1 CDX and iTraxx and their Relation to the Systemically Important Financial Institutions: Evidence from the 2008-2009 Financial Crisis Giovanni Calice

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CDX and iTraxx and their Relation to CDX and iTraxx and their Relation to the Systemically Important Financial the Systemically Important Financial Institutions: Evidence from the 2008-Institutions: Evidence from the 2008-

2009 Financial Crisis2009 Financial Crisis

Giovanni CaliceGiovanni Calice(Loughborough University)(Loughborough University)

88thth Financial Risks International Forum Financial Risks International Forum 20152015

Paris – March 30, 2015Paris – March 30, 2015

Credit Derivatives and Financial StabilityCredit Derivatives and Financial Stability

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Outline of Discussion

• Context and Motivation• Literature Review• Methodology• Main Results• Concluding Remarks• Regulatory and Policy Implications• Further Directions of Research


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Credit DerivativesCredit DerivativesCredit DerivativesCredit Derivatives

...or a Panacea for Risk?...or a Panacea for Risk?

A Ticking Time Bomb...A Ticking Time Bomb...


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Purposes and Objectives of the Study

• The aim of the research is to take a new look at the potential The aim of the research is to take a new look at the potential implications of the introduction of credit derivatives for implications of the introduction of credit derivatives for financial stabilityfinancial stability

• More specifically, the analysis is focused on the impact that More specifically, the analysis is focused on the impact that such markets exert on the viability of such markets exert on the viability of the Systemically the Systemically Important Financial InstitutionsImportant Financial Institutions (SIFIs) (SIFIs)

• This paper represents an attempt to understand some of the This paper represents an attempt to understand some of the aspects of the potential relationship between the CDS index aspects of the potential relationship between the CDS index market and the banking and insurance sector. For this we focus market and the banking and insurance sector. For this we focus on default risk as perceived by the market through SIFIs share on default risk as perceived by the market through SIFIs share pricesprices

• The main contribution of our paper is to investigate the relation The main contribution of our paper is to investigate the relation between changes in the level of the CDX and iTraxx indices and between changes in the level of the CDX and iTraxx indices and equity prices movements of a group of SIFIs. In particular, we equity prices movements of a group of SIFIs. In particular, we focus on a number of US as well as European-based systemically focus on a number of US as well as European-based systemically important banks and insurance companies whose failure can important banks and insurance companies whose failure can pose negative externalities to the financial systempose negative externalities to the financial system


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Research Questions

The research restricts itself to the following questions• Question 1: What was the role of the CDs markets in the 2008-2009

destabilization of the global financial system?• Question 2: Do fluctuations in the CDX and iTraxx indices play a

significant role in transmitting shocks across the financial system? • Question 3: Does exist an empirical relationship between the dynamic

patterns of the CDX and iTraxx indices and changes in the equity prices of SIFIs?

• Question 4: To what extent the change in the risk profile (higher moments) of CDSs indices does affect the volatility of SIFIs returns?


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Related Literature (cont.)

• To address these questions, we develop tests that exploit the richness of our To address these questions, we develop tests that exploit the richness of our dataset and builds upon Yang et al. (2006, dataset and builds upon Yang et al. (2006, Journal of Applied EconometricsJournal of Applied Econometrics) who ) who employ generalized forecasts error variance decompositions (GVDs) to examine employ generalized forecasts error variance decompositions (GVDs) to examine short-run dynamic causal linkages across the stock markets in Central and short-run dynamic causal linkages across the stock markets in Central and Eastern Europe, before and after the 1998 Russian financial crisisEastern Europe, before and after the 1998 Russian financial crisis

• Moreover, our paper is related to a growing body of empirical work featuring Moreover, our paper is related to a growing body of empirical work featuring GVDs to measure systemic risk and financial connectedness for a set of the GVDs to measure systemic risk and financial connectedness for a set of the largest international financial institutions around the recent global credit crisis largest international financial institutions around the recent global credit crisis (e.g. Yang and Zhou (2013. (e.g. Yang and Zhou (2013. Management ScienceManagement Science), Diebold and Yilmaz (2013, ), Diebold and Yilmaz (2013, Journal of EconometricsJournal of Econometrics))))


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Context

• Reports from the International Monetary Fund (IMF), the Financial Stability Forum, the Bank for International Settlements (BIS) and other policy authorities have outlined, against the backdrop of exceptional instability in the global financial system, the appalling scale of risks inherent in these instruments

• Specifically, the October 2008 issue of the IMF’s Global Financial Stability Report (IMF, 2008) noted that the confidence in global financial institutions and markets has been badly shaken. Moreover, threats to systemic stability became manifest in September 2008 with the collapse or near-collapse of several SIFIs (e.g. Lehman Brothers, Merrill Lynch, Citigroup, AIG)


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Motivation

• This paper is motivated by the observation that while the number and diversity of innovative or alternative financial products is increasing steadily, the number of financial crises has not clearly declined in recent years

• The main reason we focus on this topic is that the stability of the banking sector and the financial system at large is of the utmost importance for a sustainable and stable growth of the global economy. The extent to which the increasing marketability of credit risk can influence credit and economic cycles is of particular macroeconomic importance


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Related LiteratureIn the literature, there is no unambiguous consensus to the question of whether these derivatives have a positive or negative effect on financial stability

• Bystrom (2005) finds that stock price volatility is significantly correlated with CDS spreads and the spreads are found to increase (decrease) with increasing (decreasing) stock price volatilities. Furthermore, the other interesting finding in this paper is the significant positive autocorrelation present in all the studied iTraxx indices

• Arping (2004) shows how CDs can facilitate banks’ quest for more effective lending relationships. He argues that CDs can have ambiguous effects on financial stability, and that disclosure requirements can strengthen the efficacy of the CDs market


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• Instefjord (2005) analyzes risk taking by a bank that has access to CDs for risk management purposes. He finds that innovations in CDs markets lead to increased risk taking because of enhanced risk management opportunities

• Verdier (2004) argues that, from a broader stability perspective, CDs in their current form increase the likelihood of future sovereign defaults

• Wagner and Marsh (2004) demonstrate that CRT mechanism, under certain conditions, is generally welfare enhancing

• Wagner (2005) shows that the increased portfolio diversification possibilities introduced by CRT can increase the probability of liquidity-based crises

• Rajan (2005) has suggested that the hedging opportunities afforded by CDs and other risk management techniques are transforming the banking industry


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• Partnoy and Skeel (2006) suggest that CDOs are too complex. The transaction costs are high, the benefits questionable. They conclude that CDOs are being used to transform existing debt instruments that are accurately priced into new ones that are overvalued

• Wagner (2007) argues that new credit derivative instruments would improve the banks’ ability to sell their loans making them less vulnerable to liquidity shocks However, this again might encourage banks to take on new risks because a higher liquidity of loans enables them to liquidate them more easily in a crisis. This effect would offset the initial positive impact on financial stability

• Wagner and Marsh (2006), on the other hand, argue that especially the transfer of credit risk from banks to non-banks would be beneficial for financial stability


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Main Contributions

The contribution of the study is twofold a) a methodological• At first, it complements existing work on the

implications of structured credit products volatility for financial sector stability. We do this by applying an innovative modelling approach which handles the indirect VAR methodology to readily available financial market data

b) an empirical one • The second contribution is to provide evidence

of the impact of the evolution of the co-movements between the standardized CDSs indices on the global financial system, by assessing the extent to which SIFIs asset prices are driven by the volatility in the CDS index market


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CDS Indices• A CDS index is a CD used to hedge credit risk or to take

a position on a basket of credit entities. Unlike a CDS, which is an over the counter CD, a CDS index is a completely standardised credit security and may therefore be more liquid and trade at a smaller bid-offer spread

• CDX is the brand-name for the family of CDS Index products of a portfolio of 125 5-year default swaps, covering equal principal amounts of debt of each of 125 named North American investment-grade issuers

• iTraxx contains 125 equally weighted default swaps, composed of both investment grade CDSs and speculative, high-yield CDSs. CDSs are chosen to be part of the index based on their liquidity The most widely traded of the CDS indices is the iTraxx Europe index composed of the most liquid 125 CDSs referencing European investment grade credits


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Dataset of CDSs Prices

We use price data for the traded We use price data for the traded DJ CDX North AmericaDJ CDX North America index and the index and the iTraxx Main Europe iTraxx Main Europe index, respectivelyindex, respectively

• The analysis is restricted to the 5–year indices The analysis is restricted to the 5–year indices maturities, since these contracts are reportedly most maturities, since these contracts are reportedly most actively tradedactively traded

• The indices CDS prices and the bid–ask spreads are The indices CDS prices and the bid–ask spreads are extracted from an extensive proprietary database extracted from an extensive proprietary database obtained from one of the major global investment banks obtained from one of the major global investment banks ((Morgan StanleyMorgan Stanley))

• This dataset covers virtually the entire history of the This dataset covers virtually the entire history of the CDXCDX and and iTraxxiTraxx indices through 2005. Data is missing indices through 2005. Data is missing for some days during the earlier part of the sample. We for some days during the earlier part of the sample. We omit these days from the sample, leaving us with a total omit these days from the sample, leaving us with a total of 1414 daily observations for the global banks and index of 1414 daily observations for the global banks and index datadata

• In contrast, 1501 daily returns are observed between the In contrast, 1501 daily returns are observed between the insurance companies and index data for the 6 and half-insurance companies and index data for the 6 and half-year sample periodyear sample period


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Banking Institutions

BankBank LocationLocation

Bank of America Merrill Bank of America Merrill

LynchLynch

United StatesUnited States

BarclaysBarclays United KingdomUnited Kingdom

BNPBNP FranceFrance

CitigroupCitigroup United StatesUnited States

Credit SuisseCredit Suisse SwitzerlandSwitzerland

Deutsche BankDeutsche Bank GermanyGermany

Goldman SachsGoldman Sachs United StatesUnited States

HSBCHSBC United KingdomUnited Kingdom

JP MorganJP Morgan United StatesUnited States

Lehman BrothersLehman Brothers United StatesUnited States

Morgan StanleyMorgan Stanley United StatesUnited States

RBSRBS United KingdomUnited Kingdom

Société GénéraleSociété Générale FranceFrance

UBSUBS SwitzerlandSwitzerland

Wells FargoWells Fargo United StatesUnited States


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Insurance Institutions

Insurance CompanyInsurance Company LocationLocation

AEGONAEGON NetherlandsNetherlands

AllianzAllianz GermanyGermany

American International American International

groupgroup

United StatesUnited States

Assicurazioni GeneraliAssicurazioni Generali ItalyItaly

AvivaAviva United KingdomUnited Kingdom

AXAAXA FranceFrance

Berkshire HathawayBerkshire Hathaway United StatesUnited States

INGING NetherlandsNetherlands

ManulifeManulife United StatesUnited States

MetLifeMetLife United StatesUnited States

Munich ReinsuranceMunich Reinsurance GermanyGermany

Prudential Prudential United KingdomUnited Kingdom

Swiss LifeSwiss Life SwitzerlandSwitzerland

Swiss ReinsuranceSwiss Reinsurance SwitzerlandSwitzerland

Zurich FinancialZurich Financial SwitzerlandSwitzerland


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Research Methodology Following Yang et. al. (2006), we estimate the exposure of the major global financial

institutions to the CDs market by examining the extent to which developments in the CDS index market contribute to the variability of the firm’s equity returnsEmpirical Model of Financial Stability

A. We test possible influence of fluctuations of the indices on the banks’ equity returns through a SVAR model (approach first suggested by Hasbrouck, 1991)

B.To identify the impact on other endogenous variables in the structure of the VAR, namely the institutions equity return, we compute generalised forecast error variance decompositions (GVDs) between the equity and index returns

C. We then proceed to estimate the influence of the conditional volatility of assets traded in the CD markets on the conditional volatility of the banks’ equity indirectly by using a VAR–MV(GARCH) system


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The Impact of CDS Indices on the Value of Bank EquitySVAR ModelWe estimate the following structural VAR system:

where: denotes matrices in the lag operator

We have established the “weak exogeneity” of the CDX index with respect to the iTraxx

LALALA

LALA

LA

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r

r

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t

t

bank

iTraxx

cdx

333231

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it

t

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t

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bank

iTraxx

cdx

bank

iTraxx

cdx

r

r

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The Transmission of Volatility from the CDS Indices on Bank Equity Volatility - VAR

MV(GARCH) ModelTo extract the conditional volatility of the CDS index market, we estimate:

where:

and y denotes the returns of the two indicesWe then use the predicted volatilities from this system into:

tttty 2

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iTraxxCDXit hhGARCHh 1,1

itit h,0

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Impact Effect (GVD - Banks)Credit Derivatives and Financial StabilityCredit Derivatives and Financial Stability

BankBank CDXCDX iTraxxiTraxx DominanDominan

tt

BarclaysBarclays 1.311.31 14.4514.45iTraxxiTraxx

Royal Bank of ScotlandRoyal Bank of Scotland 0.620.62 13.2313.23iTraxxiTraxx

Société GénéraleSociété Générale 2.242.24 12.2112.21iTraxxiTraxx

Lehman BrothersLehman Brothers 12.6812.68 0.040.04 CDXCDX

BNP ParibasBNP Paribas 1.831.83 12.3712.37iTraxxiTraxx

UBSUBS 1.471.47 11.5511.55iTraxxiTraxx

Morgan StanleyMorgan Stanley 11.2311.230.280.28 CDXCDX

CitigroupCitigroup 10.7410.740.310.31 CDXCDX

Deutsche BankDeutsche Bank 0.740.74 8.828.82iTraxxiTraxx

Credit SuisseCredit Suisse 2.342.34 7.687.68iTraxxiTraxx

Bank of America/Merrill Bank of America/Merrill

LynchLynch

7.667.660.490.49 CDXCDX

JP MorganJP Morgan 7.237.230.420.42 CDXCDX

Wells FargoWells Fargo 6.336.330.420.42 CDXCDX

Goldman SachsGoldman Sachs 5.285.280.610.61 CDXCDX

HSBCHSBC 0.660.66 4.224.22 iTraxxiTraxx

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Impact Effect (GVD – Insurance Companies)Credit Derivatives and Financial StabilityCredit Derivatives and Financial Stability

Insurance CompanyInsurance Company CDXCDX iTraxxiTraxx DominantDominant

INGING 0.970.97 15.7315.73iTraxxiTraxx

AXAAXA 0.870.87 14.2214.22iTraxxiTraxx

AEGONAEGON 0.920.92 14.1214.12iTraxxiTraxx

Prudential Prudential 0.810.81 13.4813.48iTraxxiTraxx

AvivaAviva 0.820.82 11.1311.13iTraxxiTraxx

MetLifeMetLife 13.7213.72 0.810.81 CDXCDX


GroupGroup

13.2813.28 00730073 CDXCDX

AllianzAllianz 0.740.74 10.3410.34iTraxxiTraxx

ManulifeManulife 9.519.510.710.71 CDXCDX

Assicurazioni GeneraliAssicurazioni Generali 0.550.55 8.948.94 iTraxxiTraxx

Swiss LifeSwiss Life 0.550.55 8.478.47 iTraxxiTraxx

Zurich FinancialZurich Financial 0.530.53 7.567.56 iTraxxiTraxx

Swiss ReinsuranceSwiss Reinsurance 0.490.49 7.127.12 iTraxxiTraxx

Munich ReinsuranceMunich Reinsurance 0.510.51 6.746.74 iTraxxiTraxx

Berkshire HathawayBerkshire Hathaway 3.893.89 0.320.32 CDXCDX

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Impact of CDS Index Volatility on Bank Equity (T-stat)


BankBank Sum of Sum of

CoefficientsCoefficients

Lehman BrothersLehman Brothers 0.96860.9686

CitigroupCitigroup 0.96390.9639

Goldman SachsGoldman Sachs 0.95750.9575

RBSRBS 0.95110.9511

UBSUBS 0.94720.9472

Bank of America Merrill Bank of America Merrill

LynchLynch

0.94220.9422

HSBCHSBC 0.93930.9393

JP MorganJP Morgan 0.93780.9378

Wells FargoWells Fargo 0.93370.9337

BNP ParibasBNP Paribas 0.93150.9315

Morgan StanleyMorgan Stanley 0.92600.9260

Deutsche BankDeutsche Bank 0.92510.9251

BarclaysBarclays 0.92500.9250

Credit SuisseCredit Suisse 0.91950.9195

Société GénéraleSociété Générale 0.90360.9036

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Impact of CDS Index Volatility on Equity: Insurance Companies


Insurance CompanyInsurance Company Sum of Sum of

CoefficientsCoefficients

ManulifeManulife 0.94340.9434

Assicurazioni GeneraliAssicurazioni Generali 0.93760.9376


GroupGroup

0.92870.9287

Zurich FinancialZurich Financial 0.91680.9168

MetLifeMetLife 0.91420.9142

AvivaAviva 0.91300.9130

Swiss ReinsuranceSwiss Reinsurance 0.91010.9101

Swiss LifeSwiss Life 0.90830.9083

INGING 0.90020.9002

Munich ReinsuranceMunich Reinsurance 0.89940.8994

AEGONAEGON 0.89470.8947

AllianzAllianz 0.89280.8928

AXAAXA 0.88830.8883

Prudential Prudential 0.88280.8828

Berkshire HathawayBerkshire Hathaway 0.86270.8627

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Impact of CDS Index Volatility on the Institutions’ Equity Prices


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Main Findings

Our most important findings are threefold1. Equity returns for all the LCFIs are negatively

correlated to both the CDX and the iTraxx indices2. The CDX index is the dominant factor driving

shocks across all the LCFIs and its influence varies substantially across the institutions included in this study. Moreover, our empirical evidence uncovers a strong association of negative sign between the geographical location of a SIFI and a shock in the corresponding CDS index market

3. More importantly, the impact of CDS market volatility on the equity return volatility of LCFIs appears very pronounced, suggesting a transmission mechanism which results in the destabilisation of banks and a subsequent increase in their default risk


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Concluding Remarks

• At present this paper propose an econometric approach with some striking results regarding the potential default risk of several international LCFIs

• Our preliminary results suggest that default risk is highly correlated across international boundaries and that information contained in the market prices of CDs do impact on the of equity and asset volatilities of LCFIs

• Given this transmission mechanism we suggest that there is significant evidence that large default events can propagate across institutions and that this shock propagation to the collective asset volatility is enough to create significant default events in those institutions heavily exposed in these markets


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Regulatory and Policy Implications

• The analysis underlines the potential instability effects of the CDS market as a whole, since substantial declines in the equity prices of LCFIs may directly impair the regulatory capital ratios for these institutions and shut off the equity market as a source of new Tier 1 capital

• We believe that our findings have important stability implications for the banking system as a whole, since a collapse in the equity prices for most banks would make it difficult for them to raise common equity thus materially undermining the overall capital adequacy and solvency of the system

• The results, therefore, could help regulators shed more light on the CDS index market and its interaction with other markets and inform on policy implications


Supervisory effort are underway to better understand the complex interactions of the CRT market

Documents

1 CDX and iTraxx and their Relation to the Systemically Important Financial Institutions: Evidence from the 2008-2009 Financial Crisis Giovanni Calice