Unveiling trading patterns: iTraxx Europe financials from the great financial crisis to ECB monetary easing
-
DOIhttp://dx.doi.org/10.21511/bbs.17(3).2022.16
-
Article InfoVolume 17 2022, Issue #3, pp. 188-200
- Cited by
- 563 Views
-
193 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Financial stability is a statutory concern of the European Central Bank. Spreads of bank credit default swaps (CDS) indices are a reference for financial stability, but the literature is scarce in this respect. This paper poses the novel research question of which characteristics of investors in these derivatives are implied by the volatility behavior of the returns of financial CDS indices. Daily spread returns for the 5-year maturity iTraxx Europe Financials (subordinated and senior), for the period between June 2004 and March 2015, are used to estimate a GJR-M model with Student t innovations, and two MGARCH models (one with constant and the other with dynamic conditional correlations). The results show that investors in the index referring to subordinated debt are risk averse (risk premium estimate of 0.688) and liable to leverage effects, while investors in the index for senior debt do not have such characteristics. The degrees of freedom of the Student t innovations are estimated to be 4 for both indices, implying that returns have distributions with very fat tails. Population excess kurtosis diverges to infinity. The results show that the conditional correlation between the indices is dynamic. Although correlations vary widely, most of that variation occurs before the Euro Area crisis. It is concluded that the inclusion of both indices in a portfolio would be misadvised for bear markets with distressed financial entities: the correlations are always positive, above 0.75 since 2010. Moreover, both indices prove to be sensitive to the varying surrounding conditions as investors share market sentiments.
Acknowledgments
NECE’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/04630/2020
CEBER’s research is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., Project UIDB/05037/2020
- Keywords
-
JEL Classification (Paper profile tab)C58, E52, E58, G01, G21
-
References45
-
Tables1
-
Figures2
-
- Figure 1. Dynamic conditional correlations from MGARCH-DCC
- Figure 2. iTraxx Financials Europe spreads for subordinated and senior debt
-
- Table 1. Estimation results for the GJR (1,1)_t-M model of the iTraxx returns
-
- Afonso, A., Gomes, P., & Rother, P. (2007). What “hides” behind sovereign debt ratings? (Working Paper Series No. 711). European Central Bank.
- Alemany, A., Ballester, L., & González-Urteaga, A. (2015). Volatility spillovers in the European bank CDS market. Finance Research Letters, 13, 137-147.
- Alter, A., & Schüler, Y. S. (2012). Credit spread interdependencies of European states and banks during the financial crisis. Journal of Banking & Finance, 36(12), 3444-3468.
- Bollerslev, T. (1990). Modeling the coherence in short-term nominal exchange rates: A multivariate generalized ARCH approach. Review of Economics and Statistics, 72(3), 498-505.
- Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A Capital Asset Pricing Model with Time Varying Covariances. Journal of Political Economy, 96(1), 116-131.
- Bratis, T., Laopodis, N. T., & Kouretas, G. P. (2020). Systemic risk and financial stability dynamics during the Eurozone debt crisis. Journal of Financial Stability, 47, 100723.
- Bruneau, C., Delatte, A., & Fouquau, J. (2014). Was the European sovereign crisis self-fulfilling? Empirical evidence about the drivers of market sentiments. Journal of Macroeconomics, 42(C), 38-51.
- Calice, G. (2014). CDX and iTraxx and their relation to the systemically important financial institutions: Evidence from the 2008-2009 financial crisis. Journal of International Financial Markets, Institutions and Money, 32(1), 20-37.
- Chiarella, C., ter Ellen, S., He, X., & Wu, E. (2015). Fear or fundamentals? Heterogeneous beliefs in the European sovereign CDS market. Journal of Empirical Finance, 32, 19-34.
- Choe, G. H., Choi, S. E., & Jang, H. J. (2020). Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness. North American Journal of Economics and Finance, 54, 100907.
- Covi, G., & Eydam, U. (2020). End of the sovereign-bank doom loop in the European Union? The Bank Recovery and Resolution Directive. Journal of Evolutionary Economics, 30, 5-30.
- Drago, D., Di Tommaso, C., & Thornton, J. (2017). What determines bank CDS spreads? Evidence from European and US banks. Finance Research Letters, 22, 140-145.
- ECB. (2002). Protocol on the Statute of the European System of Central Banks and of the European Central Bank. European Central Bank.
- ECB. (2006). Subordinated Debt Issues by Euro Area Banks. Financial Stability Review (pp. 115-117). European Central Bank.
- Ehmer, P. (2017). Monetary policy has reduced fiscal pressure in euro area – but interest rate turnaround is coming. KfW Research - Focus on Economics, 176, 1-4.
- Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate GARCH models. Journal of Business and Economic Statistics, 20(3), 339-350.
- Engle, R. F., Lilien, D., & Robins, R. (1987). Estimating Time-Varying Risk Premia in the Term Structure: The ARCH-M Model. Econometrica, 55(2), 391-407.
- EU. (2014). Directive 2014/59/EU of The European Parliament and of the Council of 15 May 2014. Official Journal of the European Union (pp. 173-190).
- Eurostat. (2021). Euroindicators No. 119/2021.
- Eurostat. (2022). Euroindicators No. 46/2022.
- Fang, H., & Lee, Y-H. (2011). The impact of the subprime financial crisis on stock index returns for high- and low-risk countries via CDS indices. Investment Management and Financial Innovations, 8(4), 123-137.
- Fenech, J-P., Vosgha, H., & Shafik, S. (2014). Modelling the dependence structures of Australian iTraxx CDS index. Applied Economics, 46(4), 420-431.
- Financial Times. (2022a). Letter: It’s 10 years since Draghi’s ‘Whatever it takes’ speech.
- Financial Times. (2022b). ECB raises rates for first time in more than a decade.
- Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. Journal of Finance, 48(5), 1779-1801.
- Gropp, R., Vesala, J., & Vulpes, G. (2006). Equity and bond market signals as leading indicators of bank fragility. Journal of Money, Credit, and Banking, 38(2), 399-428.
- Gubareva, M. (2020). Excess liquidity premia of single-name CDS vs iTraxx/CDX spreads: 2007–2017. Studies in Economics and Finance, 37(1), 18-28.
- Hippert, B., Uhde, A., & Wengerek, S. T. (2019). Portfolio benefits of adding corporate credit default swap indices: evidence from North America and Europe. Review of Derivatives Research, 22, 203-259.
- Hui, C-H., Lo, C-F., & Lau, C-S. (2013). Option-implied correlation between iTraxx Europe Financials and Non-Financials Indexes: A measure of spillover effect in European debt crisis. Journal of Banking & Finance, 37(9), 3694-3703.
- ISDA. (2014). Credit Derivatives Definitions and Standard Reference Obligations – FAQ. International Swaps and Derivatives Association.
- Johnson, N. L., Kotz, S., & Balakrishnan, N. (1995). Continuous Univariate Distributions – Volume 2. Wiley Series in Probability and Mathematical Statistics. New York: Wiley.
- Kato, P., & Hagendorff, J. (2010). Distance to default, subordinated debt, and distress indicators in the banking industry. Accounting and Finance, 50(4), 853-870.
- Katsampoxakis, I. (2022). ECB’s unconventional monetary policy and spillover effects between sovereign and bank credit risk. EuroMed Journal of Business, 17(2), 218-245.
- Katsourides, Y. (2016). Negative Images of Europe in an Era of Crisis: The Media and Public Opinion in Cyprus. Journal of Contemporary European Studies, 24(1), 65-85.
- King, M. (2019). Time to buy or just buying time? Lessons from October 2008 for the cross-border bailout of banks. Journal of Financial Stability, 41, 55-72.
- Klimek, P., Poledna, S., Farmer, J. D., & Thurner, S. (2015). To bail-out or to bail-in? Answers from an agent-based model. Journal of Economic Dynamics & Control, 50, 144-154.
- Markit (2019). iTraxx Europe and iTraxx Crossover Index Rules.
- Markit. (2021). CDS Indices Primer.
- Miller, S., Olson, E., & Yeager, T. J. (2015). The relative contributions of equity and subordinated debt signals as predictors of bank distress during the financial crisis. Journal of Financial Stability, 16, 118-137.
- Oliveira, M. A., & Santos, C. (2015). Market Exuberance in Sovereign Credit Default Swaps: Assessing the EU Regulatory Framework and Trading Profit Opportunities. Investment Management and Financial Innovations, 12(4), 70-80.
- Oliveira, M. A., & Santos, C. (2018). Determinants of credit default swaps implied ratings during the crisis: was sovereign risk mispriced? Investment Management and Financial Innovations, 15(3), 1-14.
- Tamakoshi, G., & Hamori, S. (2013). An asymmetric DCC analysis of correlations among bank CDS indices. Applied Financial Economics, 23, 475-481.
- Tamakoshi, G., & Hamori, S. (2014). The conditional dependence structure of insurance sector credit default swap indices. North American Journal of Economics and Finance, 30, 122-132.
- Tsay, R. S. (2010). Analysis of Financial Time Series. Wiley Series in Probability and Statistics. New Jersey: Wiley.
- Wang, X., & Zhong, Z. (2022). Dealer inventory, pricing, and liquidity in the OTC derivatives markets: Evidence from index CDSs. Journal of Financial Markets, 57, 100617.