This paper focuses on operational risk measurement
techniques and on economic capital estimation methods. A data
sample of operational losses provided by an anonymous Central
European bank is analyzed using several approaches. Loss
Distribution Approach and scenario analysis method are considered.
Custom plausible loss events defined in a particular scenario are
merged with the original data sample and their impact on capital
estimates and on the financial institution is evaluated. Two main
questions are assessed – What is the most appropriate statistical
method to measure and model operational loss data distribution? and
What is the impact of hypothetical plausible events on the financial
institution? The g&h distribution was evaluated to be the most
suitable one for operational risk modeling. The method based on the
combination of historical loss events modeling and scenario analysis
provides reasonable capital estimates and allows for the measurement
of the impact of extreme events on banking operations.
[1] Arai T (2006): Key points of scenario analysis, Bank of Japan, 2006,
http://www.boj.or.jp/en/type/release/zuiji_new/data/fsc0608be2.pdf
[2] BCBS (2006): International Convergence of Capital Measurement and
Capital Standards, A Revised Framework, Comprehensive Version,
Basel Committee on Banking Supervision, Bank for International
Settlement, Basel June 2006, http://www.bis.org/publ/bcbs128.pdf
[3] Chalupka R, TeplÛ P (2008): Operational Risk Management and
Implications for Bank-s Economic Capital - A Case Study, IES Working
Papers 17/2008,
http://ies.fsv.cuni.cz/sci/publication/show/id/3477/lang/cs
[4] Chernobai A, Rachev S, Fabozzi F (2007): Operational Risk. A Guide
to Basel II Capital Requirements, Models and Analysis, John Willey &
Sons, Inc., March 2007, ISBN: 0470148780
[5] Cihak M (2004): Designing Stress Tests for the Czech Banking System,
CNB Internal Research and Policy Note 03/2004,
http://www.cnb.cz/en/research/research_publications/irpn/download/irpn
_3_2004.pdf
[6] de Fontnouvelle P, Jordan J, Rosengren E (2005): Implications of
Alternative Operation Risk Modeling Techniques, NBER Working Paper
Series, Cambridge February 2005
http://www.nber.org/papers/w11103.pdf
[7] de Fontnouvelle P, de Jesus-Rueff V, Jordan J, Rosengren E (2003):
Using Loss Data to Quantify Operational Risk, Technical report, Federal
Reserve Bank of Boston and Fitch Risk
[8] Degen M, Embrechts P, Lambrigger D (2007): The Quantitative
Modelling of Operational Risk: Between g-and-h and EVT, ETH Zurich
2007, http://www.math.ethz.ch/~degen/g-and-h.pdf
[9] Dutta K, Perry J (2007): A Tale of Tails: An Empirical Analysis of Loss
Distribution Models for Estimating Operational Risk Capital, Working
Paper 06-13, Federal Reserve Bank of Boston, Boston January 2007,
http://www.bos.frb.org/economic/wp/wp2006/wp0613.pdf
[10] Embrechts P, Frey R, McNeil A (2005): Quantitative Risk Management:
Concepts, Techniques and Tools, Princeton Series in Finance
[11] Jorion P (2007): Value at Risk: The New Benchmark for Managing
Financial Risk, 3rd edition, McGraw-Hill 2007
[12] Kuhn R, Neu P (2004): Adequate capital and stress testing for
operational risks, Dresdner Bank AG 2004,
http://www.gloriamundi.org/picsresources/rkpn2.pdf
[13] Mejstř├¡k M, Pe─ìen├í M, Tepl├¢ P (2008): "Basic Principles of Banking",
Karolinum Press, Prague.
[14] Mignola G, Ugoccioni R (2007): Statistical Approach to Operational
Risk Management, Sampolo IMI Group Italy 2007, http://www.rproject.
org/user-2006/Abstracts/Mignola+Ugoccioni.pdf
[15] Rippel M (2008): Operational Risk - Scenario Analysis, IES FSV UK
Diploma Thesis 2008
[16] Rippel M, TeplÛ P (2010): "Stress Testing and Scenario Analysis",
VDM Verlag, Saarbr├╝cken, Germany
[17] TeplÛ P (2010): "THE TRUTH ABOUT THE 2008-2009 CRISIS: A
Hard Lesson for The Global Markets", VDM Verlag, Saarbr├╝cken,
Germany
[18] Rosengren E (2006): Scenario analysis and the AMA, Federal Reserve
Bank of Boston, 2006,
http://www.bos.frb.org/bankinfo/qau/presentations/2006/er71906.pdf
[1] Arai T (2006): Key points of scenario analysis, Bank of Japan, 2006,
http://www.boj.or.jp/en/type/release/zuiji_new/data/fsc0608be2.pdf
[2] BCBS (2006): International Convergence of Capital Measurement and
Capital Standards, A Revised Framework, Comprehensive Version,
Basel Committee on Banking Supervision, Bank for International
Settlement, Basel June 2006, http://www.bis.org/publ/bcbs128.pdf
[3] Chalupka R, TeplÛ P (2008): Operational Risk Management and
Implications for Bank-s Economic Capital - A Case Study, IES Working
Papers 17/2008,
http://ies.fsv.cuni.cz/sci/publication/show/id/3477/lang/cs
[4] Chernobai A, Rachev S, Fabozzi F (2007): Operational Risk. A Guide
to Basel II Capital Requirements, Models and Analysis, John Willey &
Sons, Inc., March 2007, ISBN: 0470148780
[5] Cihak M (2004): Designing Stress Tests for the Czech Banking System,
CNB Internal Research and Policy Note 03/2004,
http://www.cnb.cz/en/research/research_publications/irpn/download/irpn
_3_2004.pdf
[6] de Fontnouvelle P, Jordan J, Rosengren E (2005): Implications of
Alternative Operation Risk Modeling Techniques, NBER Working Paper
Series, Cambridge February 2005
http://www.nber.org/papers/w11103.pdf
[7] de Fontnouvelle P, de Jesus-Rueff V, Jordan J, Rosengren E (2003):
Using Loss Data to Quantify Operational Risk, Technical report, Federal
Reserve Bank of Boston and Fitch Risk
[8] Degen M, Embrechts P, Lambrigger D (2007): The Quantitative
Modelling of Operational Risk: Between g-and-h and EVT, ETH Zurich
2007, http://www.math.ethz.ch/~degen/g-and-h.pdf
[9] Dutta K, Perry J (2007): A Tale of Tails: An Empirical Analysis of Loss
Distribution Models for Estimating Operational Risk Capital, Working
Paper 06-13, Federal Reserve Bank of Boston, Boston January 2007,
http://www.bos.frb.org/economic/wp/wp2006/wp0613.pdf
[10] Embrechts P, Frey R, McNeil A (2005): Quantitative Risk Management:
Concepts, Techniques and Tools, Princeton Series in Finance
[11] Jorion P (2007): Value at Risk: The New Benchmark for Managing
Financial Risk, 3rd edition, McGraw-Hill 2007
[12] Kuhn R, Neu P (2004): Adequate capital and stress testing for
operational risks, Dresdner Bank AG 2004,
http://www.gloriamundi.org/picsresources/rkpn2.pdf
[13] Mejstř├¡k M, Pe─ìen├í M, Tepl├¢ P (2008): "Basic Principles of Banking",
Karolinum Press, Prague.
[14] Mignola G, Ugoccioni R (2007): Statistical Approach to Operational
Risk Management, Sampolo IMI Group Italy 2007, http://www.rproject.
org/user-2006/Abstracts/Mignola+Ugoccioni.pdf
[15] Rippel M (2008): Operational Risk - Scenario Analysis, IES FSV UK
Diploma Thesis 2008
[16] Rippel M, TeplÛ P (2010): "Stress Testing and Scenario Analysis",
VDM Verlag, Saarbr├╝cken, Germany
[17] TeplÛ P (2010): "THE TRUTH ABOUT THE 2008-2009 CRISIS: A
Hard Lesson for The Global Markets", VDM Verlag, Saarbr├╝cken,
Germany
[18] Rosengren E (2006): Scenario analysis and the AMA, Federal Reserve
Bank of Boston, 2006,
http://www.bos.frb.org/bankinfo/qau/presentations/2006/er71906.pdf
@article{"International Journal of Business, Human and Social Sciences:63024", author = "Milan Rippel and Petr Teply", title = "Operational Risk – Scenario Analysis", abstract = "This paper focuses on operational risk measurement
techniques and on economic capital estimation methods. A data
sample of operational losses provided by an anonymous Central
European bank is analyzed using several approaches. Loss
Distribution Approach and scenario analysis method are considered.
Custom plausible loss events defined in a particular scenario are
merged with the original data sample and their impact on capital
estimates and on the financial institution is evaluated. Two main
questions are assessed – What is the most appropriate statistical
method to measure and model operational loss data distribution? and
What is the impact of hypothetical plausible events on the financial
institution? The g&h distribution was evaluated to be the most
suitable one for operational risk modeling. The method based on the
combination of historical loss events modeling and scenario analysis
provides reasonable capital estimates and allows for the measurement
of the impact of extreme events on banking operations.", keywords = "operational risk, scenario analysis, economic capital,loss distribution approach, extreme value theory, stress testing", volume = "4", number = "6", pages = "1430-8", }
