A value at risk analysis of credit default swaps

We study the risk of holding credit default swaps (CDS) in the trading book. In particular, we compare the Value at Risk (VaR) of a CDS position to the VaR for investing in the respective firm's equity. Our sample consists of CDS – stock price pairs for 86 actively traded firms over the period from March 2003 to October 2006. We find that the VaR for a stock is usually far larger than the VaR for a position in the same firm's CDS. However, the distance between CDS VaR and equity VaR is markedly smaller for firms with high credit risk. The distance also declines for longer holding periods. We also observe a positive correlation between CDS and equity VaR. -- Kreditderivate wie Credit Default Swaps (CDS) haben in den letzten Jahren den Handel mit Kreditrisiko signifikant vereinfacht. Ein standardisiertes Kontrakt-Design, niedrige Transaktionskosten und eine große and heterogene Gruppe von Marktteilnehmern haben dazu beigetragen, dass CDS die Benchmark - Funktion für die Preisbestimmung im Markt für Unternehmens-Verschuldung erreichen. Heute ist der CDS das am meisten gehandelte Kreditderivat. Wir analysieren das Risiko von CDS, die im Handelsbuch gehalten werden. Wir vergleichen den Value at Risk (VaR) der CDS Position mit dem VaR für eine Position in der Aktie der gleichen Firma. Unsere Stichprobe umfasst CDS ? Aktien Paare für 86 aktiv gehandelte Firmen im Zeitraum von März 2003 bis Oktober 2006. Wir finden, dass der VaR der Aktie meistens den VaR der CDS - Position deutlich übersteigt. Die Distanz zwischen dem CDS - VaR und dem Aktien - VaR ist jedoch bei Firmen mit hohem Kreditrisiko deutlich geringer. Die Distanz sinkt auch bei längeren Haltedauern. Wir beobachten weiter eine positive Korrelation zwischen dem CDS - VaR und dem Aktien - VaR.Credit default swap,Value at Risk,Capital structure arbitrage

An analysis of euro area sovereign CDS and their relation with government bonds

This paper studies the relative pricing of euro area sovereign CDS and the underlying government bonds. Our sample comprises weekly CDS and bond spreads of ten euro area countries for the period from January 2006 to June 2010. We first compare the determinants of CDS spreads and bond spreads and test how the crisis has affected market pricing. Then we analyse the ‘basis’ between CDS spreads and bond spreads and which factors drive pricing differences between the two markets. Our first main finding is that the recent repricing of sovereign credit risk in the CDS market seems mostly due to common factors. Second, since September 2008, CDS spreads have on average exceeded bond spreads, which may have been due to ‘flight to liquidity’ effects and limits to arbitrage. Third, since September 2008, market integration for bonds and CDS varies across countries: In half of the sample countries, price discovery takes place in the CDS market and in the other half, price discovery is observed in the bond market. JEL Classification: G00, G01CDS, Credit Spread, financial crisis, Government bond, limits to arbitrage

Modelling the implied probability of stock market movements

In this paper we study risk-neutral densities (RNDs) for the German stock market. The use of option prices allows us to quantify the risk-neutral probabilities of various levels of the DAX index. For the period from December 1995 to November 2001, we implement the mixture of log-normals model and a volatility-smoothing method. We discuss the time series behaviour of the implied PDFs and we examine the relations between the moments and observable factors such as macroeconomic variables, the US stock markets and credit risk. We find that the risk-neutral densities exhibit pronounced negative skewness. Our second main observation is a significant spillover of volatility, as the implied volatility and kurtosis of the DAX RND are mostly driven by the volatility of US stock prices. JEL Classification: C22, C51, G13, G15Option prices, risk-neutral density, spillover, Volatility

A value at risk analysis of cedit default swaps

We investigate the risk of holding credit default swaps(CDS) in the trading book and compare the Value at Risk (VaR) of a CDS position to the VaR for investing in the respective firm’s equity using a sample of CDS – stock price pairs for 86 actively traded firms over the period from March 2003 to October 2006. We find that the VaR for a stock is usually far larger than the VaR for a position in the same firm’s CDS. However, the ratio between CDS and equity VaR is markedly smaller for firms with high credit risk. The ratio also declines for longer holding periods. We also observe a positive correlation between CDS and equity VaR. Panel regressions suggest that our findings are consistent with qualitative predictions of the Merton (1974) model. JEL Classification: E43, G12, G13credit default swap, Structural Credit Risk Models, Value at Risk

How has CDO market pricing changed during the turmoil? Evidence from CDS index tranches

This paper applies regression analysis to investigate the fundamental factors of the variation of CDS index tranches. The sample comprises daily data on the tranche premia of the European iTraxx and North American CDX index from the start of the market in summer 2004 to January 2008. I estimate the relationship between tranche premia and market-based measures of credit risk, liquidity risk and interest rate risk. In this context, I analyse how the set of explanatory factors has changed since the start of the credit market turmoil in 2007. Overall, I find that pricing of CDX and iTraxx tranches differs although the specifications of the two contracts are very similar. Since July 2007, tranche investors appear to have repriced CDX contracts to a larger extent than iTraxx contracts. Credit risk and liquidity factors are priced in almost all tranches with liquidity risk playing a larger role since the start of the turmoil. JEL Classification: E43, G12, G13, G14Collateralised Debt Obligation, Correlation, Credit derivative, Credit Spread

Asset correlations and credit portfolio risk: an empirical analysis

In credit risk modelling, the correlation of unobservable asset returns is a crucial component for the measurement of portfolio risk. In this paper, we estimate asset correlations from monthly time series of Moody's KMV asset values for around 2,000 European firms from 1996 to 2004. We compare correlation and value-atrisk (VaR) estimates in a one-factor or market model and a multi-factor or sector model. Our main finding is a complex interaction of credit risk correlations and default probabilities affecting total credit portfolio risk. Differentiation between industry sectors when using the sector model instead of the market model has only a secondary effect on credit portfolio risk, at least for the underlying credit portfolio. Averaging firm-dependent asset correlations on a sector level can, however, cause a substantial underestimation of the VaR in a portfolio with heterogeneous borrower size. This result holds for the market as well as the sector model. Furthermore, the VaR of the IRB model is more stable over time than the VaR of the market model and the sector model, while its distance from the other two models fluctuates over time. --Asset correlations,sector concentration,credit portfolio risk

What do asset prices have to say about risk appetite and uncertainty?

Implied volatility indices should have information about risk parameters, once they are cleansed of the influence of normal volatility dynamics and macro-economic uncertainty. Building on intuition from the dynamic asset pricing literature, we uncover unobserved risk aversion and fundamental uncertainty from the observed time series of the VIX and the credit spreads while controlling for realized volatility, expectations about the macroeconomic outlook, and interest rates. We apply this methodology to monthly data from both Germany and the US. We find that implied volatilities contain a substantial amount of information regarding risk aversion whereas credit spreads have a lot to say about both risk aversion and uncertainty. Moreover, there is a significant comovement in the German and US risk aversion. JEL Classification:Credit Spread, Economic uncertainty, risk aversion, Time variation in risk and return, Volatility dynamics

The forecasting performance of German stock option densities

In this paper the authors estimate risk-neutral densities (RND) for the largest euro-area stock market (the index of which is the German DAX), reporting their statistical properties, and evaluating their forecasting performance. The authors have applied an innovative test procedure to a new, rich, and accurate data set. They have two main results. First, They have recorded strong negative skewness in the densities. Second, they find evidence for a significant difference between the actual density and the risk-neutral density, leading to the conclusion that market participants were surprised by the extent of both the rise and the fall of the DAX.Stock market - Germany ; Stock options

The New Basel Capital Framework and its implementation in the European Union

Following the adoption by the Basel Committee of new capital rules for banks, a process is now taking place in the EU to transpose the rules into Community law and, ultimately, into national legislation. This paper gives an overview of the main issues that relate to the EU implementation, mainly from the perspectives of financial stability and financial integration. Although the EU rules are to a large extent based on the texts of the Basel Committee, modifications have been introduced to account for the specific legal and institutional setting, as well as for some features of the European financial system. The paper gives an overview of these modifications and deals in greater detail with a number of selected topics: the monitoring of procyclicality, the role of the consolidating supervisor and the treatment of real estate lending and covered bonds. The paper concludes with an outlook for the future.Banks, Basel II, capital requirements, financial regulation, financial stability, financial supervision, risk management.

The Forecasting Performance of German Stock Option Densities

In this paper we will be estimating risk-neutral densities (RND) for the largest euro area stock market (the index of which is the German DAX), reporting their statistical properties, and evaluating their forecasting performance. We have applied an innovative test procedure to a new, rich, and accurate data set. We have two main results. First, we have recorded strong negative skewness in the densities. Second, we find evidence for significant differences between the actual density and the risk-neutral density, leading to the conclusion that market participants were surprised by the extent of both the rise and the fall of the DAX. -- In dieser Arbeit werden "risikoneutrale" Dichtefunktionen über künftige DAXIndexstände aus täglich beobachteten Preisen europäischer Kauf- und Verkaufsoptionen mit verschiedenen Restlaufzeiten abgeleitet. Das hierbei verwendete Berechnungsverfahren beruht auf der Mischung von zwei Log-Normalverteilung, bei dem fünf Parameter (der Mischungsparameter, zwei Mittelwerte und zwei Standardabweichungen) so bestimmt werden, dass der quadratische Abstand zwischen beobachteten und impliziten Optionspreisen minimal ist. Die Preisnotierungen für die Derivative werden der Eurex entnommen und der Untersuchungszeitraum erstreckt sich von Dezember 1995 bis Mai 2002, also sowohl über die Boom- als auch über die Niedergangsphase des DAX. Die Vorhersagehorizonte der Dichten sind auf Grund der Datenlage auf sechs bis acht Wochen begrenzt. Die Vorhersagegüte dieser Dichten wird über verschiedene neuartige statistische Evaluierungsverfahren abgeschätzt. Im Ergebnis stellt sich folgendes heraus: Erstens: Die Dichten weisen im Durchschnitt eine negative Schiefe (negatives drittes Moment) auf, so dass das linke Ende der Dichte "dicker" ist als das rechte und die Marktteilnehmer somit einen bestimmten prozentualen Kursverlust als wahrscheinlicher einschätzten als einen Kursgewinn. Zweitens: Die Evaluierungstests für die Dichten machen deutlich, dass die tatsächlichen Dichten im Mittel deutlich von den risikoneutralen Dichten abweichen. Dabei kann ausgeschlossen werden, dass es sich lediglich um einen "Mittelwert"fehler handelt. Vielmehr scheinen die Markteilnehmer sowohl in der Aufschwung- als auch in der Abschwungphase von den Kursbewegungen des DAX überrascht worden zu.option prices,risk-neutral density,density evaluation,overlapping data