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The use of coherent risk measures in operational risk modeling
Lebovič, Michal ; Teplý, Petr (advisor) ; Doležel, Pavel (referee)
The debate on quantitative operational risk modeling has only started at the beginning of the last decade and the best-practices are still far from being established. Estimation of capital requirements for operational risk under Advanced Measurement Approaches of Basel II is critically dependent on the choice of risk measure, which quantifies the risk exposure based on the underlying simulated distribution of losses. Despite its well-known caveats Value-at-Risk remains a predominant risk measure used in the context of operational risk management. We describe several serious drawbacks of Value-at-Risk and explain why it can possibly lead to misleading conclusions. As a remedy we suggest the use of coherent risk measures - and namely the statistic known as Expected Shortfall - as a suitable alternative or complement for quantification of operational risk exposure. We demonstrate that application of Expected Shortfall in operational loss modeling is feasible and produces reasonable and consistent results. We also consider a variety of statistical techniques for modeling of underlying loss distribution and evaluate extreme value theory framework as the most suitable for this purpose. Using stress tests we further compare the robustness and consistency of selected models and their implied risk capital estimates...
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Cyber risk modelling using copulas
Spišiak, Michal ; Teplý, Petr (advisor) ; Baruník, Jozef (referee)
Cyber risk or data breach risk can be estimated similarly as other types of operational risk. First we identify problems of cyber risk models in existing literature. A large dataset consisting of 5,713 loss events enables us to apply extreme value theory. We adopt goodness of fit tests adjusted for distribution functions with estimated parameters. These tests are often overlooked in the literature even though they are essential for correct results. We model aggregate losses in three different industries separately and then we combine them using a copula. A t-test reveals that potential one-year global losses due to data breach risk are larger than the GDP of the Czech Republic. Moreover, one-year global cyber risk measured with a 99% CVaR amounts to 2.5% of the global GDP. Unlike others we compare risk measures with other quantities which allows wider audience to understand the magnitude of the cyber risk. An estimate of global data breach risk is a useful indicator not only for insurers, but also for any organization processing sensitive data.
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Assessment of cyber risk in the banking industry
Spišiak, Michal ; Teplý, Petr (advisor) ; Maršál, Aleš (referee)
There has never been more need to discuss cybersecurity related issues. We live in a world where criminals do not have to physically visit a bank to steal money from it, where elections results can be influenced by data breached from personal email accounts, where to win a war a country needs skilled cybersecurity specialists rather than powerful weapons and where patients do not get recommended treatment because a hospital is under a cyberattack. The financial industry as a backbone of any modern economy requires adequate protection against cybercrime. We discuss major cyber threats for financial institutions as well as possible protection methods. After that we introduce Basel II Framework for operational risk assessment and we evaluate data breach risk in an empirical analysis. 1
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LDA approach to operational risk modelling
Kaplanová, Martina ; Mazurová, Lucie (advisor) ; Zichová, Jitka (referee)
In this thesis we will deal with the term of operational risk, as it is presented in the directives Basel 2 that are mandatory for financial institutions in the European Union. The main problem is operational risk modeling, therefore, how to measure and manage it. In the first part we will look at the possibility of calculating the capital requirements for operational risk under Basel 2, mainly the calculation with the internal model. We will describe the specific procedures for the development of the internal model and we will focus on Loss Distribution Approach. The internal model will be based on modeling of loss in each risk cell separately. In the second part we will show, how to include modeling of dependence structure between risk cells to the internal model with using copulas. Finally, we will show the illustrative example, where we will see, whether the modeling of dependence leads to a reduction of the total capital requirement. Powered by TCPDF (www.tcpdf.org)
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Methods of Risk Aggregation on Financial Markets
Pavlovičová, Jana ; Gapko, Petr (advisor) ; Báťa, Karel (referee)
This diploma thesis "Methods of risk aggregation on financial markets" introduces all kinds of risk that are present on the financial markets. In the first part there are explained the ways and methods of measurement of these risks. Next there are shown the methods of aggregation of credit, market and operational risks. One of these methods are copula functions which are constructed in practical part of this thesis.
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The use of coherent risk measures in operational risk modeling
Lebovič, Michal ; Teplý, Petr (advisor) ; Doležel, Pavel (referee)
The debate on quantitative operational risk modeling has only started at the beginning of the last decade and the best-practices are still far from being established. Estimation of capital requirements for operational risk under Advanced Measurement Approaches of Basel II is critically dependent on the choice of risk measure, which quantifies the risk exposure based on the underlying simulated distribution of losses. Despite its well-known caveats Value-at-Risk remains a predominant risk measure used in the context of operational risk management. We describe several serious drawbacks of Value-at-Risk and explain why it can possibly lead to misleading conclusions. As a remedy we suggest the use of coherent risk measures - and namely the statistic known as Expected Shortfall - as a suitable alternative or complement for quantification of operational risk exposure. We demonstrate that application of Expected Shortfall in operational loss modeling is feasible and produces reasonable and consistent results. We also consider a variety of statistical techniques for modeling of underlying loss distribution and evaluate extreme value theory framework as the most suitable for this purpose. Using stress tests we further compare the robustness and consistency of selected models and their implied risk capital estimates...
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Cyber risk in banking
Linert, Jan ; Teplý, Petr (advisor) ; Stádník, Bohumil (referee)
The bachelor thesis deals with the cyber risk in banking industry. Its main goal is to stress the imporatance of cyber risk both verbally and numericaly and review the approach of banks to this risk. The first part of this thesis specifies what cyber risk is and how it fits among other operational risks, presents the common cyber-attacks and archetypes of cyber criminals, later it delves into the cyber risk in Czech Republic and at the end of this part it mentions the legislation that covers the cyber risk. The second part of this thesis examines the cyber risk from three different angles: the amount of security threats from the analyses of security experts, the importance of cyber risk to the bankers from market analyses and evolution of the regulatory capital for operational risk from annual reports of chosen banks and the statistical data of EBA, ECB and ČNB.
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Managing operational risk using scenario analysis
Vostatek, Jan ; Blahová, Naděžda (advisor) ; Brada, Jaroslav (referee)
The master thesis is dealing with the contemporary issues of operational risk management in financial institutions. Author sets a theoretical basis and legal background of the topic and describes the contemporary practices of managing the operational risk. Author focuses on the scenario analysis as a specific method which is described and evaluated. Scenario analysis is applied on the rogue trading risk. In the thesis there is created a model institution on which author applies the operational risk theory using best practices and expert opinions. The model situation provides the analysis of the processes of the financial institution and choose the suitable measures in order to defend against the risk. The author also analyses the past cases of rogue trading which helps to understand the prevention and the historical significance of the operational risk.
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