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Author: Darrell Duffie Publisher: OUP Oxford ISBN: 019150047X Category : Business & Economics Languages : en Pages : 122
Book Description
This book, based on the author's Clarendon Lectures in Finance, examines the empirical behaviour of corporate default risk. A new and unified statistical methodology for default prediction, based on stochastic intensity modeling, is explained and implemented with data on U.S. public corporations since 1980. Special attention is given to the measurement of correlation of default risk across firms. The underlying work was developed in a series of collaborations over roughly the past decade with Sanjiv Das, Andreas Eckner, Guillaume Horel, Nikunj Kapadia, Leandro Saita, and Ke Wang. Where possible, the content based on methodology has been separated from the substantive empirical findings, in order to provide access to the latter for those less focused on the mathematical foundations. A key finding is that corporate defaults are more clustered in time than would be suggested by their exposure to observable common or correlated risk factors. The methodology allows for hidden sources of default correlation, which are particularly important to include when estimating the likelihood that a portfolio of corporate loans will suffer large default losses. The data also reveal that a substantial amount of power for predicting the default of a corporation can be obtained from the firm's "distance to default," a volatility-adjusted measure of leverage that is the basis of the theoretical models of corporate debt pricing of Black, Scholes, and Merton. The findings are particularly relevant in the aftermath of the financial crisis, which revealed a lack of attention to the proper modelling of correlation of default risk across firms.
Author: Darrell Duffie Publisher: OUP Oxford ISBN: 019150047X Category : Business & Economics Languages : en Pages : 122
Book Description
This book, based on the author's Clarendon Lectures in Finance, examines the empirical behaviour of corporate default risk. A new and unified statistical methodology for default prediction, based on stochastic intensity modeling, is explained and implemented with data on U.S. public corporations since 1980. Special attention is given to the measurement of correlation of default risk across firms. The underlying work was developed in a series of collaborations over roughly the past decade with Sanjiv Das, Andreas Eckner, Guillaume Horel, Nikunj Kapadia, Leandro Saita, and Ke Wang. Where possible, the content based on methodology has been separated from the substantive empirical findings, in order to provide access to the latter for those less focused on the mathematical foundations. A key finding is that corporate defaults are more clustered in time than would be suggested by their exposure to observable common or correlated risk factors. The methodology allows for hidden sources of default correlation, which are particularly important to include when estimating the likelihood that a portfolio of corporate loans will suffer large default losses. The data also reveal that a substantial amount of power for predicting the default of a corporation can be obtained from the firm's "distance to default," a volatility-adjusted measure of leverage that is the basis of the theoretical models of corporate debt pricing of Black, Scholes, and Merton. The findings are particularly relevant in the aftermath of the financial crisis, which revealed a lack of attention to the proper modelling of correlation of default risk across firms.
Author: Sanjiv Ranjan Das Publisher: ISBN: Category : Languages : en Pages : 45
Book Description
Using a comprehensive and unique data set from Moody's, we examine correlations between default risk for over 7,000 U.S. public firms. This is the first paper to empirically document the correlation structure both in the time-series and in the cross-section across almost all U.S. non-financial firms. We find that default probabilities of issuers vary over time, and are positively correlated. Moreover, the correlations across firms also vary over time systematically, in a manner that is related to an economy-wide level of default risk. Joint default risk increases as the default risk in the economy increases. Our results also suggest that the magnitude of joint default depends on the quality of issuers; highest quality issuers have higher default correlations than medium grade firms.
Author: Sanjiv Ranjan Das Publisher: ISBN: Category : Languages : en Pages : 37
Book Description
Modeling correlated default risk is a new phenomenon currently sweeping through the credit markets. In this paper, we develop a methodology to model, simulate and assess the joint default process of hundreds of issuers. Our study is based on a data set of default probabilities supplied by Moody's Risk Management Services. We undertake an empirical examination of the joint stochastic process of default risk over the period of 1987-2000 using copula functions. To determine the appropriate choice of the joint default process, we propose a new metric. This metric accounts for different aspects of default correlation, namely (i) level, (ii) asymmetry and (iii) tail-dependence and extreme behavior. Our model, based on estimating a joint system of over 600 issuers, is designed to replicate the empirical joint distribution of defaults. A comparison of a jump model and a regime-switching model shows that the latter provides a better representation of the properties of correlated default. We also find that the skewed double-exponential distribution is the best choice for the marginal distribution of each issuer's hazard rate process, and combines well with the normal, Gumbel, Clayton and student's t copulas in the joint dependence relationship amongst issuers. As a complement to the methodological innovation, we show that (a) appropriate choices of marginal distributions and copulas are essential in modeling correlated default, (b) accounting for regimes is an important aspect of joint specifications of default risk, and (c) misspecification of credit portfolio risk can occur easily if joint distributions are inappropriately chosen. The empirical evidence suggests that improvements are indeed possible over the standard Gaussian copula used in practice.
Author: Siamak Javadi Publisher: ISBN: Category : Languages : en Pages :
Book Description
Extracting information from daily CDS spreads, we propose a measure of correlated default risk, which we show is a meaningful predictor of bankruptcy clusters. Focusing on U.S. corporate bonds, we also find that our measure of correlated default risk is more pronounced and commands a higher premium during periods of financial distress and for speculative issues. For instance, we find that after controlling for other known determinants of bond pricing, a 0.5 increase in aggregate correlated default risk is associated with a 13-bps increase in credit spreads, and elevates to a 22-bps premium for speculative issues and to a 17-bps premium during periods of financial distress. Overall, our paper provides compelling evidence as to the efficacy of our measure in capturing correlations in the likelihood of default over time, and has important implications for future work in asset allocation and fixed-income pricing.
Author: Nikola A. Tarashev Publisher: ISBN: Category : Languages : en Pages :
Book Description
In order to analyze the pricing of portfolio credit risk - as revealed by tranche spreads of a popular credit default swap (CDS) index - we extract risk-neutral probabilities of default (PDs) and physical asset return correlations from single-name CDS spreads. The time profile and overall level of index spreads validate our PD measures. At the same time, the physical asset return correlations are too low to account for the spreads of index tranches and, thus, point to a large correlation risk premium. This premium, which covaries negatively with current realized correlations and positively with future realized correlations, sheds light on market perceptions of and attitude towards correlation risk.Das Portfoliokreditrisiko setzt sich aus drei Hauptkomponenten zusammen: der Ausfallwahrscheinlichkeit (probability of default, PD), der Verlustquote (loss given default, LGD) und der Wahrscheinlichkeitsverteilung für gemeinsame Ausfälle. Mit der rasanten Entwicklung innovativer Produkte im Bereich der strukturierten Finanzierung ist die Bedeutung der dritten Komponente zusehends gestiegen. Allerdings herrscht keine Einigkeit darüber, wie die Marktteilnehmer diese schätzen. Im vorliegenden Arbeitspapier schlagen wir zunächst einen auf CDSMarktdaten beruhenden Ansatz zur Ableitung der Wahrscheinlichkeitsverteilung für gemeinsame Ausfälle vor. Mit diesem Ansatz werden risikoneutrale PDs und physische Asset-Return-Korrelationen aus der Höhe der Preise und dem Gleichlauf (Co-movement) von Single-name-CDS-Spreads abgeleitet. Anschließend benutzen wir diese Schätzungen in einer konkreten Anwendung unseres Ansatzes zur Berechnung von Prognosen für Tranchenspreads eines bekannten CDS-Index (Dow Jones CDX North America Investment Grade Index) und vergleichen diese mit empirischen Spreads am CDS-Indexmarkt.
Author: Xiaowei Ding Publisher: ISBN: Category : Languages : en Pages :
Book Description
Credit risk pervades all nancial transactions. The credit crisis has indicated the need for quantitative models for valuation, hedging, rating, risk management and regulatory monitoring of credit risk. A credit investor such as a bank granting loans to rms or an asset manager buying corporate bonds is exposed to correlated default risk. A portfolio credit derivative is a nancial security that allows the investor to transfer this risk to the credit market. In the rst part of this thesis, we study the valuation and risk analysis of portfolio derivatives. To capture the complex economic phenomena that drive the pricing of these securities, we introduce a time-changed birth process as a probabilistic model of correlated event timing. The self-exciting property of a time-changed birth process captures the feedback from events that is often observed in credit markets. The stochastic variation of arrival rates between events captures the exposure of rms to common economic risk factors. We derive a closed-form expression for the distribution of a time-changed birth process, and develop analytically tractable pricing relations for a range of portfolio derivatives valuation problems. We illustrate our results by calibrating a tranche forward and option pricer to market rates of index and tranche swaps. A loss point process model such as a time-changed birth process is speci ed without reference to the portfolio constituents. It is silent about the portfolio constituent risks, and cannot be used to address applications that are based on the relationship between portfolio and component risks, for example constituent risk hedging. The second part of this thesis develops a method that extends the reach of these models to the constituents. We use random thinning to decompose the portfolio intensity into the sum of the constituent intensities. We show that a thinning process, which allocates the portfolio intensity to constituents, uniquely exists and is a probabilistic model for the next-to-default. We derive a formula for the constituent default probability in terms of the thinning process and the portfolio intensity, and develop a semi-analytical transform approach to evaluate it. The formula leads to a calibration scheme for the thinning processes, and an estimation scheme for constituent hedge sensitivities. An empirical analysis for September 2008 shows that the constituent hedges generated by our method outperform the hedges prescribed by the Gaussian copula model, which is widely used in practice.
Author: Kay Giesecke Publisher: ISBN: Category : Languages : en Pages : 31
Book Description
Using data on corporate default experience in the U.S. and market rates of CDX index and tranche swaps of various maturities, we estimate reduced-form models of correlated default timing in the CDX High Yield and Investment Grade portfolios under actual and risk-neutral probabilities. The striking contrast between the estimated processes followed by the actual and risk-neutral arrival intensities of defaults, and between the parameters governing the actual and risk-neutral dynamics of the risk-neutral intensities, indicates the presence of substantial default risk premia in CDX swap market rates. The effects of risk premia on swap rates covary strongly across maturities, and depend on general stock market volatility and several measures of credit spreads. Large moves in the effects of these premia on swap rates have natural interpretations in terms of economic and financial market developments during the sample period, April 2004 to October 2007. Our results suggest that a large portion of the movements in CDX swap market rates observed during the sample period may be caused by changing attitudes towards correlated default risk rather than changes in the economic factors affecting the actual risk of clustered defaults, which ultimately governs swap payoffs.
Author: Darrell Duffie
Author: Darrell Duffie
Author: Sanjiv Ranjan Das
Author: Nikola A. Tarashev
Author: Ismail Onur Filiz
Author: Sanjiv Ranjan Das
Author: Siamak Javadi
Author: Nikola A. Tarashev
Author: Xiaowei Ding
Author: Chunsheng Zhou
Author: Kay Giesecke