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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 2 Issue 6 pp. 1895-1900 , 2012

An empirical study to measure the effects of various factors on operating loss Pages 1895-1900 Right click to download the paper Download PDF

Authors: Mohammad Khodaei Valahzaghard, Maryam Khalili Araghi, Seyyed Mahmoud Golampour Papkiyadeh, Saeeid Khodaei Valahzaghard

DOI: 10.5267/j.msl.2012.06.034

Keywords: Bank Mellat, Basel II, Operational Risk

Abstract: In this paper, we present an empirical investigation to measure the effects of various factors on operating loss in one of major Iranian banks called Bank Mellat. The proposed study of this paper uses a standard questionnaire and distributes it among 57 people who are mainly in top management levels. The questions are categorized into five groups including events related to the processes and methods, events outside the organization, related events within the organization and business disruptions and system failure. The results of our survey confirm that the loss associated with events related to the processes and methods increases operating risk meaningfully, the loss associated with business disruptions and system failure increases operating risk meaningfully and the loss associated with related events within the organization increases operating risk meaningfully. However, our survey do not confirm that the loss associated with events outside the organization increase operating, risk meaningfully. Finally, the preliminary survey of our analysis shows that there is not enough evidence to believe that the effects of business disruption and internal affairs are significantly different from the other event.

How to cite this paper
Valahzaghard, M., Araghi, M., Papkiyadeh, S & Valahzaghard, S. (2012). An empirical study to measure the effects of various factors on operating loss.Management Science Letters , 2(6), 1895-1900.

Refrences
Aquaro, V., Bardoscia, M., Bellotti, R., Consiglio, A., De Carlo, F., & Ferri, G. (2010). A Bayesian Networks approach to Operational Risk. Physica A: Statistical Mechanics and its Applications, 389(8), 1721-1728.

Chavez-Demoulin, V., Embrechts, P., & Ne?lehov?, J. (2006). Quantitative models for operational risk: Extremes, dependence and aggregation. Journal of Banking & Finance, 30(10), 2635-2658.

Chateau, J.P.D. (2009). Marking-to-model credit and operational risks of loan commitments: A Basel-2 advanced internal ratings-based approach. International Review of Financial Analysis, 18(5), 260-270.

Feng-ge, Y., & Ping, Z. (2012). The measurement of operational risk based on CVaR: A decision engineering technique. Systems Engineering Procedia, 4, 438-447.

Jiménez-Rodr?guez, E.J., Feria-Dom?nguez, J.M., & Mart?n-Marin, J.L. (2011). The regulatory loss cut-off level: Does it undervalue the operational capital at risk? The Spanish Review of Financial Economics, 9(2), 49-54.

Peters, G.W., Shevchenko, P.V., Young, M., & Yip, W. (2011). Analytic loss distributional approach models for operational risk from the -stable doubly stochastic compound processes and implications for capital allocation. Insurance: Mathematics and Economics, 49(3), 565-579.

Wahlstr?m, G. (2009). Risk management versus operational action: Basel II in a Swedish context. Management Accounting Research, 20(1), 53-68.

Xie, Y., Wu, Y.W., & Hu, Y.C. (2011). The Engineering of China Commercial Bank Operational Risk Measurement. Systems Engineering Procedia, 1, 330-336.
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Journal: Management Science Letters | Year: 2012 | Volume: 2 | Issue: 6 | Views: 1808 | Reviews: 0

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