1 / 31

M.Sc. Student: Bucsa Paul Bogdan Supervisor Professor: Moisa Altar

Academy of Economic Studies Doctoral School of Finance and Banking - DOFIN. DYNAMIC RELATIONSHIP BETWEEN EMERGING SOVEREIGN CDS AND BOND SPREADS AND CO-MOVEMENTS OF CREDIT SPREADS. M.Sc. Student: Bucsa Paul Bogdan Supervisor Professor: Moisa Altar. Bucharest, July 2009.

morty
Download Presentation

M.Sc. Student: Bucsa Paul Bogdan Supervisor Professor: Moisa Altar

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Academy of Economic Studies Doctoral School of Finance and Banking - DOFIN DYNAMIC RELATIONSHIP BETWEEN EMERGING SOVEREIGN CDS AND BOND SPREADS AND CO-MOVEMENTS OF CREDIT SPREADS M.Sc. Student: Bucsa Paul Bogdan Supervisor Professor: Moisa Altar Bucharest, July 2009

  2. Topics of the dissertation paper • Brief review regarding studies on Emerging Sovereign CDS and bond spreads. • Spreads evolution during the current financial turmoil • Long term and short-term relation between Bond spreads and CDS. Which market leads in price discovery? • Co-movements and volatility spillover in emerging sovereign CDS using a Component GARCH model • A short look at the global factors that affect spreads • Conclusions

  3. Brief Literature review I. CDS and Bond spreads: two measures of the same risk DYNAMIC RELATIONSHIP BETWEEN CDS AND BOND SPREADS: CDS and bond spreads reflect roughly the same risk, the risk of default of the reference entity. They move in tandem in the long -run; a long bond + short risk-free bond+CDS=0 (Ammer and Cai (2007). Although CDS and bond spreads are two measures of the same credit risk, in practice, there are various factors that cause the two to be different such as "cheapest-to-deliver" option in the CDS, the relative liquidity in the CDS and/or bond market, the global market liquidity, bond short-sale restrictions, etc. (Wit (2006), Zhu (2006)) • Long-run equilibrium between CDS and Bond spreads; Blanco et al. (2005), Zhu (2006), Chan-Lau and Kim (2004) show that the theoretical parity relationship between the two credit spreads holds as a long-run equilibrium condition. • CDS market is the main forum for credit risk price discovery (Blanco et al. (2005), Zhu (2006)) or results are mixed ( Chan-Lau and Kim (2004), In et al. (2006) )

  4. Brief Literature review II Determinants of bond spreads and CDS: • Global market and country specific determinants of bond spreads (Hartelius et al. (2008), Ebner (2009), Culha et al.(2006), Baek et al.(2005) or of bond market distress( Walti(2009)) • Ratings (as measure of a country's creditworthiness) in relation with CDS and bond spreads (Sy (2002), Hull et al. (2004), Cantor et al.(1996) Gaillard (2009) ) • The high correlation of Sovereign Credit risk and CDS relation to US stock and HY bond markets, global risk premia, international liquidity and trading (Longstaff et al.(2007), Ozatay et al.(2009), Cifarelli et al. (2006)) • Common factor, capturing global financial conditions and also associated effects on the world economy, can account up to 80% of the increase of EM spreads during the turmoil (Ciarlone et al.(2008)) - Sovereign emerging Bond spreads in conjunction with an IMF supported program (Eichengeen (2006), Walti(2009)) A single-name credit default swap (CDS) is a bilateral, off-balance sheet agreement between two counterparties in which one party, the protection seller or writer, offers the other party, the buyer, protection or insurance against credit risk on a specific amount of face value of bonds (the notional amount) against a credit event by a third party (reference entity), for a specified period of time, in return for premium payments. In fewer words, a credit default swap (CDS) is an agreement between two parties to exchange the credit risk of a reference entity. (Duffie (1999)) CDS contracts caracteristics and evolution ( Meng et al. (2007), Mengle (2007)) and recovery rates (Singh et al.(2009))

  5. Evolution of JPM EMBIG Global Index ( Index of Bond spreads of Emerging Sovereigns) Evolution of spreads of Emerging Sovereign bond spreads was affected in a high measure by the financial turmoil; financial markets events such as funds and banks that went bankrupt impacted heavily risk-aversion that reached record-highs in Autumn 2008. Lack of trust between financial institutions led to low desire to lend between the financial institutions and to businesses. Therefore, to revive the trust and lending, CBs lowered interest rates and adopted quantitative easing and started buying long term bonds from the market.

  6. World CDS spreads evolution Evolution of 5Y CDS spreads for selected countries in Latin America and Europe. (Jan 06-Apr 09): We notice Ukraine and Venezuela have much higher CDS than the other countries, as they are more likely to default 1 year evolution of 5Y CDS spreads for selected Emerging CEE sovereigns: We notice the high degree of co-movements between the countries' 5Y CDS spreads and the sharp increase after Lehman default in Sep 08

  7. 2 year correlations between Sovereign CDS: High correlation between CDS There are high correlations between Sovereign CDS spreads. I consider that co-movements are in line with global factors evolutions (such as risk aversion, global economic growth, global liquidity availability…) The correlations are significant at 1%, with smaller degree between AUSTRIA and RUSSIA/UKRAINE/ARGENTINA

  8. Evolution of Romania 5Y CDS and Bond spreads Romania Sovereign, 5Y, EUR, Senior, Unsecured, CDS spreads' evolution (Jan 2006-April 2009). Maximum CDS price of 780. Evolution of the Bid Yield To Maturity for the Romania 8 ½, 2012 EUR Bond Evolution of the Mid Z-Spread Line for Romania 8 ½, 2012 EUR Bond, 31/01/2006 - 24/04/2009. Record high of 943 bp.

  9. Long - run relation and price discovery in Emerging Europe Sovereign debt market. CEE CDS spreads lead their corresponding bond spreads 1. Long-term relationship between CDS and Bond spreads. Cointegration -there is a strong similarity in the pricing of risk between the two markets in times of normal market conditions -CDS tend to react ( price in the news) first in times of increased risk aversion and reduced optimism -in times of turmoil, each market's liquidity and imperfections combined with product/market characteristics and high risk aversion made the gap widen…still we can see an adjusting of the spreads to long term equilibrium as the crisis eased Relation between the CDS spread and bond spread for Romania

  10. Long-term relationship between CDS and Bond spreads. Cointegration Unit root tests results: All CDS and bond spread series have unit roots. *, **, *** shows significance at 10%, 5% and 1% confidence level Johansen Cointegration Rank Test results: As per our expectations, there is a long term strong relation between CDS and bonds spreads, as they are cointegrated ** Trace test indicates 1 cointegrating eqn(s) at the 0.05 level

  11. Short-term relation CDS- Bond spreads. Price discoveryGranger causality approach (I) CDS market dominates the bond market at low number of lags. No single market dominates a high number of lags

  12. Short-term relation CDS- Bond spreads. Price discoveryGranger causality approach (II) CDS spreads lead Bond spreads in price discovery

  13. A VECM approach to price discovery As the CDS and Bond spreads are cointegrated, a solution to study the price discovery process is by an error correction model. The focus is put on the adjustment coefficients λ1 and λ2. Optimal number of lags is chosen based on SIC and AIC. ,Pcds - CDS PRICE ,Pcs - Bond spread The estimated adjustment coefficients λ1 and λ2 measure the degree to which prices in a particular market adjust to correct pricing discrepancies from their long term trend. For example, if λ2 is significantly positive, it implies that the cash market adjusts to remove pricing errors, meaning that, the derivatives market moves ahead of the cash market in reflecting changes in credit conditions. Alternatively, if λ1 is significantly negative, it implies that the CDS market moves after the cash market. If both coefficients are significant, the relative magnitude of the two coefficients reveals which of the two markets leads in terms of price discovery. Hasbrouck’s model of “information shares” assumes that price volatility reflects new information, and so the market that contributes most to the variance of the innovations is presumed to also contribute most to price discovery. Gonzalo and Granger’s model attributes superior price discovery to the market that adjusts least to price movements in the other market. The contributions of market 1 (the CDS market) to price discovery are defined by the following expressions: Gonzalo-Granger ratio:

  14. Price discovery occurs mainly in the CDS market

  15. Co-movements, common volatility trends and spillover effects in the Emerging Countries Sovereign CDS In this part of the paper we test for the existence of co-movements and for the existing of spillover in the CDS spreads of Emerging Sovereigns. The countries included in this study (8) are: Romania, Hungary, Poland, Croatia, Russia, Ukraine, Venezuela and Mexico. The data used is daily and ranges from October 2004 to end of March 2009. The model used is a Component – GARCH model that decomposes variance in a permanent component and in a transitory component. We focus on the permanent component of variance of the daily CDS returns of the above countries. The assumptions that I have made is that there is a strong connection between daily CDS returns and daily returns in VDAX – implied volatilityof DAX. Also, a term that to show there is asymmetry in the way CDS react to good and bad news.

  16. C-GARCH estimates results *, **, *** shows significance at 10%, 5% and 1% confidence level Full data sample available in Bloomberg and Reuters: 04/10/2004-27/03/2009 Bad news's impact is stronger than good news's impact

  17. Permanent component of variance We notice interesting similarity between PCV and market risk aversion, proxied bellow by VDAX - German VDAX volatility index

  18. High correlation between Permanent components Correlation coefficients between permanent components of variance • High correlation coefficients between Permanent Components of Variance for the CDS returns between : • Hungary and Poland, and in general CEE countries • Ukraine, Russia and Mexico • Lower correlation between Venezuela and the rest, as Venezuela imbalances and default risk are high

  19. Large degree of co-movements in Permanent components Full data sample available in Bloomberg and Reuters: 04/10/2004 - 27/03/2009 Principal components analysis for the permanent components of variance. Principal Components analysis results for the permanent component of variance, sample: 01/01/2007- 3/27/2009

  20. PCA for PCV for Romania, Poland and Hungary • Principal components analysis for the permanent components of variance (full data set) for Romania, Poland and Hungary shows that first component accounts for a high 82%, showing high similarities in the movements of CDS spreads. • The result is in line with expectations as often the CEE countries are viewed as an homogenous group.

  21. Spillover between PCV • In order to test for spillover effects towards and from a country (Romania) we re-estimate the CGARCH model using in the equation for the permanent component of variance for a country the lagged estimated permanent components for each of the other countries

  22. Spillover effects in PCV Spillover effects from the permanent component of variance of country j to the permanent component of variance of returns of Romania CDS spreads Spillover effects from the permanent component of variance of returns of Romania CDS spreads to the permanent component of variance of country j. *, **, *** shows significance at 10%, 5% and 1% confidence level

  23. Granger causality between PCV Granger Causality tests for each pair of countries' permanent components of variance (PCV) show a large number of significant causalities in PCV *, **, *** shows significance at 10%, 5% and 1% confidence level • We see that Croatia, a relative smaller country, has less power to influence the variance of other countries, but is influenced by the PCVs of all other countries at 1% significance level. • Mexico, a known country in the market of sovereign debt Granger causes all other PCV but is Granger caused at 1% by the larger countries in this study. • The results show that there is causality from all countries to Romania and from Romania to all countries except towards Venezuela and to Poland.

  24. What drives CDS, Bond spreads? Country specific factors Global factors • Reserves/ GDP • Debt/ GDP, FX debt/GDP • Inflation • Short term debt • Current account balance, openness • Budget deficit • Industrial production growth • GDP volatility • History of default • Ratings • Socio-polical stability, democracy • IMF program • … • Risk aversion • Global liquidity - interest rates • Global trust in financial system • Global investment flows • Global GDP growth • War/conflicts in region • Regional developments • Gold/ commodities/oil prices • …

  25. LIBOR-OIS spread - a very good relation with the financial turmoil LOIS, the "spread" between LIBOR rates and OIS ratesis an important measure of trust in the money markets,considered by many, including former US Federal Reserve chairman Alan Greenspan, to be a strong indicator for the relative stress in the money markets. A higher spread is typically interpreted as indication of a decreased willingness to lend by major banks, while a lower spread indicates higher liquidity in the market. As such, the spread can be viewed as indication of banks' perception of the creditworthinessof other financial institutions and the general availability of funds for lending purposes.

  26. OLS estimation results for J.P.MORGAN EMBIG COMPOSITE spread, monthly data observations *, **, *** shows significance at 10%, 5% and 1% confidence level

  27. Few cross-market correlations for Romania CDS We notice high correlation between Romania 5Y CDS, VDAX volatility index and iTraxx Europe Crossover index Correlations between markets provide tradable (speculation, hedging) oportunities Evolution of the Romania 5Y CDS is similar to the implied volatility of the 1M EURRON options. This is as a result of the fact that global market conditions, especially risk aversion, affected all Emerging markets not only debt market.

  28. Conclusions • There is a dynamic relationship between CDS and Bond spreads. Price discovery occurs in CDS market • There are co-movements and spillover effects in Emerging Sovereign CDS market • There are important similarities between CEE Emerging Sovereigns CDS spreads • Global market factors such as risk aversion, liquidity availability, creditworthiness, economic sentiment outlook, economic growth impact CDS and Bond spreads movements

  29. Selective References 1 • Alexander, C. and A. Kaeck (2008), “Regime dependent determinants of credit default swap spreads”, Journal of Banking and Finance, 32, 1008-1021. • Ammer, J. and F.Cai (2007), “Sovereign CDS and Bond Pricing Dynamics in Emerging Markets: Does the Cheapest-to-Deliever Option Matter?” Board of Governors of the Federal Reserve System, International Finance Discussion Papers, No 912. • Andritzky, J., G. Bannister, and N. Tamirisa (2005), “The Impact of Macroeconomic Announcements on Emerging Market Bonds”, IMF Working Paper, WP/05/83 • Baek, I., A. Bandopadhyaya, and C. Du (2005), “Determinants of market-assessed sovereign risk: Economic fundamentals or market risk appetite?”, Journal of International Money and Finance, 24, 533-548. • Blanco, R., S. Brennan, and I. Marsh (2005), “An empirical analysis of the dynamic relationship between investment-grade bonds and credit default swaps”, Journal of Finance, 60, 2255-2281. • Borensztein, E. and U. Panizza (2008), “The Costs of Sovereign Default”, IMF Working Paper, WP/08/238. • Bunda, I., A. Hamann, and S. Lall (2009), “Correlations in emerging market bonds: The role of local and global factors”, Emerging Markets Review; EMEMAR-00205. • Cailleteau, P., K. Lindow, and D. Hornung (2009), “Moody’s Global Sovereign – ‘Emerging’ European Sovereigns: The Case for Risk Differentiation”, Moody’s, www.moodys.com. • Cantor , R. (2004), “An introduction to recent research on credit ratings”, Journal of Finance and Banking, 28 , 2565-2573. • Cantor, R. and F. Packer (1996), “Determinants and Impact of Sovereign Credit Ratings”, Federal Reserve Bank of New York Economic Policy Review, vol. 2, 37-53. • Chan-Lau, J. and Y. Kim (2004), “Equity Prices, Credit Default Swaps and Bond Spreads in Emerging Markets”, IMF Working Paper, WP/04/27. • Ciarlone, A., P. Piselli, and G. Trebeschi (2008), “Emerging market spreads in the recent financial turmoil”, Banca D’Italia Ocassional Papers, No. 35. • Ciarlone, A., P. Piselli, and G. Trebeschi (2009), “Emerging markets’ spreads and global financial conditions”, Journal of International Financial Markets, Institutions and Money, 19, 222–239. • Cifarelli, G. and G. Paladino (2006), “Volatility co-movements between emerging sovereign bonds: Is there segmentation between geographical areas?”, Global Finance Journal, 16, 245-263. • Culha, O.Y., F. Ozatay, and G. Sahinbeyoglu (2006), “The Determinants of Sovereign Spreads in Emerging Markets”,Central Bank of the Republic of Turkey Working Paper, No. 06/04. • Das, S. and P. Hanouna (2009), “Hedging Credit; Equity Liquidity Matters”, Journal of Financial intermediation, 18, 112-123. • Duffie, D. (1999), “Credit Swap Valuation”, Financial Analysis Journal, Jan/Feb 1999, 55, 1. • Duggar, E. (2009), “Sovereign Default and Recovery Rates”, 1983-2008. Moody’s Global Policy Credit Policy. • Dungey, M., R. Fry, B. Gonzalez, and V. Martin (2006), “Contagion in international bond markets during the Russian and the LTCM crises”, Journal of Financial Stability, 2, 1-27. • Ebner, A. (2009), “An empirical analysis on the determinants of CEE government bond spreads”, Emerging Markets Review, doi:10.1016/j.ememar.2009.02.001. • Eichengreen, B., K. Kletzer, and A. Mody (2006), “The IMF in a world of private capital markets”, Journal of Banking & Finance, 30, 1335-1357. • Eichengreen, B. and A. Mody (1998), “What explains changing spreads on emerging- market debt: Fundamentals or market sentiment?”, NBER Working Paper, WP 6408.

  30. Selective References 2 • Fabozzi, F., X. Cheng, and R. Chen (2007), “Exploring the components of credit risk in credit default swaps”, Finance Research Letters, 4, 10-18. • Ferruci, G. (2003), “Empirical Determinants of Emerging Market Economies’ Sovereign Bond Spreads”, Bank of England Working Paper, No. 205. • Gaillard, N. (2009), “Fitch, Moody’s and S&P’s Sovereign Ratings and EMBI Global Spreads: Lesons from 1993-2007”, International Research Journal of Finance and Economics, 26. • Gande, A. and D. Parsley (2005), “News spillovers in the sovereign debt market”, Journal of Financial Economics, 75. 691-734. • Hartelius, K., K. Kashiwase, and L. Kodres (2008), “Emerging market Spread Compression: Is it Real or is it Liquidity?”, IMF Working Paper, WP/08/10. • Hull, J., M. Predescu, and A. White (2004), “The relationship between credit default swap spreads, bond yields and credit rating announcements”, Journal of Banking and Finance, 28, 2789-2811. • In, F., B. Kang, and S. T. Kim (2007), “Sovereign credit default swaps, sovereign debt and volatility transmission across emerging markets”, Social Science Research Network, http://ssrn.com/abstract=1090408. • Kaminsky, G. and S. L. Schmukler (2002), “Emerging Market Instability: Do Sovereign Ratings Affect Country Risk and Stock Returns?”, The World Bank Economic Review, Vol.16, No.2, 171-195. • Lake, A. and N. Apergis (2009), “Credit Default Swaps and Stock Prices: Further Evidence within and Across Markets from Mean and Volatility Transmission with a MVGARCH-M Model and Newer Data”, Available at SSRN: http://ssrn.com/abstract=1330011. • Longstaff, F., J. Pan, L. Pederson, and K. Singleton (2007), “How Sovereign Is Sovereign Credit Risk?”, NBER Working Paper Series, Working Paper 13658. • Meng, L. and O. Gwilym (2007), “The characteristics and evolution of credit default swap trading”, Journal of Derivatives and Hedge Funds, Volume 13, No. 3, 186-198. • Mengle, D. (2007), “Credit Derivatives: An Overview. Federal Reserve Bank of Atlanta”, Economic Review, Forth Quarter. • Ozatay F., E. Ozmen, and G. Sahinbeyoglu (2009), Emerging market sovereign spreads, global financial conditions and US macroeconomic news”, Economic Modelling, 26, 526-531.. • Rocha, K., R. Siqueira, and F. Pinheiro (2007), “Vulnerability of Emerging Markets to Global Shocks: The Role of Debt and Governance on Sovereign Spreads”, The Journal of Fixed Income, Fall 2007, 17, 2. • Rowland, P. (2004), “The Colombian Sovereign Spread and its Determinants”, Columbia Banco de la Republica. • Singh, M. and J. Andritzky (2005), “Overpricing in Emerging Market Credit- Default-Swap Contracts: Some Fvidence from Recent Distress Cases”, IMF Working Paper, WP/05/125. • Skinner, F. and J. Nuri (2007), “Hedging emerging market bonds and the rise of the credit default swap”, International Review of Financial Analysis, 16, 452-470. • Skinner, F. and T. Townend (2002), “An empirical analysis of credit default swaps”, International Review of Financial Analysis, 11, 297-309. • Sy, A. (2002), “Emerging Market Bond Spreads and Sovereign Credit Ratings: Reconciling market views with economic fundamentals”, Emerging Markets Review, 3, 380-408. • Tang, D.Y. and H. Yan (2007), “Liquidity and Credit Default Swap Spreads”, NBER Working Paper Series. • Walti, S. and G. Weber (2009), “Recovering from bond market distress: Good luck and good policy”, Emerging Market Review, 10, 36-50. • Wit, J. (2006), “Exploring the CDS – Bond Basis”, National Bank of Belgium Working Paper Research, Available at www.nbb.be. • Zhu, H. (2006), “An Empirical Comparison of Credit Spreads between the Bond Market and the Credit Default Swap Market”, Journal of Financial Services Research, 29, 211-235.

  31. Thank You! • Questions and Answers

More Related