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Functional correlation approach to operational risk in banking organizations

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  • Kühn, Reimer
  • Neu, Peter

Abstract

A Value-at-Risk-based model is proposed to compute the adequate equity capital necessary to cover potential losses due to operational risks, such as human and system process failures, in banking organizations. Exploring the analogy to a lattice gas model from physics, correlations between sequential failures are modeled by as functionally defined, heterogeneous couplings between mutually supportive processes. In contrast to traditional risk models for market and credit risk, where correlations are described as equal-time-correlations by a covariance matrix, the dynamics of the model shows collective phenomena such as bursts and avalanches of process failures.

Suggested Citation

  • Kühn, Reimer & Neu, Peter, 2003. "Functional correlation approach to operational risk in banking organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 322(C), pages 650-666.
    • Handle: RePEc:eee:phsmap:v:322:y:2003:i:c:p:650-666
    DOI: 10.1016/S0378-4371(02)01822-8
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
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    Cited by:

    1. Dalla Valle, L. & Giudici, P., 2008. "A Bayesian approach to estimate the marginal loss distributions in operational risk management," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3107-3127, February.
    2. Marco Bardoscia & Roberto Bellotti, 2012. "A Dynamical Approach to Operational Risk Measurement," Papers 1202.2532, arXiv.org.
    3. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    4. Wang, Zongrun & Wang, Wuchao & Chen, Xiaohong & Jin, Yanbo & Zhou, Yanju, 2012. "Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks," Economic Modelling, Elsevier, vol. 29(6), pages 2095-2103.
    5. Lu, Zhaoyang, 2011. "Modeling the yearly Value-at-Risk for operational risk in Chinese commercial banks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 604-616.
    6. Deepak Tandon & Yogieta S. Mehra, 2017. "Impact of Ownership and Size on Operational Risk Management Practices: A Study of Banks in India," Global Business Review, International Management Institute, vol. 18(3), pages 795-810, June.
    7. Neu, Peter & Kühn, Reimer, 2004. "Credit risk enhancement in a network of interdependent firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 639-655.
    8. Xu, Chi & Zheng, Chunling & Wang, Donghua & Ji, Jingru & Wang, Nuan, 2019. "Double correlation model for operational risk: Evidence from Chinese commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 327-339.
    9. Luciana Dalla Valle, 2009. "Bayesian Copulae Distributions, with Application to Operational Risk Management," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 95-115, March.

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