Bilateral Risk Valuation of Credit Default Swap Contracts: Under multivariate Variance Gamma Process with flexible dependence structure

Document Type : Original Article

Authors
1 Student of finance, banking major, department of financial management, faculty of management and economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 Assistant Professor, Department of Financial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3 Associate Professor, Department of Finance, Faculty of Management, Center Tehran Branch, Islamic Azad University, Tehran, Iran.
10.30495/jik.2024.71018.4170
Abstract
Financial markets have always been subject to the impact of incoming news and react to it according to investor's expectations. Here we develop a quantitative extension of Merton's structural model to capture the impact of news on the credit worthiness of Banks affected by them. Dynamic asset selection and particularly dependence modeling multi-asset plays a critical role in structural model. Multidimensional levy processes has many used in the recent years to model the joint dynamics of multiple financial assets. Some models extend one dimensional VG process to multidimensional with a assumption about common time change for each marginal process, which implies limited dependence structure and similar kurtosis on each margin so we use a new multivariate variance gamma process which allows arbitrary marginal VG processes with flexible dependence structure and this multidimensional Levy process is easy to simulate and estimate. Also we have introduced a multidimensional partial integro-differential equations (PIDE) for default and Credit Default Swap problem Caused by interconnected banking system with mutual liabilities of the structural credit risk model with multivariate VG Process to achieve a new technique to improve this valuations and adjustments.
Keywords

Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of finance29(2), 449-470.
 
[2] Zhou, C. (2001). An analysis of default correlations and multiple defaults. The Review of Financial Studies14(2), 555-576.
 
[3] Hull, J. C., & White, A. D. (2001). Valuing credit default swaps II: Modeling default correlations. The Journal of derivatives8(3), 12-21.
 
[4] Haworth, H., Reisinger, C., & Shaw, W. (2008). Modelling bonds and credit default swaps using a structural model with contagion. Quantitative Finance8(7), 669-680.
 
[5] Li, D. X. (2000). On default correlation: A copula function approach. The Journal of Fixed Income9(4), 43-54.
 
[6] Kiesel, R., & Scherer, M. (2007). Dynamic credit portfolio modelling in structural models with jumps. Preprint, Universität Ulm.
 
[7] Jarrow, R. A., & Turnbull, S. M. (1995). Pricing derivatives on financial securities subject to credit risk. The journal of finance50(1), 53-85.
 
[8] Blanchet-Scalliet, C., & Patras, F. (2008). Counterparty risk valuation for CDS. arXiv preprint arXiv:0807.0309.
 
 
[9] Asmussen, S., Madan, D., & Pistorius, M. (2007). Pricing Equity Default Swaps under an approximation to the CGMY L vy Model. arXiv preprint arXiv:0711.2807.
 
[10] Turnbull, S. (2005). The pricing implications of counterparty risk for non-linear credit products. The Journal of Credit Risk4(1), 117-133.
 
[11] Jarrow, R. A., & Yu, F. (2001). Counterparty risk and the pricing of defaultable securities. the Journal of Finance56(5), 1765-1799.
 
[12] Leung, S. Y., & Kwok, Y. K. (2005). Credit default swap valuation with counterparty risk. The Kyoto Economic Review74(1), 25-45.
 
[13] Sepp, A. (2006). Extended CreditGrades model with stochastic volatility and jumps. Wilmott Magazine, 50-62.
 
[14] Lipton, A., & Sepp, A. (2009). Credit value adjustment for credit default swaps via the structural default model. The Journal of Credit Risk5(2), 127-150.

[15] Lipton, A., & Savescu, I. (2014). Pricing credit default swaps with bilateral value adjustments. Quantitative Finance14(1), 171-188.
 
[16] Crépey, S. (2015). Bilateral counterparty risk under funding constraints—Part II: CVA. Mathematical Finance25(1), 23-50.
 
[17] Pykhtin, Michael, and Steven H. Zhu. "Measuring counterparty credit risk for trading products under Basel II." RISK Books (2006).
[18] Gregory, Jon. "Being two-faced over counterparty credit risk." Risk 22.2 (2009): 86-90.
 
[19] Brigo, D., & Chourdakis, K. (2009). Counterparty risk for credit default swaps: Impact of spread volatility and default correlation. International Journal of Theoretical and Applied Finance12(07), 1007-1026.
 
[20] Cesari, G., Aquilina, J., Charpillon, N., Filipovic, Z., Lee, G., & Manda, I. (2009). Modelling, pricing, and hedging counterparty credit exposure: A technical guide. Springer Science & Business Media.
 
[21] Bielecki, T., Brigo, D., & Patras, F. (2011). Credit risk frontiers: Subprime crisis, pricing and hedging, CVA, MBS, ratings, and liquidity (Vol. 138). John Wiley & Sons.
 
[22] Lipton, A., & Rennie, A. (Eds.). (2013). The Oxford Handbook of Credit Derivatives. OUP Oxford.
 
[23] Brigo, D., Pede, N., & Petrelli, A. (2018). Multi currency credit default swaps: Quanto effects and fx devaluation jumps. Available at SSRN 2703605.