The mutual-information-based variance–covariance approach: an application to operational risk aggregation in Chinese banking

2014 ◽  
Vol 9 (3) ◽  
pp. 3-19 ◽  
Author(s):  
Jianping Li ◽  
Xiaoqian Zhu ◽  
Yongjia Xie ◽  
Jianming Chen ◽  
Lijun Gao ◽  
...  
Keyword(s):  
Mutual Information ◽  
Operational Risk ◽  
Risk Aggregation ◽  
Chinese Banking

scholarly journals Operational Risk Aggregation Based on Business Line Dependence: A Mutual Information Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Wenzhou Wang ◽  
Limeng Shi ◽  
Xiaoqian Zhu
Keyword(s):  
Mutual Information ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Risk Estimation ◽  
Pearson Correlation ◽  
Operational Risk ◽  
Random Variable ◽  
Data Set ◽  
Risk Aggregation ◽  
Business Line

The dependencies between different business lines of banks have serious effects on the accuracy of operational risk estimation. Furthermore, the dependencies are far more complicated than simple linear correlation. While Pearson correlation coefficient is constructed based on the hypothesis of a linear association, the mutual information that measures all the information of a random variable contained in another random variable is a powerful alternative. Based on mutual information, the generalized correlation coefficient which can capture both linear and nonlinear correlation can be derived. This paper models the correlation between business lines by mutual information and normal copula. The experiment on a real-world Chinese bank operational risk data set shows that using mutual information to model the dependencies between business lines is more reasonable than linear correlation.

scholarly journals Operational Risk Aggregation across Business Lines Based on Frequency Dependence and Loss Dependence

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jianping Li ◽  
Xiaoqian Zhu ◽  
Jianming Chen ◽  
Lijun Gao ◽  
Jichuang Feng ◽  
...  
Keyword(s):  
Frequency Dependence ◽  
Operational Risk ◽  
Copula Function ◽  
Limited Attention ◽  
Risk Modeling ◽  
Risk Capital ◽  
Loss Distribution ◽  
Risk Aggregation ◽  
The Impact ◽  
Chinese Banking

In loss distribution approach (LDA), the most popular approach in operational risk modeling, frequency dependence and loss distribution dependence across business lines are two dependences which banks should consider. In practice, mainly for simplicity, many banks only model frequency dependence although they think that the impact of frequency dependence is insignificant. In this study, two approaches, respectively, models frequency dependence and loss distribution dependence, are introduced. Both approaches are modeled by copula function, which is capable of capturing nonlinear correlation. Based on the most comprehensive operational risk dataset of Chinese banking as far as we know, the operational risk capital charge of the overall Chinese banking is calculated by the two approaches. The results show that there is an obvious distinction between the capital calculated by modeling frequency dependence and the capital calculated by modeling loss dependence. The approach with very limited attention exactly yields a much larger capital result. So it is advised in this paper that banks should not just rely on the approach to modeling frequency dependence for it is natural and easy to deal with. A safer and more effective way for banks is to comprehensively take the results of the two kinds of approach into consideration.

Should the Advanced Measurement Approach for Operational Risk be Discarded? Evidence from the Chinese Banking Industry

2019 ◽  
Vol 22 (01) ◽  
pp. 1950007 ◽  
Author(s):  
Xiaoqian Zhu ◽  
Jianping Li ◽  
Dengsheng Wu
Keyword(s):  
Banking Industry ◽  
Operational Risk ◽  
Banking Supervision ◽  
Clear Trend ◽  
The Past ◽  
Regulatory Frameworks ◽  
Chinese Banks ◽  
Chinese Banking Industry ◽  
Measurement Approach ◽  
Chinese Banking

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 AMAs does not narrow as envisioned prior. This paper discusses whether this judgment of the BCBS holds for the Chinese banking industry. We first review the development of operational risk data collection and AMAs in China over the past decade. Then, capital requirement results for Chinese banks based on these datasets and approaches are summarized and analyzed. It is shown that along with the accumulation of operational risk data and the refinement of AMAs, operational risk results for the Chinese banking industry have shown a clear trend of convergence that is exactly opposed to judgments of the BCBS. Therefore, the removal of the AMA from regulatory frameworks may not be reasonable.

scholarly journals A Nonparametric Operational Risk Modeling Approach Based on Cornish-Fisher Expansion

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoqian Zhu ◽  
Jianping Li ◽  
Jianming Chen ◽  
Yingqi YangHuo ◽  
Lijun Gao ◽  
...  
Keyword(s):  
Operational Risk ◽  
Risk Modeling ◽  
Parametric Approach ◽  
Risk Capital ◽  
Loss Distribution ◽  
Modeling Approach ◽  
Loss Distribution Approach ◽  
Operational Risk Modeling ◽  
Chinese Banking ◽  
Distribution Assumption

It is generally accepted that the choice of severity distribution in loss distribution approach has a significant effect on the operational risk capital estimation. However, the usually used parametric approaches with predefined distribution assumption might be not able to fit the severity distribution accurately. The objective of this paper is to propose a nonparametric operational risk modeling approach based on Cornish-Fisher expansion. In this approach, the samples of severity are generated by Cornish-Fisher expansion and then used in the Monte Carlo simulation to sketch the annual operational loss distribution. In the experiment, the proposed approach is employed to calculate the operational risk capital charge for the overall Chinese banking. The experiment dataset is the most comprehensive operational risk dataset in China as far as we know. The results show that the proposed approach is able to use the information of high order moments and might be more effective and stable than the usually used parametric approach.

A mutual information‐based likelihood function for particle filter flood extent assimilation

2021 ◽  
Author(s):  
Antara Dasgupta ◽  
Renaud Hostache ◽  
RAAJ Ramasankaran ◽  
Guy J.‐P Schumann ◽  
Stefania Grimaldi ◽  
...  
Keyword(s):  
Mutual Information ◽  
Particle Filter ◽  
Likelihood Function

Nonlinear Pattern Analysis of Ventricular Premature Beats by Mutual Information

1997 ◽  
Vol 36 (04/05) ◽  
pp. 257-260 ◽  
Author(s):  
H. Saitoh ◽  
T. Yokoshima ◽  
H. Kishida ◽  
H. Hayakawa ◽  
R. J. Cohen ◽  
...  
Keyword(s):  
Mutual Information ◽  
Temporal Pattern ◽  
Pattern Analysis ◽  
Autonomic Activity ◽  
Correlation Measure ◽  
Ventricular Premature Beats ◽  
Risk Of Mortality ◽  
Premature Beats ◽  
Information Values ◽  
Nonlinear Pattern

Abstract:The frequency of ventricular premature beats (VPBs) has been related to the risk of mortality. However, little is known about the temporal pattern of occurrence of VPBs and its relationship to autonomic activity. Hence, we applied a general correlation measure, mutual information, to quantify how VPBs are generated over time. We also used mutual information to determine the correlation between VPB production and heart rate in order to evaluate effects of autonomic activity on VPB production. We examined twenty subjects with more than 3000 VPBs/day and simulated ran-( dom time series of VPB occurrence. We found that mutual information values could be used to characterize quantitatively the temporal patterns of VPB generation. Our data suggest that VPB production is not random and VPBs generated with a higher value of mutual information may be more greatly affected by autonomic activity.

Data Screening Methods – Application to Differential Diagnosis in Pancreatic Pathology from Radiological Signs

1978 ◽  
Vol 17 (01) ◽  
pp. 36-40 ◽  
Author(s):  
J.-P. Durbec ◽  
Jaqueline Cornée ◽  
P. Berthezene
Keyword(s):  
Differential Diagnosis ◽  
Mutual Information ◽  
Data Processing ◽  
Screening Methods ◽  
Automatic Data ◽  
Chronic Calcifying Pancreatitis ◽  
Number Of Patients ◽  
Calcifying Pancreatitis ◽  
Pancreatic Pathology ◽  
Data Screening

The practice of systematic examinations in hospitals and the increasing development of automatic data processing permits the storing of a great deal of information about a large number of patients belonging to different diagnosis groups.To predict or to characterize these diagnosis groups some descriptors are particularly useful, others carry no information. Data screening based on the properties of mutual information and on the log cross products ratios in contingency tables is developed. The most useful descriptors are selected. For each one the characterized groups are specified.This approach has been performed on a set of binary (presence—absence) radiological variables. Four diagnoses groups are concerned: cancer of pancreas, chronic calcifying pancreatitis, non-calcifying pancreatitis and probable pancreatitis. Only twenty of the three hundred and forty initial radiological variables are selected. The presence of each corresponding sign is associated with one or more diagnosis groups.

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