial strategy changes, implemented by the Company at the end of 2008. Effects of the strategic changes and challenges of the future development of the Institution are discussed in the last chapter. Additionally, the Thesis includes annexes, which further deal with selected topics and their general relations to investments banks and two annexes which compare Morgan Stanley with its nearest peers during specific periods.

In the last decade, a considerable growth has been added to the volume of the credit risk derivatives market. This growth has been followed by the current financial market turbulence. These two periods have outlined how significant and important are the credit derivatives market and its products. Modelling-wise, this growth has parallelised by more complicated and assembled credit derivatives products such as mth to default Credit Default Swaps (CDS), m out of n (CDS) and collateralised debt obligation (CDO). In this thesis, the Lévy process has been proposed to generalise and overcome the Credit Risk derivatives standard pricing model's limitations, i.e. Gaussian Factor Copula Model. One of the most important drawbacks is that it has a lack of tail dependence or, in other words, it needs more skewed correlation. However, by the Lévy Factor Copula Model, the microscopic approach of exploring this factor copula models has been developed and standardised to incorporate an endless number of distribution alternatives those admits the Lévy process. Since the Lévy process could include a variety of processes structural assumptions from pure jumps to continuous stochastic, then those distributions who admit this process could represent asymmetry and fat tails as they could characterise symmetry and normal tails. As a consequence they could capture both high and low events¿ probabilities. Subsequently, other techniques those could enhance the skewness of its correlation and be incorporated within the Lévy Factor Copula Model has been proposed, i.e. the 'Stochastic Correlated Lévy Factor Copula Model' and 'Lévy Random Factor Loading Copula Model'. Then the Lévy process has been applied through a number of proposed Pricing Basket CDS&CDO by Lévy Factor Copula and its skewed versions and evaluated by V-FFT limiting and mixture cases of the Lévy Skew Alpha-Stable distribution and Generalized Hyperbolic distribution. Numerically, the characteristic functions of the mth to default CDS's and (n/m) th to default CDS's number of defaults, the CDO's cumulative loss, and loss given default are evaluated by semi-explicit techniques, i.e. via the DFT's Fast form (FFT) and the proposed Very Fast form (VFFT). This technique through its fast and very fast forms reduce the computational complexity from O(N2) to, respectively, O(N log2 N ) and O(N ).

In the last decade, a considerable growth has been added to the volume of the credit risk derivatives market. This growth has been followed by the current financial market turbulence. These two periods have outlined how significant and important are the credit derivatives market and its products. Modelling-wise, this growth has parallelised by more complicated and assembled credit derivatives products such as mth to default Credit Default Swaps (CDS), m out of n (CDS) and collateralised debt obligation (CDO). In this thesis, the Lévy process has been proposed to generalise and overcome the Credit Risk derivatives standard pricing model's limitations, i.e. Gaussian Factor Copula Model. One of the most important drawbacks is that it has a lack of tail dependence or, in other words, it needs more skewed correlation. However, by the Lévy Factor Copula Model, the microscopic approach of exploring this factor copula models has been developed and standardised to incorporate an endless number of distribution alternatives those admits the Lévy process. Since the Lévy process could include a variety of processes structural assumptions from pure jumps to continuous stochastic, then those distributions who admit this process could represent asymmetry and fat tails as they could characterise symmetry and normal tails. As a consequence they could capture both high and low events' probabilities. Subsequently, other techniques those could enhance the skewness of its correlation and be incorporated within the Lévy Factor Copula Model has been proposed, i.e. the 'Stochastic Correlated Lévy Factor Copula Model' and 'Lévy Random Factor Loading Copula Model'. Then the Lévy process has been applied through a number of proposed Pricing Basket CDS&CDO by Lévy Factor Copula and its skewed versions and evaluated by V-FFT limiting and mixture cases of the Lévy Skew Alpha-Stable distribution and Generalized Hyperbolic distribution. Numerically, the characteristic functions of the mth to default CDS's and (n/m) th to default CDS's number of defaults, the CDO's cumulative loss, and loss given default are evaluated by semi-explicit techniques, i.e. via the DFT's Fast form (FFT) and the proposed Very Fast form (VFFT). This technique through its fast and very fast forms reduce the computational complexity from O(N2) to, respectively, O(N log2 N ) and O(N ).