El OpVaR como medida del riesgo operacional

  1. Feria Domínguez, José Manuel
  2. Jiménez-Rodríguez, Enrique
  3. Martín Marín, José luis
Journal:
Boletín de estudios económicos

ISSN: 0006-6249

Year of publication: 2008

Issue Title: La internacionalización de la empresa

Volume: 63

Issue: 193

Pages: 135-159

Type: Article

More publications in: Boletín de estudios económicos

Abstract

In the last few years, bank industry has suffered from important losses due to operational failures. Being aware of that, in 2004 the Basel Committee published a New Capital Accord in which financial institutions were encouraged to measure, control and manage operational risk. In this context, Value at Risk (VaR) turns into essential for market risk measurement, this time applied to operational risk and, what is more important, for estimating capital requirements (Capital at Risk). In this paper, we focused on the Operational Value at Risk (OpVaR) measure and the methodological process for its estimation by using the Aggregate Loss Distribution approach (LDA).

Bibliographic References

  • ÁLVAREZ, P. (2001): “El Coeficiente de Solvencia de las Entidades de Crédito Españolas”, Estabilidad Financiera, Nº. 1, pp. 171-191, Banco de España, Septiembre.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2001): “Working Paper on the Regulatory Treatment of Operational Risk”, Nº. 8, Basilea, Septiembre.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2002): “Operational Risk Data Collection Exercise 2002”, Basilea, Junio.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2003): “Sound Practices for the Management and Supervision of Operational Risk”, Nº. 96, Basilea, Febrero.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2004): “International Convergence of Capital Measurement and Capital Standards: a Revised Framework”, Nº. 107, Basilea, Junio.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2005): “The Treatment of Expected Losses by Banks Using the AMA under the Basel II Framework”, Nº. 7, Basilea, Noviembre.
  • BASEL COMMITTEE ON BANKING SUPERVISION (2006): “Observed Range of Practice in Key Elements of Advanced Measurement Approaches (AMA)”, Basilea, Octubre.
  • BAUD, N.; FRACHOT, A. y RONCALLI, T. (2002): Internal Data, External Data and Consortium Data for Operational Risk Measurement: How to Pool Data Properly?, Documento de trabajo, Credit Lyonnais.
  • BÜHLMANN, H. (1970): “Mathematical Methods in Risk Theory”, Grundlehren Der Mathematischen Wissenschaften, Band 172, Springer-Verlag, Heidelberg.
  • CARRILLO, S. (2006): Riesgo Operacional: Medición y Control. Jornadas Técnicas sobre Basilea II, UNIA, Sevilla, Septiembre.
  • CEA, J.M. (2002): Mitigación del Riesgo Operacional. II Jornadas de Riesgos Financieros, Risklab, Madrid, Noviembre.
  • CHAPELLE (2006): Practical methods for measuring and managing operational risk in the financial sector: A clinical study, Documento de trabajo nº 200611/13, Ecole de Gestion de l’Univerite de Liege.
  • CHERNOBAI, A.; RACHEV, S. T. y FABOZZI, F. J. (2005): Composite goodness-of-fit tests for left-truncated loss samples. Technical Report, University of California, Santa Barbara.
  • DA COSTA, N. (2004): Operational Risk with Excel and VBA. John Wiley & Sons.
  • D’AGOSTINO, R. B. y STEPHENS, M. A. (1986): Goodness-of-fit Techniques. Dekker, New York.
  • FERIA, J.M. (2005): El Riesgo de Mercado su Medición y Control. Delta Publicaciones, Madrid.
  • FONTNOUVELLE, P.; DEJESUS-RUEFF, V.; ROSENGREN, E. y JORDAN, J. (2003): Using Loss Data to Quantify Operational Risk. Working Paper. Federal Reserve Bank of Boston.
  • FONTNOUVELLE, P.; ROSENGREN, E. y JORDAN, J. (2004): Implications of Alternative Operational Risk Modeling Techniques. Working Paper. Federal Reserve Bank of Boston.
  • FRACHOT, A.; GEORGES, P. y RONCALLI, T. (2001): Loss Distribution Approach for Operational Risk. Documento de trabajo, Credit Lyonnais.
  • FRACHOT, A.; MOUDOULAUD, O. y RONCALLI, T. (2003): Loss Distribution Approach in Practice. Documento de trabajo, Credit Lyonnais.
  • GARMAN, M. y BLANCO, C. (1998): “Nuevos Avances en la Metodología de Valor en Riesgo: Conceptos de Verdelta y Verbeta”, Revista Análisis Financiero, nº 75.
  • GUSTAFSSON, J.; GUILLEN, M.; NIELSEN, J.P. y PRITCHARD, P. (2005): Using external data in the calculation of operational risk capital requirements with particular reference to under-reporting. Working Paper, Social Science Research Network (SSRN).
  • INSTEFJORD, N. y PERRAUDIN, W. (1998): Securities Fraud and Irregularities: Case Studies and Issues for Senior Management. Operational Risk and Financial Institutions, pp. 147-158, Arthur Andersen, Risk Books, London.
  • HOFFMAN, D.G. (1998): New Trends in Operational Risk Measurement and Management. Operational Risk and Financial Institutions, pp. 29-42, Arthur Andersen, Risk Books, London.
  • JORION, P. (1997): Value at Risk: the New Benchmark for Controlling Derivatives Risk, McGraw-Hill.
  • KLUGMAN, S.; PANJER, H. y WILLMOT, G. (2004): Loss Models: from Data to Decisions. 2ª ed. John Wiley & Sons, New York.
  • MARSHALL, C. y SIEGEL, M. (1997): “Value at Risk: Implementing a Risk Measurement Standard”, The Journal of Derivatives, volumen 4, nº3, pág. 91- 110.
  • MIGNOLA, G. y UGOCCIONI, R. (2006): “Sources of uncertainty in modelling operational risk losses”, Journal of Operational Risk, Volumen 1, Número 2, pág. 33–50.
  • MOSCADELLI, M. (2004): The Modelling of Operational Risk: Experience with the Analysis of the Data Collected by the Basel Committee”. Documento de Trabajo del Banco de Italia.
  • NIETO, M.A. (2005): “El Tratamiento del Riesgo Operacional en Basilea II”, Estabilidad Financiera, Nº. 8, pp. 164-185, Mayo.
  • PANJER, H. (1981): “Recursive evaluation of a family of coumpound distributions”, Astin Bulletin 12.
  • PANJER, H. (2006): Operational Risk. Modelling Analytics, John Wiley & Sons.
  • SCHWARZ, G. (1978): “Estimating the dimension of a model”, Annals of Statistics, nº 6, 461–464.
  • VARGAS, F. (2001): “Introducción al Pilar 1 de Basilea II”, Estabilidad Financiera, Nº. 1, p. 59-92, Septiembre.