A framework for measuring and predicting system risk with the conditional value at risk approach

Subject Areas : Financial Knowledge of Securities Analysis

Ja'far  Baba Jani ¹ (Faculty member of of Allameh Tabatabai University)
M. Taghi  Taghavi Fard ² (Faculty member of of Allameh Tabatabai University)
Amin  Ghazali ³ (PhD student at Allameh Tabatabai University)

Received: 2016-12-05 Accepted : 2017-06-22 Published : 2018-09-23

Keywords: systemic risk, systemic risk measurement, prediction of systemic risk, conditional value at risk (CoV, macro-prudential policies,

Abstract :

In recent years with the increasing integration and innovation in financial markets, concerns about the overall stability of the financial system has increased and the concept of systemic risk has become more important. systemic risk is the risk imposed by interlinkages and interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a crisis in the entire system or market. In this study, we presented a framework for measuring and predicting systemic risk in the capital market of Iran using conditional value at risk approach (CoVaR). On this basis, ΔCoVaR as a measure of systematic risk using quintile regression based on a set of state variables that indicates changes in the distribution of asset returns has been estimated. As well as to enhance the accuracy of the estimate, the research variables modeled after the conditional autoregressive value at risk model (CAViaR) has been developed and some Lagged firm specific characteristic has also been added. In order to test the validity of the model back testing methods have been used. On the other hand, The potential for systemic risk increases when volatility decreases (volatility paradox). In this study, we try to predict systemic risk by take advantage of the panel structure of the data and the relationship between ΔCoVaR and firm-specific variables that are available in certain sections.

References:

*      رادپور، علی، علی رسولی‌زاده و احسان رفیعی (۱۳۸۸)؛ مدیریت ریسک بازار: رویکرد ارزش در معرض خطر، شرکت ماتریس تحلیلگران سیستم‌های پیچیده، تهران، انتشارات آتی نگر.

*      Adrian, T., and Markus K. Brunnermeier (2008-2014) CoVaR, FRB of New York Sta
 Report, (567).

*      Ang, A., Chen, J. and Xing, Y. (2006), Downside Risk, Review of Financial Studies , Vol. 19, pp. 1191–1239.

*      Arias, Mauricio , Juan Carlos Mendoza and David Perez-Reynay (2010) Applying CoV aR to Measure Systemic Market Risk: the Colombian Case, Financial Stability Department at the Banco de la Republica.

*      Bhar, R. and B. Nikolova (2009), “Oil prices and equity returns in the BRIC countries”, World Economy, Vol 32, No 7.

*      Bernal, Oscar, Jean-Yves Gnabo and Grégory Guilmin (2014) Assessing the contribution of banks, insurance and other financial services to systemic risk, Journal of Banking & Finance, 47, 270–287.

*      Bernardi, M., G. Gayraud, and L. Petrella (2013) Bayesian inference for CoVaR," arXiv preprint arXiv:1306.2834.

*      Borri, N., Di Giorgio, G., Caccavaio, M., Sorrentino, A.M., (2012) Systemic Risk in the European Banking Sector, CASMEF Working Paper Series, No 11

*      Borry, N., M. Caccavaio, G. D. Giorgio and A. M. Sorrentino (2014) Systemic Risk in the Italian Banking Industry, Economic Notes by Banca Monte dei Paschi di Siena SpA, vol. 43, no. 1-2014: pp. 21–38.

*      Buhai, S. (2004) Quantile regressions: overview and selected applications. Unpublished manuscript. Tinbergan Institute and Erasmus University Rotterdam.

*      Campbell, R., Huisman, R. & Koedijk, K. (2001) Optimal portfolio selection in a Value-at-Risk framework, Journal of Banking & Finance, vol. 25(9), pp. 1789-1804.

*      Chan-Lau, J.A. (2008) Default risk codependence in the Global Financial System: Was the Bear Stearns Bailout Justified?, IMF and Tufts University

*      Christofferssen, P. (1998) Evaluating Interval Forecasts. International Economic Review, 39, 841-862.

*      Drakos, Anastassios A. and Georgios P. Kouretas (2015) Bank ownership, financial segments and the measurement of systemic risk: An application of CoVaR, International Review of Economics and Finance, 40, 127–140.

*      Federal Reserve Bank of St. Louis (2013) Review, 95(3), pp. 181-97.

*      Girardi, Giulio and A. Tolga Ergün (2013) Systemic risk measurement: Multivariate GARCH estimation of CoVaR, Journal of Banking & Finance, 2013, vol. 37, issue 8, pages 3169-3180.

*      Granger, C. W. J. (1969) Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica 37 (3): 424–438. doi:10.2307/1912791.

*      Hansen, Lars Peter (2013) Challenges in Identifying and Measuring Systemic Risk, University of Chicago and the NBER.

*      Hong, KiHoon Jimmy (2011) Analytical CoVaR, Faculty of Economics, University of Cambridge, Work in Progress.

*      Jorion, P. (2005) Banking Trading Risk and Systemic Risk, NBER Working Paper, No. 11037.

*      Kambhu, John, Scott Weidman, and Neel Krishnan, Rapporteurs (2007) New directions for understanding systemic risk, National Research Council, the finational academies press, Washington, d.c.

*      Kaufman G. and Scott K. E. (2003) What Is Systemic Risk, and Do Bank Regulators Retard or Contribute to It?, The Independent Review, v. VII, n. 3, pp. 371– 391.

*      Koenker, R., and G. Jr.Bassett (1978) Regression Quantiles Econometrica 46 (1), 33-50.

*      Kragh, Jonas (2011) Measuring Systemic Risk: A Comparison of MES and CoVaR on the European Banking System. Supervisor: Professor Asger Lunde. School of Economics and Management, Aarhus University.

*      Kupiec, P. (1995), Techniques for Verifying the Accuracy of Risk Management Models, Journal of Derivatives 3:73-84.

*      Lopez-Espinosa, G., Moreno, A., Rubia, A., and Valderrama, L. (2012). Short-term wholesale funding and systemic risk: A global CoVaR approach. Journal of Banking and Finance, 36(12):3150{62.

*      Mainik, G., and E. Schaanning (2012) On dependence consistency of CoVaR and some other systemic risk measures," arXiv preprint arXiv:1207.3464.

*      Moreno, María Rodríguez (2013) Systemic Risks: Measures and Determinants, tesis doctoral, deoartmento de economia de la empresa.

*      Oh, D. H., and A. J. Patton (2013) Time-varying systemic risk: Evidence from a dynamic copula model of cds spreads," Duke University Working Paper.

*      Rodriguez-Moreno, M. and Pena, J. (2013) Systemic risk measures: The simpler the better? Journal of Banking and Finance, 37(6):1817{31.

*      Schwarcz S. L. (2008) Systemic Risk, Duke Law School Legal Studies Research Paper Series, Research Paper No. 163

*      Sedunov, J. (2013) What is systemic risk exposure of financial institutions? Working Paper, SSRN.

*      Sheu, H. J.; Cheng, C. L. (2011) A study of China’s and U.S. volatility spillover effects on Hong Kong and Taiwan, Africa Journal of Business and Management 5(13): 5222–5240.

*      Sheu, Her-Jiun and Chien-Ling Cheng (2012) Systemic Risk in Taiwan Stock Market, Journal of Business Economics and Management,Volume 13(5): 895–914

*      Smaga, Paweł (2014) The Concept of Systemic Risk, SRC Special Paper No 5, systemic risk center,  the London school of economics and political science

*      Trapp, Monika and Claudio Wewel (2013) Transatlantic systemic risk. Journal of Banking & Finance 37 (11), 4241{4255.

*      Wang, Yan, Shoudong Chen and Xiu Zhang (2014) Measuring systemic financial risk and analyzing influential factors: AnExtreme Value approach, China Finance Review International, Vol. 4 Iss 4 pp