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On the aggregation of credit, market and operational risks

Published on Jan 1, 2015in Review of Quantitative Finance and Accounting
· DOI :10.1007/s11156-013-0426-0
Jianping LiXiaolei19
Estimated H-index: 19
(CAS: Chinese Academy of Sciences),
Xiaoqian Zhu7
Estimated H-index: 7
(CAS: Chinese Academy of Sciences)
+ 3 AuthorsYong Shi39
Estimated H-index: 39
(CAS: Chinese Academy of Sciences)
Cite
Abstract
Risk aggregation considering inter-risk dependence has always been a challenge to both researchers and practitioners. The objective of this study is to formulate ways of aggregation of bank risks and comprehensively compare simple summation, variance–covariance and copula approach. Firstly, the three popular approaches are adopted to aggregate credit risk, market risk and operational risk of banks based on Austrian banking data. Then, two comparisons are mainly made. Total risks aggregated by different approaches are compared to analyze their relative magnitudes. Diversification benefits of different approaches are further compared to investigate their tail dependence structures. Based on the empirical analysis, some facts are verified and some interesting findings are uncovered, leading to the conclusions that simple summation approach is too conservative and variance–covariance approach is overly optimistic, so it is suggested that copula approach is the future major trend for bank risk aggregation. Especially, t copula with degree of freedom between 1 and 10 is a good choice to capture tail dependence while Gaussian copula is not recommended. Besides, the proposed mixture copula consisting of t copula and Gumbel copula exhibits heavier right tail dependence than single t copula.
  • References (51)
  • Citations (18)
Cite
References51
Newest
Meichi Huang1
Estimated H-index: 1
(NTPU: National Taipei University),
Chih-Chiang Wu1
Estimated H-index: 1
(YZU: Yuan Ze University)
The study delivers new implications for risk management and asset allocation by investigating extreme dependences between real estate investment trust (REIT) and stock returns, where ‘extreme dependences’ refer to cross-asset linkages during extraordinary periods. It primarily differentiates itself from prior studies in three respects. First, it examines the role of asymmetric extreme dependences in establishing an optimal investment portfolio during the 2000–2010 period. Second, it provides an ...
Gregor N.F. Weiß11
Estimated H-index: 11
(Technical University of Dortmund)
In this paper, we analyze the accuracy of the copula-GARCH and Dynamic Conditional Correlation (DCC) models for forecasting the value-at-risk (VaR) and expected shortfall (ES) of bivariate portfolios. We then try to answer two questions: First, does the correlation-based DCC model outperform the copula models? Second, how can the optimal model for forecasting portfolio risk be identified via in-sample analysis? We address these questions using an extensive empirical study of 1,500 bivariate port...
Published on Jun 1, 2013in International Review of Economics & Finance1.43
Yi-Hsuan Chen3
Estimated H-index: 3
(CHU: Chung Hua University),
Anthony H. Tu1
Estimated H-index: 1
The conventional portfolio value-at-risk model with the assumption of normal joint distribution, which is commonly practiced, exhibits considerable biases due to model specification errors. This paper utilizes the estimation of hedged portfolio value-at-risk (HPVaR) to illustrate the potential model risk due to inappropriate use of the correlation coefficient and normal joint distribution between index spot and futures returns. The results show that HPVaR estimation can be improved by using the ...
Jianping LiXiaolei19
Estimated H-index: 19
,
Jichuang Feng6
Estimated H-index: 6
+ 1 AuthorsMinglu Li6
Estimated H-index: 6
Recently, the number of consultative documents and research papers that discuss risk integration has grown considerably. This paper presents a comprehensive review of the work done on risk integration in the banking industry. This survey includes: (1) risk integration methods within regulatory frameworks and the banking industry; (2) challenges of risk integration; (3) risk interaction mechanisms; (4) development of risk integration approaches; (5) risk interaction results: diversification versu...
Published on Mar 1, 2012in Journal of Banking and Finance2.21
William Francis4
Estimated H-index: 4
(Federal Reserve System),
Matthew Osborne7
Estimated H-index: 7
(Financial Services Authority)
The financial crisis prompted widespread interest in developing a better understanding of how capital regulation drives bank behavior. This paper uses a unique, comprehensive database of regulatory capital requirements on all UK banks to examine their effects on capital, lending and balance sheet management behavior. We find that capital requirements that include firm-specific, time-varying add-ons set by supervisors affect banks’ desired capital ratios and that resulting adjustments to capital ...
Published on Sep 1, 2011in Metrika0.64
Matthias Meyer10
Estimated H-index: 10
(TUHH: Hamburg University of Technology),
Cathérine Grisar2
Estimated H-index: 2
(TUHH: Hamburg University of Technology),
Felix Kuhnert2
Estimated H-index: 2
(WHU - Otto Beisheim School of Management)
This paper develops a systematic approach to quantifying the effect of judgmental biases on aggregate risk measures. Starting with the standard risk management process, we derive the areas that require expert judgment as input in order to aggregate risk into risk measures such as Earnings at Risk. We specify three possible gateways for biases and identify several psychological theories to quantify deviations of expert judgments from objective probabilities. The impact of these cognitive biases o...
Published on Jun 1, 2011in Journal of Banking and Finance2.21
Paula Antão4
Estimated H-index: 4
(Banco de Portugal),
Ana Lacerda3
Estimated H-index: 3
(Banco de Portugal)
This work aims to study the hypothesis of lower capitalization of banks under the risk-based rules introduced in Basel II. In this sense, an assessment of the impact of these rules on the capital requirements for non-financial firms' credit risk is performed. A comparison with Basel I is presented and intervals of variation for the risk drivers such that capital requirements exceed the ones under Basel I are established. Data for a European country supports the hypothesis of a smaller capitaliza...
Published on Dec 1, 2010in Journal of Banking and Finance2.21
Gavin Lee Kretzschmar7
Estimated H-index: 7
(Edin.: University of Edinburgh),
Alexander J. McNeil32
Estimated H-index: 32
,
Axel Kirchner6
Estimated H-index: 6
With the majority of large UK and many US banks collapsing or being forced to raise capital over the 2007-9 period, blaming bankers may be satisfying but is patently insufficient; Basel II and Federal oversight frameworks also deserve criticism. We propose that the current methodological void at the heart of Basel II, Pillar 2 is filled with the recommendation that banks develop fully-integrated models for economic capital that relate asset values to fundamental drivers of risk in the economy to...
Published on Jun 1, 2010in European Journal of Operational Research3.81
Peter Grundke5
Estimated H-index: 5
(University of Osnabrück)
Banks and other financial institutions try to compute the necessary amount of total capital that they need for absorbing stochastically dependent losses from different risk types (e.g., credit risk and market risk). Two sophisticated procedures of this so-called integrated risk management are the top-down and the bottom-up approaches. When banks apply a more sophisticated risk integration approach at all, it is usually the top-down approach where copula functions are employed for linking the mar...
Published on May 30, 2010
Jimmy Skoglund4
Estimated H-index: 4
(SAS: SAS Institute)
Risk management for banks involves risk measurement and risk control at the individual risk level, including market risk for trading books, credit risk for trading and banking books, operational risks and aggregate risk management. In many banks, aggregate risk is defined using a rollup or risk aggregation model; capital, as well as capital allocation, is based on the aggregate risk model. The aggregate risk is the basis for defi ning a bank’s economic capital, and is used in value-based managem...
Cited By18
Newest
Lu Wei2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences),
Guowen Li2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences)
+ 1 AuthorsXiaoqian Zhu7
Estimated H-index: 7
(CAS: Chinese Academy of Sciences)
Abstract Approaches based on financial statements are important to the field of bank risk aggregation. However, previous studies only used numerical data recorded in financial statements to aggregate bank risk. Time lags in numerical data can bias risk aggregation results. Thus, this paper first incorporates forward-looking textual risk disclosures reported in financial statements into bank risk aggregation. In doing so, we overcome the drawback of risk aggregation resulting from using only hist...
Published on Feb 19, 2019in Accounting and Finance1.48
Lu Wei2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences),
Guowen Li2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences)
+ 1 AuthorsJianping LiXiaolei19
Estimated H-index: 19
(CAS: Chinese Academy of Sciences)
Published on Mar 31, 2019in Journal of Risk Research1.70
Chunbing Bao3
Estimated H-index: 3
,
Jie Wan1
Estimated H-index: 1
+ 1 AuthorsJianping LiXiaolei19
Estimated H-index: 19
AbstractRisk matrices have been proven as useful risk management tools, especially in the cases where data are not sufficient. Current usage of risk matrices in both literature and practice is related to single risk assessment. However, sometimes the decision makers care more about the overall risk consisting of several of single risks, which is in the scope of the aggregation of single risks measured by risk matrices. Unfortunately, two notions, namely, incomparability of different qualitative ...
Xiaoqian Zhu7
Estimated H-index: 7
(CAS: Chinese Academy of Sciences),
Jianping LiXiaolei19
Estimated H-index: 19
(CAS: Chinese Academy of Sciences),
Dengsheng Wu10
Estimated H-index: 10
(CAS: Chinese Academy of Sciences)
The Basel Committee on Banking Supervision (BCBS) states that in addition to the fact that it lacks simplicity, the Advanced Measurement Approach (AMA) must be discarded because the flexibility of ...
Published on Sep 1, 2018in Annals of Data Science
Lu Wei2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences),
Jianping LiXiaolei19
Estimated H-index: 19
(CAS: Chinese Academy of Sciences),
Xiaoqian Zhu7
Estimated H-index: 7
(CAS: Chinese Academy of Sciences)
This paper is the first to provide a comprehensive overview of the worldwide operational loss data collection exercises (LDCEs) of internal loss, external loss, scenario analysis and business environment and internal control factors (BEICFs). Based on analyzing operational risk-related articles from 2002 to March 2017 and surveying a large amount of other information, various sources of operational risk data are classified into five types, i.e. individual banks, regulatory authorities, consortia...
Jianping LiXiaolei19
Estimated H-index: 19
(CAS: Chinese Academy of Sciences),
Lu Wei2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences)
+ 2 AuthorsDengsheng Wu10
Estimated H-index: 10
(CAS: Chinese Academy of Sciences)
Abstract One of the major challenges involved in risk aggregation is the lack of risk data. Recently, researchers have found that mapping financial statements into risk types is a satisfactory way to resolve the problem of data shortage and inconsistency. Nevertheless, ignoring off-balance sheet (OBS) items has so far been regarded as the usual practice in risk aggregation, which may lead to deviations in conclusions. Hence, we improve the financial statements based risk aggregation framework by...
Published on Jan 1, 2018in Information Sciences5.52
Jie Sun2
Estimated H-index: 2
(TUFE: Tianjin University of Finance and Economics),
Jie Lang1
Estimated H-index: 1
(ZJNU: Zhejiang Normal University)
+ 1 AuthorsHui Li2
Estimated H-index: 2
(NKU: Nankai University)
Abstract Enterprise credit evaluation model is an important tool for bank and enterprise risk management, but how to construct an effective decision tree (DT) ensemble model for imbalanced enterprise credit evaluation is seldom studied. This paper proposes a new DT ensemble model for imbalanced enterprise credit evaluation based on the synthetic minority over-sampling technique (SMOTE) and the Bagging ensemble learning algorithm with differentiated sampling rates (DSR), which is named as DTE-SBD...
Published on Jan 1, 2018in Procedia Computer Science
Yinghui Wang1
Estimated H-index: 1
(CAS: Chinese Academy of Sciences),
Guowen Li2
Estimated H-index: 2
(CAS: Chinese Academy of Sciences)
+ 1 AuthorsXiaoqian Zhu7
Estimated H-index: 7
(CAS: Chinese Academy of Sciences)
Abstract Operational risk events occur in almost all processes of bank’s operation and management. Due to the dispersion and complexity of operational risk, few previous studies answer how many types of factors affect bank operational risk totally. This paper first introduces the text mining approach into operational risk domain to comprehensively identify risk factors leading to operational risk from textual risk disclosures. Based on 36573 risk factor headings from 1264 Form 10-K of 158 U.S. b...
Published on Sep 1, 2017in Economic Modelling2.06
Miloš Božović3
Estimated H-index: 3
(University of Belgrade),
Jelena Ivanović
This paper studies adverse interaction between credit and market risk. We develop a comprehensive Merton-type model, in which payment ability of borrowers is driven by the overall economic growth, while the level of their liabilities is sensitive to market variables. To illustrate the model, we apply numerical simulations to estimate credit, market and integrated Value at Risk from the loss distribution using industry-wide data from the Serbian banking sector. We show that—even after accounting ...
Hanène Mejdoub1
Estimated H-index: 1
(Tunis University),
Mounira Ben Arab1
Estimated H-index: 1
(College of Business Administration)
The purpose of this paper is to provide an extension to recent contributions in the field of quantitative risk management by modeling non-life insurance risks in a multivariate framework. This contribution examines the impact of explicit dependence modeling among non-life insurance losses on capital requirement. First, we focus on the modeling of dependence structure using copulas when the losses from the different business lines are dependent in some sense. Second, we concentrate on Value-at-Ri...
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