Academic literature on the topic 'Credit valuation adjustment (cva)'

We generalize the arbitrage-free valuation framework for counterparty credit risk (CCR) adjustments when credit triggers are allowed in the contract. The settlement of the deal for the investor could be either obliged or optional to execute when the counterparty hits the credit trigger before any default events from the two parties. General formulas for credit value adjustment (CVA) are given for all four cases: obliged unilateral, obliged bilateral, optional unilateral and optional bilateral. The unilateral CVA with an optional credit trigger is found to be the same as the unilateral CVA with an analogous obliged credit trigger. We show that adding credit triggers will decrease the unilateral CVA for both obliged and optional cases, which are in line with the motivation of investors to reduce CCR. However, adding credit triggers may not necessarily reduce bilateral CVA. Counter-intuitively, we show that the bilateral CVA may actually increase by adding credit triggers. Moreover, the increased amount of bilateral CVA due to credit triggers for one party is exactly the same amount of bilateral CVA reduced for the other party. The CVA calculation is subjected to large uncertainty of model risks, mostly due to the lack of data for calibrating jump-to-default probabilities. Some explicit models for obliged unilateral CVA are discussed with special caveats on the model assumptions. Numerical examples are also given to illustrate the model risk of CVA calculation due to the uncertainty of jump sizes, even though pure jump models are assumed.

Counterparty valuation adjustment (CVA) risk accounts for losses due to the deterioration in credit quality of derivative counterparties with large credit spreads. Of the losses attributed to counterparty credit risk incurred during the financial crisis of 2008-9 were due to CVA risk; the remaining third were due to actual defaults. Regulatory authorities have acknowledged and included this risk in the new Basel III rules. The capital implications of CVA risk in the South African milieu are explored, as well as the sensitivity of CVA risk components to market variables. Proposed methodologies for calculating changes in CVA are found to be unstable and unreliable at high average spread levels.

Since the 2008–2009 financial crisis, banks have introduced a family of X-valuation adjustments (XVAs) to quantify the cost of counterparty risk and of its capital and funding implications. XVAs represent a switch of paradigm in derivative management, from hedging to balance sheet optimization. They reflect market inefficiencies that should be compressed as much as possible. In this work, we present a genetic algorithm applied to the compression of credit valuation adjustment (CVA), the expected cost of client defaults to a bank. The design of the algorithm is fine-tuned to the hybrid structure, both discrete and continuous parameter, of the corresponding high-dimensional and nonconvex optimization problem. To make intensive trade incremental XVA computations practical in real-time as required for XVA compression purposes, we propose an approach that circumvents portfolio revaluation at the cost of disk memory, storing the portfolio exposure of the night so that the exposure of the portfolio augmented by a new deal can be obtained at the cost of computing the exposure of the new deal only. This is illustrated by a CVA compression case study on real swap portfolios.

In this paper we discuss the issue of computation of the bilateral credit valuation adjustment (CVA) under rating triggers, and in presence of ratings-linked margin agreements. Specifically, we consider collateralized OTC contracts, that are subject to rating triggers, between two parties — an investor and a counterparty. Moreover, we model the margin process as a functional of the credit ratings of the counterparty and the investor. We employ a Markovian approach for modeling of the rating transitions of the two parties to the contract. In this framework, we derive the representation for bilateral CVA. We also introduce a new component in the decomposition of the counterparty risky price: namely the rating valuation adjustment (RVA) that accounts for the rating triggers. We give two examples of dynamic collateralization schemes where the margin thresholds are linked to the credit ratings of the parties. Our results are illustrated via computation of various counterparty risk adjustments for a CDS contract and for an IRS contract.

We study the impact of wrong way risk (WWR) on credit valuation adjustment (CVA) for Bermudan options. WWR is modeled by a dependency between the underlying asset and the intensity of the counterparty’s default. Two WWR models are proposed, based on a deterministic function and a CIR-jump (CIRJ) model, respectively. We present a nonnested Monte Carlo approach for computing CVA–VaR and CVA–expected shortfall (ES) for Bermudan options. By varying correlation coefficients, we study the impact of credit quality and WWR on the optimal exercise boundaries and CVA values of Bermudan products. Stress testing is performed.

According to the Basel Committee’s estimate, three quarters of counterparty credit risk losses during the financial crisis in 2008 originate from credit valuation adjustment’s losses and not from actual defaults. Therefore, from 2015, the Third Basel Accord (EU, 2013a) and (EU, 2013b) instructed banks to calculate the capital requirement for the risk of credit valuation adjustment (CVA). Banks are trying to model CVA to hold the prescribed standards and also reach the lowest possible impact on their profit. In this paper, we try to model CVA using methods that are in compliance with the prescribed standards and also achieve the smallest possible impact on the bank’s earnings. To do so, a data set of interest rate swaps from 2015 is used. The interest rate term structure is simulated using the Hull-White one-factor model and Monte Carlo methods. Then, the probability of default for each counterparty is constructed. A safe level of CVA is reached in spite of the calculated the CVA achieving a lower level than CVA previously used by the bank. This allows a reduction of capital requirements for banks.

In the absence of a universally accepted procedure for the credit valuation adjustment (CVA) calculation, we compare a number of different bilateral counterparty valuation adjustment (BVA) formulas. First we investigate the impact of the choice of the closeout convention used in the formulas. Important consequences on default contagion manifest themselves in a rather different way depending on which closeout formulation is used (risk-free or replacement), and on default dependence between the two entities in the deal. Second we compare the full bilateral formula with an approximation that is based on subtracting two unilateral credit valuation adjustment (UCVA) formulas. Although the latter might be attractive for its instantaneous implementation once one has a unilateral CVA system, it ignores the impact of the first-to-default time, when closeout procedures are ignited. We illustrate in a number of realistic cases both the contagion effect due to the closeout convention, and the CVA pricing error due to ignoring the first-to-default time.

Basel III requires banks to include a credit value adjustment (CVA) into capital charges. Both CVA and debt value adjustment (DVA) must be included for derivatives using mark-to-market accounting. An effective method to calculate bilateral-CVA (BR-CVA) by incorporating wrong-way risk (WWR) for a collateralized counterparty is proposed which handles WWR — defined as when counterparty credit exposure increases as default probability increases — by building a trivariate Gaussian copula between the aggregate market risk exposure factor and default quality of the financial institution and counterparty. This paper extends the ordered-scenario copula model proposed in the literature. It links BR-CVA pricing and WWR, which is close to the current regulatory requirement and useful for managing a financial institution's risk. A practical example is provided. Numerical results suggest that the proposed method is efficient and robust and can easily stress test the impact of WWR in BR-CVA pricing.

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short) as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.

This paper investigates calculations of robust X-Value adjustment (XVA), in particular, credit valuation adjustment (CVA) and funding valuation adjustment (FVA), for over-the-counter derivatives under distributional ambiguity using Wasserstein distance as the ambiguity measure. Wrong way counterparty credit risk and funding risk can be characterized (and indeed quantified) via the robust XVA formulations. The simpler dual formulations are derived using recent Lagrangian duality results. Next, some computational experiments are conducted to measure the additional XVA charges due to distributional ambiguity under a variety of portfolio and market configurations. Finally some suggestions for further work are discussed.

This thesis is intended to give an overview of creditvaluation adjustment (CVA) and adjacent concepts. Firstly, the historicalevents that preceded the initiative to reform the Basel regulations and tointroduce CVA as a core component of counterparty credit risk are illustrated.After some conceptual background material, a journey is taken through theregulatory aspects of CVA. The three most commonly used methods for calculatingthe regulatory CVA capital charge are explained in detail and potentialchallenges with the methods are addressed. Further, the document analyses ingreater depth two of the methods; the internal model method (IMM) and thecurrent exposure method (CEM). The differences between these two methods areexplained mathematically and analysed. This comparison is supported bysimulations of portfolios containing interest rate swap contracts with differenttime to maturity and of counterparties with varying credit ratings. Oneconcluding observations is that credit valuation adjustment is a measure of centralimportance within counterparty credit risk. Further, it is shown that IMM has someimportant advantages over CEM, especially when it comes to model connection withreality. Finally, some possible future work to be done within the topic area is suggested.

Before the global financial crisis around 2008, the priority of the credit margin was comparatively low and was not taken into consideration as much as today. Many actors believed that credit risk could be neglected at various valuations. Due to that a lot of parties went bankrupt because of the low priorities. Today, this is a natural component in the financial market due to the capital regulation CRR and the Capital requirement directives (CRD IV), which are directly related to Basel III. In this thesis the authors have created a Credit valuation adjustment model, or a CVA-model, on behalf of the consulting firm AGL who want to use it in negotiations of interest rate swap with financial institutions. Factors as expected exposure, loss given default and probability of default are estimated in order to estimate a fair value for CVA. As a final product, the authors have created a model in VBA that can price CVA for individual contracts. This model is then evaluated and a sensitivity analysis is performed to see what impact credit rating and maturity have on the result.

Since the default of Lehman Brothers in 2008, it has become increasingly important to measure, manage and price the default risk in financial derivatives. Default risk in financial derivatives is referred to as counterparty credit risk (CCR). The price of CCR is captured in Credit Valuation Adjustment (CVA). This adjustment should in principle always enter the valuation of a derivative traded over-the-counter (OTC). To calculate CVA, one needs to know the probability of default of the counterparty. Since CVA is a price, what one needs is the risk-neutral probability of default. The typical way of obtaining risk-neutral default probabilities is to build credit curves calibrated using Credit Default Swaps (CDS). However, for a majority of a bank's counterparties there are no CDSs liquidly traded. This constitutes a major challenge. How does one model the risk-neutral default probability in the absence of observable CDS spreads? A number of methods for constructing proxy credit curves have been proposed previously. A particularly popular choice is the so-called Nomura (or cross-section) model. In studying this model, we find some weaknesses, which in some instances lead to degenerate proxy credit curves. In this thesis we propose an altered model, where the modelling quantity is changed from the CDS spread to the hazard rate. This ensures that the obtained proxy curves are valid by construction. We find that in practice, the Nomura model in many cases gives degenerate proxy credit curves. We find no such issues for the altered model. In some cases, we see that the differences between the models are minor. The conclusion is that the altered model is a better choice since it is theoretically sound and robust.<br>Sedan Lehman Brothers konkurs 2008 har det blivit allt viktigare att mäta, hantera och prissätta kreditrisken i finansiella derivat. Kreditrisk i finansiella derivat benämns ofta motpartsrisk (CCR). Priset på motpartsrisk fångas i kreditvärderingsjustering (CVA). Denna justering bör i princip alltid ingå i värderingen av ett derivat som handlas över disk (eng. over-the-counter, OTC). För att beräkna CVA behöver man veta sannolikheten för fallissemang (konkurs) hos motparten. Eftersom CVA är ett pris, behöver man den riskneutrala sannolikheten för fallissemang. Det typiska tillvägagångsättet för att erhålla riskneutrala sannolikheter är att bygga kreditkurvor kalibrerade med hjälp av kreditswappar (CDS:er). För en majoritet av en banks motparter finns emellertid ingen likvid handel i CDS:er. Detta utgör en stor utmaning. Hur ska man modellera riskneutrala fallissemangssannolikheter vid avsaknad av observerbara CDS-spreadar? Ett antal metoder för att konstruera proxykreditkurvor har föreslagits tidigare. Ett särskilt populärt val är den så kallade Nomura- (eller cross-section) modellen. När vi studerar denna modell hittar vi ett par svagheter, som i vissa fall leder till degenererade proxykreditkurvor. I den här uppsatsen föreslår vi en förändrad modell, där den modellerade kvantiteten byts från CDS-spreaden till riskfrekvensen (eng. hazard rate). Därmed säkerställs att de erhållna proxykurvorna är giltiga, per konstruktion. Vi finner att Nomura-modellen i praktiken i många fall ger degenererade proxykreditkurvor. Vi finner inga sådana problem för den förändrade modellen. I andra fall ser vi att skillnaderna mellan modellerna är små. Slutsatsen är att den förändrade modellen är ett bättre val eftersom den är teoretiskt sund och robust.

Submitted by Eitan Chernizon (eitan.chernizon@sgcib.com) on 2013-02-15T17:46:24Z No. of bitstreams: 1 MODELAGEM DA DEPENDÊNCIA ENTRE FATORES DE CRÉDITO E MERCADO.pdf: 1474762 bytes, checksum: 19b13b065762c89e556619042eaf016d (MD5)<br>Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-02-18T12:58:52Z (GMT) No. of bitstreams: 1 MODELAGEM DA DEPENDÊNCIA ENTRE FATORES DE CRÉDITO E MERCADO.pdf: 1474762 bytes, checksum: 19b13b065762c89e556619042eaf016d (MD5)<br>Made available in DSpace on 2013-02-18T13:20:44Z (GMT). No. of bitstreams: 1 MODELAGEM DA DEPENDÊNCIA ENTRE FATORES DE CRÉDITO E MERCADO.pdf: 1474762 bytes, checksum: 19b13b065762c89e556619042eaf016d (MD5) Previous issue date: 2013-02-01<br>Apesar das recentes turbulências nos mercados, a utilização de derivativos negociados fora de uma câmara de compensação tem apresentado rápido crescimento, constituindo um dos maiores componentes do mercado financeiro global. A correta inclusão da estrutura de dependência entre fatores de crédito e mercado é de suma importância no apreçamento do risco de crédito adjacente a exposições geradas por derivativos. Este é o apreçamento, envolvendo simulações de Monte Carlo, feito por uma instituição negociante para determinar a redução no valor do seu portfólio de derivativos devido a possibilidade de falência da contraparte. Este trabalho apresenta um modelo com abordagem paramétrica para lidar com a estrutura de dependência, intuitivo e de fácil implementação. Ao mesmo tempo, os números são contrastados com os resultados obtidos através de uma abordagem neutra ao risco para um portfólio replicante, sob o mesmo processo estocástico. O modelo é aplicado sobre um contrato a termo de câmbio, e diferentes cópulas e fatores de correlação são utilizados no processo estocástico.<br>Despite recent turmoils, the use of derivatives traded outside of a clearinghouse has shown rapid growth and is a major component of the global financial market. The correct inclusion of the dependence structure between market and credit factors is of high importance in the pricing of credit risk exposures generated by the adjacent derivatives. This pricing, involving Monte Carlo simulations, is done by a dealer to determine the reduction in the value of its derivatives portfolio because of the bankruptcy of the counterparty. This paper presents a model with parametric approach to deal with the dependence structure, intuitive and easily implemented. Meanwhile, the numbers are contrasted with results obtained using a risk neutral approach for a replicating portfolio under the same stochastic process. The model is applied on a forward exchange contract, and different copulas and correlation factors are used in the stochastic process.

Nous entamons ce rapport de thèse par l’évaluation de l’espérance espérée qui représente une des composantes majeures des ajustements XVA. Sous l’hypothèse d’indépendance entre l’exposition et les coûts de financement et de crédit, nous dérivons dans le chapitre 3 une représentation nouvelle de l’exposition espérée comme la solution d’une équation différentielle ordinaire par rapport au temps d’observation du défaut. Nous nous basons, pour le cas unidimensionnel, sur des arguments similaires à ceux de la volatilité locale de Dupire. Et pour le cas multidimensionnel, nous nous référons à la formule de la Co-aire. Cette représentation permet d’expliciter l’impact de la volatilité sur l’exposition espérée : Cette valeur temps fait intervenir la volatilité des sous-jacents ainsi que la sensibilité au premier ordre du prix, évalués sur un ensemble fini de points. Malgré des limitations numériques, cette méthode est une approche précise et rapide pour la valorisation de la XVA unitaire en dimension 1 et 2.Les chapitres suivants sont dédiés aux aspects du risque de corrélations entre les enveloppes d’expositions et les coûts XVA. Nous présentons une modélisation du risque général de corrélation à travers une diffusion stochastique multivariée, comprenant à la fois les sous-jacents des dérivés et les intensités de défaut. Dans ce cadre, nous exposons une nouvelle approche de valorisation par développements asymptotiques, telle que le prix d’un ajustement XVA correspond au prix de l’ajustement à corrélation nulle, auquel s’ajoute une somme explicite de termes correctifs. Le chapitre 4 est consacré à la dérivation technique et à l’étude de l’erreur numérique dans le cadre de la valorisation de dérivés contingents au défaut. La qualité des approximations numériques dépend uniquement de la régularité du processus de diffusion de l’intensité de crédit, et elle est indépendante de la régularité de la fonction payoff. Les formules de valorisation pour CVA et FVA sont présentées dans le chapitre 5. Une généralisation des développements asymptotiques pour le cadre bilatéral de défaut est adressée dans le chapitre 6.Nous terminons ce mémoire en abordant un cas du risque spécifique de corrélation lié aux contrats de migration de rating. Au-delà des formules de valorisation, notre contribution consiste à présenter une approche robuste pour la construction et la calibration d’un modèle de transition de ratings consistant avec les probabilités de défaut implicites de marché<br>The point of departure of this thesis is the valuation of the expected exposure which represents one of the major components of XVA adjustments. Under independence assumptions with credit and funding costs, we derive in Chapter 3 a new representation of the expected exposure as the solution of an ordinary differential equation w.r.t the default time variable. We rely on PDE arguments in the spirit of Dupire’s local volatility equation for the one dimensional problem. The multidimensional extension is addressed using the co-area formula. This forward representation gives an explicit expression of the exposure’s time value, involving the local volatility of the underlying diffusion process and the first order Greek delta, both evaluated only on finite set of points. From a numerical perspective, dimensionality is the main limitation of this approach. Though, we highlight high accuracy and time efficiency for standalone calculations in dimensions 1 and 2.The remaining chapters are dedicated to aspects of the correlation risk between the exposure and XVA costs. We start with the general correlation risk which is classically modeled in a joint diffusion process for market variables and the credit/funding spreads. We present a novel approach based on asymptotic expansions in a way that the price of an XVA adjustment with correlation risk is given by the classical correlation-free adjustment to which is added a sum of explicit correction terms depending on the exposure Greeks. Chapter 4 is consecrated to the technical derivation and error analysis of the expansion formulas in the context of pricing credit contingent derivatives. The accuracy of the valuation approach is independent of the smoothness of the payoff function, but it is related to the regularity of the credit intensity model. This finding is of special interest for pricing in a real financial context. Pricing formulas for CVA and FVA adjustments are derived in Chapter 5, along with numerical experiments. A generalization of the asymptotic expansions to a bilateral default risk setting is addressed in Chapter 6.Our thesis ends by tackling the problem of modeling the specific Right-Way Risk induced by rating trigger events within the collateral agreements. Our major contribution is the calibration of a rating transition model to market implied default probabilities

On définit le risque de contrepartie comme le risque de détérioration de la qualité de crédit entrainant une incapacité de la contrepartie à remplir ses obligations contractuelles. De nos jours, ce risque ne se limite plus aux entreprises, mais s'est également étendu aux banques et autres institutions financières. Par conséquent, toute entité participant aux marchés dérivés OTC est exposée à ce risque. La «Credit Value Adjustment» (CVA) est la valeur de marché du risque de contrepartie. En raison de sa complexité, la mise en œuvre de la CVA demeure l'un des plus grands défis auxquels les banques font face depuis la dernière crise. Pour la plupart d’entre elles, sa mise en production nécessite des changements majeurs de l’infrastructure actuelle. En outre, le régulateur, dont le but est de renforcer la stabilité des marchés financiers, s’est également intéressé à la CVA en introduisant une nouvelle charge en capital liée au risque de contrepartie. Les contributions de notre thèse à la littérature existante sur le sujet se trouvent essentiellement aux chapitres 2, 3 et 4 du manuscrit. Dans les chapitres 2 et 3, nous proposons deux méthodes innovatrices pour le calcul de la CVA. Le chapitre 4 est, quant à lui, entièrement dédié à l’étude de la charge en capital réglementaire sous la régulation FRTB-CVA<br>Counterparty risk is defined as the risk of credit worthiness deterioration, making the counterparty unable to meet its contractual obligations. Nowadays, this risk is no longer confined to corporate clients but has spread out to other banks and financial institutions. As a consequence, any firm participating in the over-the-counter (OTC) derivatives market is exposed to this risk. Credit Value Adjustment (CVA) is the market value of counterparty credit risk. Implementation of CVA still remains one of the biggest challenges banks face since the last financial crisis, due to its complexity and cost of implementation. For most banks, pricing the whole CVA book requires major changes on the infrastructure they currently have. Furthermore, regulatory responses to the last financial turmoil aimed at strengthening the financial system by introducing new capital requirements. The Basel III regulatory standard was developed in this respect, prescribing an additional capital charge to cover CVA losses.Our contributions to the relevant literature are chapters 2, 3 and 4. In chapters 2 and 3, we propose two innovative approaches to compute CVA that allow a huge reduction in computational costs. Chapter 4 is devoted to the study of the CVA capital charge under the new FRTB-CVA regulation

In the thesis we analyse changes in derivatives valuation after the financial crisis and their impact on behaviour of financial institutions. We focus mainly on the changes related to counterparty credit risk and valuation adjustments. We describe in economical terms the relationship between counterparty credit risk and traditional credit risk, we also introduce management and modelling of this risk. In second part of the study we analyse the regulatory framework, in particular new capital requirement and mandatory central clearing of OTC derivatives. We discuss inconsistencies between regulatory and internal approaches to the counterparty risk measurement and also significant systemic risk connected to central counterparties. Finally we investigate the impact of changes in derivatives valuation on banks in both the EU and the Czech Republic. Specifically we are interested in optimal approach to entering into derivative trade.

Mestrado em Matemática Financeira<br>O Acordo de Basileia III prevê, além do aumento da qualidade e do nível de requisitos de capital, a revisão de métricas com vista a melhorar o nível de exposição ao Risco de Crédito de Contraparte (RCC). O objetivo deste trabalho é desenvolver metodologias para mensurar a exposição esperada ao RCC de derivados negociados fora de bolsa (Over-The-Counter – OTC), que consistem em contratos ligados ao futuro valor, ou situação, dos instrumentos subjacentes aos quais se referem. Neste contexto, a inovação do novo Acordo refere-se à introdução de um encargo de capital para cobrir o risco de perdas do valor de mercado do RCC esperado para os instrumentos derivados OTC. Estas potenciais perdas são denominadas Ajustamentos de Avaliação de Crédito (Credit Valuation Adjustment – CVA) e podem ser calculadas por diferentes métodos, dependendo para tal da aprovação do Banco de Portugal. Nas ilustrações, recorre-se frequentemente a Interest Rate Swaps, por serem o instrumento financeiro mais transacionado.<br>Basel III provides an increase of the quality and level of capital requirements, and also it presents a review of the metrics in order to improve the level of exposure to the Counterparty Credit Risk (CCR). In this framework I will develop methodologies to measure the expected exposure to the CCR of Over-the-Counter derivatives, which are contracts that are linked to the future value of the underlying instruments or situation to which they refer. In this context, Basel III innovation reports to the introduction of a capital charge to cover the risk of loss of the CCR Mark-to-Market expected value for OTC derivatives. These potential losses are called Credit Valuation Adjustments (CVA) and may be calculated using different methods, which must be approved by Banco de Portugal. There is a recurrent use of Interest Rate Swaps when providing examples, given that they are the most traded financial instruments.

L'objectif de cette thèse est de fournir à la banque Audi un outil à jour sur les façons de calculer le capital requis par Bâle pour certains risques financiers présents dans le portefeuille de la banque. La régulation internationale est en développement continu : des nouvelles approches sont proposées afin de couvrir au mieux les risques du marché et du secteur bancaire. Les crises financières récentes étaient à la base de ces réformes. De plus, la Banque Audi opère sur des marchés qui présentent des caractères spécifiques qu'il faut prendre en considération lors du calcul du capital requis. Cette thèse se concentre sur le risque de taux d'intérêt dans le livre de négociation de la banque, le risque de contrepartie et précisément l'ajustement d'évaluation de crédit tout en incorporant l'impact de la corrélation entre la qualité du crédit de la contrepartie et l'exposition prévue envers cette même contrepartie. La première partie de cette thèse traite de la nouvelle méthodologie suggérée par Bâle sur le Trading Book : Fundamental Review of the Trading Book. Le risque de taux d'intérêt est particulièrement analysé en utilisant la méthode standard, Sensitivity Based Approach (SBA), et des méthodes plus 'traditionnelles' de valeur à risque tout en utilisant différents modèles tels que Generalized Auto Regressive Conditional Heteroscedasticity (GARCH), l'Analyse en Composantes Principales (ACP), l'Analyse en composantes indépendantes (ACI) et la version dynamique du modèle de taux de Nelson Siegel (DNS). Une application sur des portefeuilles d'obligations zéro coupons de différentes devises permet d'identifier la diversification des résultats entre les marchés stables européens (comme la France), moins stables (exemple Etats-Unis) et les marchés émergents (tel la Turquie). La deuxième partie est consacrée au risque de Contrepartie. Récemment, un nouveau capital est requis par les normes de Bâle afin de couvrir ce genre de risque. En 2014, la méthode est publiée : Standardized Approach for Counterparty Credit Risk (SA-CCR). On applique cette méthode sur différents types de produits dérivés afin de comparer le capital demandé par cette approche à celui obtenu par les modèles internes. Les modèles internes incorporent les estimations historiques ainsi que les projections futures du marché tout en se basant sur des modèles bien connus tels que Vasicek et GARCH. Plusieurs structures de hedging sont mises en place afin de mesurer l'impact de chacune sur les deux montants de capitaux requis (sous la méthode standard ou l'IMM). L'effet sur des produits en EUR et USD reflété que le modèle interne demande 80% du capital standard quand aucune stratégie de hedging n'est mise en place. Par contre, le hedging semble être beaucoup plus favorisé par le modèle standard que le modèle interne. La troisième partie est toujours sur le risque de Contrepartie, mais se focalise sur l'ajustement d'´évaluation de crédit (CVA). Ce sujet ne faisait pas partie des capitaux requis sauf récemment. A cause de son grand impact durant les récentes crises financières. Dès lors, si une opération avec des produits dérivés ne passe pas par une central clearing houses, un capital pour le CVA est requis. Dans ce travail, on détaille les méthodes acceptées par Bâle afin de calculer ces capitaux et on les compare entre elles. La comparaison se fait en se basant sur des portefeuilles de swap de taux d'intérêts avec, comme contreparties, différents pays d'Investment Grade. Cet article incorpore en plus l'impact de la corrélation entre la détérioration de la qualité de la contrepartie et l'augmentation de l'exposition prévue avec cette contrepartie connue sous le nom de WrongWay Risk : des modèles de correction d'erreurs (ECM) sont mis en place afin de déterminer ce lien. Les résultats permettent de montrer l'importance d'utiliser les CDS des contreparties et non de se limiter à leur note (Investment Grade ou pas)<br>This thesis aims at providing Bank Audi with an updated tool to understand and investigate in given risk types encountered in their portfolios and the way Basel suggests computing their capital charges. International regulator is constantly changing and modifying previously used approaches to enhance the reflection of the market and banking sector risks. The recent financial crisis played a major role in these reforms, in addition the situation of Bank Audi and the markets it is operating in, represent certain specifications that should be accounted for. The work handles interest rate risk in the trading book, Counterparty Credit Risk faced with derivatives along a closer look on the Credit Valuation Adjustment topic and the incorporation of Wrong Way Risk. The first part discusses the new Fundamental Review of the Trading Book: focusing on the general interest rate risk factor, the paper compared Basel’s Sensitivity Based Approach (SBA) capital charge to more traditional approaches of VaR using several models such as Generalized Auto Regressive Conditional Heteroscedasticity (GARCH), Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Dynamic Nelson Siegel. Application on portfolios with zero coupon bonds of different sovereigns revealed the divergence in results between stable markets (such as France and Germany), less stable (such as the USA) and emergent markets (such as Turkey). The second part is dedicated to the Counterparty Credit Risk. A new capital charge methodology was proposed by Basel and set as a standard rule in 2014: the Standardized Approach for Counterparty Credit Risk (SA-CCR). Applying this approach on different derivatives portfolios, we compared it to internal models. The internal methodologies incorporated historical estimations and future projections based on Vasicek and GARCH models. Different hedging cases were investigated on EUR and USD portfolios. The impact of each hedging technique and the difference between IMM and the standardized methods were highlighted in this work: without hedging, the internal approach amends 80% of the standardized capital whereas, in general, the hedging is encouraged more under the standardized approach relatively to its capital reduction under the internal model. The third part remains a part of the Counterparty Credit Risk however, the main focus in this work is the Credit Valuation Adjustment. This topic was neglected in terms of capital charge earlier but due to its important impact is now incorporated as a capital charge amended when no central clearing is put in place when dealing with derivatives. We focus on the regulatory approaches of capital computation, comparing both accepted approaches based on portfolios of interest rate swaps held with investment grade sovereigns. An incorporation of the Wrong Way Risk is another addition in this work: using Error Correction Models we were able to reflect the impact of the correlation between the exposure and the credit quality of the investment grade sovereign we are dealing with. Based on such results, a suggestion of a re-calibrated standardized approach is in place to encourage the use of the CDS as an indicator of the credit quality of the counterparty and not its grade (investment or not) as followed by the new Basel regulations

The credit valuation adjustment (CVA) on an over-the-counter derivative transaction is the price of the risk associated with the potential default of the counterparties to the trade. This dissertation provides an introduction to the concept of CVA, beginning with the required backdrop of counterparty risk and the basics of default risk modelling. Right and wrong way risks are central themes of the dissertation. A model for the pricing of both the unilateral and the bilateral CVA on a credit default swap (CDS) is implemented. Each step of this process is explained thoroughly. Results are reported and discussed for a range of parameters. The trends observed in the CDS CVA numbers produced by the model are all justified and the right and wrong way nature of the exposures captured. In addition, the convergence and stability of the numerical schemes utilised are shown to be appropriate. A case study, in which the model is applied to a set of market scenarios, concludes the dissertation. Since the field is far from established, a number of areas are suggested for further research. Copyright<br>Dissertation (MSc)--University of Pretoria, 2012.<br>Mathematics and Applied Mathematics<br>unrestricted

The chapter discusses credit value adjustment (CVA) under Basel 2.5 and Basel 3. CVA is an adjustment to the fair value (or price) of derivative instruments to account for counterparty credit risk (CCR). Thus, CVA is commonly viewed as the price of CCR. The purpose of the CVA capital charge is to capitalize the risk of future changes in CVA. For most exposures, at any given time the market credit spread on the relevant counterparty is good proxy for the CVA applicable to the exposure, but the regulatory calculations involved reflect a number of factors as well as this particular input.

The elemental regime on bank capital for derivatives encompassed the credit valuation adjustment (CVA), the leverage ratio, and bank exposures to CCPs. Like for other parts of Basel III, the US and the UK were pace-setters internationally, promoting relatively precise, stringent, and consistent rules. The EU agreed on the need for higher capital requirements, but worried about negative implications for the provision of credit to the real economy. Networks of regulators were instrumental in furthering agreement amongst and within jurisdictions. They also fostered rules consistency through formal and informal coordination tools amongst international standard-setting bodies. The financial industry mobilized in order to reduce the precision and stringency of capital requirements, pointing out the need to consider capital reforms in conjunction with other post-crisis standards, notably, margins.