Linking the problems of estimating and allocating unconditional capital

  1. Ferrer Pérez, Alejandro
  2. Sotoca López, Sonia
  3. Casals Carro, José
Revista:
Documentos de Trabajo (ICAE)

ISSN: 2341-2356

Año de publicación: 2014

Número: 13

Páginas: 1-12

Tipo: Documento de Trabajo

DIALNET GOOGLE SCHOLAR lock_openDocta Complutense editor

Otras publicaciones en: Documentos de Trabajo (ICAE)

Resumen

This paper addresses two problems related to determining the unconditional capital required by a credit portfolio: Estimating it using Monte Carlo simulation and allocating it among the different risk units that form the portfolio. By elaborating on a tractable analytical framework, we propose a new simulation algorithm and a new allocation method. Both contributions rely on the conditional loss distributions and share the same core idea. We discuss their optimality, consistence and practical advantages. In an empirical study based on American data, we show the remarkable gains in efficiency achieved by the former and the improvement in the standard variance-covariance allocation provided by the latter.

Referencias bibliográficas

  • Artzner, P., Delbaen, F., Eber, J., Heath, D., 1999. Coherent measures of risk. Mathematical Finance 9 (3), 203–228.
  • BCBS, 2009. Range of practices and issues in economic capital frameworks. BCBS Working Papers.
  • BCBS, 2011. Basel III: A global regulatory framework for more resilient banks and banking systems - revised version. Bank for International Settlements.
  • Breuer, T., Jandacka, M., Rheinberger, K., Summerb, M., 2009. How to find plausible, severe, and useful stress scenarios. International Journal of Central Banking 5 (3), 205–224.
  • Cherny, A., 2009. Capital allocation and risk contribution with discrete-time coherent risk. Mathematical Finance 19 (1), 13–40.
  • Denault, M., 2001. Coherent allocation of risk capital. The Journal of Risk 4, 1–34.
  • Duffie, D., Saita, L., Wang, K., 2007. Multi-period corporate default prediction with stochastic covariates. Journal of Financial Economics 83 (3), 635–665.
  • Fernández, F. J., Harvey, A. C., 1990. Seemingly unrelated time series equations and a test for homogeneity. Journal of Business & Economic Statistics 8 (1), 71–81.
  • Ferrer, A., Casals, J., Sotoca, S., 2014. A new approach to the unconditional measurement of default risk. ICAE Working Papers.
  • Frey, R., McNeil, A., 2003. Dependent defaults in models of portfolio credit risk. The Journal of Risk 6, 59–92.
  • Frey, R., Popp, M., Weber, S., 2008. An approximation for credit portfolio losses. The Journal of Credit Risk 4 (1), 59–76.
  • Glasserman, P., 2004a. Monte Carlo methods in financial engineering. Springer Verlag.
  • Glasserman, P., 2004b. Tail approximations for portfolio credit risk. The Journal of Derivatives 12 (2), 24–42.
  • Glasserman, P., Kang, W., Shahabuddin, P., 2008. Fast simulation of multifactor portfolio credit risk. Operations Research 56 (5), 1200–1217.
  • Glasserman, P., Li, J., 2005. Importance sampling for portfolio credit risk. Management Science 51 (11), 1643–1656.
  • Gordy, M., 2000. A comparative anatomy of credit risk models. Journal of Banking & Finance 24 (1-2), 119–149.
  • Gordy, M., 2003. A risk-factor model foundation for ratings-based bank capital rules. Journal of Financial Intermediation 12 (3), 199–232.
  • Heitfield, E., Burton, S., Chomsisengphet, S., 2006. Systematic and idiosyncratic risk in syndicated loan portfolios. The Journal of Credit Risk 2 (3), 3–31.
  • Kalkbrener, M., 2005. An axiomatic approach to capital allocation. Mathematical Finance 15 (3), 425–437.
  • Kalkbrener, M., Lotter, H., Overbeck, L., 2004. Sensible and efficient capital allocation for credit portfolios. Risk 17 (1), 19–24.
  • Kish, L., 1965. Survey Sampling. New York: Wiley. Koopman, S., Lucas, A., 2005. Business and default cycles for credit risk. Journal of Applied Econometrics 20 (2), 311–323.
  • Laeven, R., Goovaerts, M., 2004. An optimization approach to the dynamic allocation of economic capital. Insurance: Mathematics and Economics 35 (2), 299–319.
  • Mausser, H., Rosen, D., 2007. Economic credit capital allocation and risk contributions. In: Birge, J. R., Linetsky, V. (Eds.), Financial Engineering. Vol. 15 of Handbooks in Operations Research and Management Science. Elsevier, pp. 681 – 726.
  • Merino, S., Nyfeler, M., 2004. Applying importance sampling for estimating coherent credit risk contributions. Quantitative Finance 4 (2), 199–207.
  • Nyström, K., Skoglund, J., 2006. A credit risk model for large dimensional portfolios with application to economic capital. Journal of Banking & Finance 30 (8), 2163–2197.
  • Pesaran, M., Schuermann, T., Treutler, B., Weiner, S., 2006. Macroeconomic dynamics and credit risk: a global perspective. Journal of Money, Credit, and Banking 38 (5), 1211–1261.
  • Riedel, F., 2004. Dynamic coherent risk measures. Stochastic Processes and their Applications 112 (2), 185–200.
  • Stoughton, N., Zechner, J., 2007. Optimal capital allocation using RAROC and EVA. Journal of Financial Intermediation 16 (3), 312–342.
  • Tasche, D., 2007. Capital allocation to business units and subportfolios: The Euler principle. In: Books, R. (Ed.), Pillar II in the New Basel Accord: The Challenge of Economic Capital. pp. 423–453.
  • Vasicek, O., 2002. The distribution of loan portfolio value. Risk 15 (12), 160–162. Wilson, T., 1997a. Credit portfolio risk I. Risk 10 (9), 111–117.
  • Wilson, T., 1997b. Credit portfolio risk II. Risk 10 (10), 56–61.
  • Yamai, Y., Yoshiba, T., 2005. Value-at-risk versus expected shortfall: A practical perspective. Journal of Banking & Finance 29 (4), 997–1015.
  • Zhou, C., 2010. Dependence structure of risk factors and diversification effects. Insurance: Mathematics and Economics 46 (3), 531–540.
Fuente de los datos: Dialnet