Analysing Model Risks in Risk Aggregation of Non-financial Corporations

2022 ◽  
pp. 17-38
Author(s):  
Gabriele Wieczorek ◽  
Dimitrios Karakidis
Keyword(s):  
Risk Aggregation

Risk‐return optimization with different risk‐aggregation strategies

2010 ◽  
Vol 11 (2) ◽  
pp. 129-146 ◽  
Author(s):  
Stan Uryasev ◽  
Ursula A. Theiler ◽  
Gaia Serraino
Keyword(s):  
Risk Return ◽  
Risk Aggregation

scholarly journals Operational Choices for Risk Aggregation in Insurance: PSDization and SCR Sensitivity

Risks ◽  
2018 ◽  
Vol 6 (2) ◽  
pp. 36
Author(s):  
Xavier Milhaud ◽  
Victorien Poncelet ◽  
Clement Saillard
Keyword(s):  
Risk Aggregation

scholarly journals Risk Aggregation by Using Copulas in Internal Models

2011 ◽  
Vol 01 (03) ◽  
pp. 50-57 ◽  
Author(s):  
Tristan Nguyen ◽  
Robert Danilo Molinari
Keyword(s):  
Internal Models ◽  
Risk Aggregation

scholarly journals Inter-Regional Variability in the Incidence of Skin and Subcutaneous Tissue Diseases of Children Aged 0–14 Years in the Russian Federation (а Population-Based Study)

2018 ◽  
Vol 15 (4) ◽  
pp. 349-353
Author(s):  
Eleonora I. Pilguy ◽  
Leyla S. Namazova-Baranova ◽  
Igor A. Gundarov
Keyword(s):  
Russian Federation ◽  
Coefficient Of Variation ◽  
Subcutaneous Tissue ◽  
Rank Correlation ◽  
Population Based ◽  
Regional Variability ◽  
Spearman’S Rank Correlation ◽  
Risk Aggregation ◽  
The Russian Federation ◽  
Range Of Variation

Background. An effective system for management of pediatric dermatological care in Russia requires taking into account the peculiarities of regional morbidity. According to modern literature, this issue is not sufficiently developed. Our aim was to study the characteristics of variability in the incidence of skin and subcutaneous tissue diseases of children aged 0–14 years in the Russian Federation. Methods. The data of the state medical statistics on 83 territorial entities of the Russian Federation for 2009–2015 was used. The analysis implemented the risk aggregation method. The degree of variability in regional morbidity was assessed by the range of variation and the coefficient of variation. Region rankings were carried out by the annual incidence. The Spearman’s rank correlation coefficient was used to study the stability of regions belonging to a certain ranked place. Results. In 2009, the incidence of skin and subcutaneous tissue diseases of children aged 0–14 years in the Russian Federation had a pronounced variability: the range of variation was 7.7 times, the coefficient of variation was 28%. The annual region rankings were carried out. In 2010–2015, the annual variability indices remained high. The coefficients of rank correlation when distributing regions by morbidity were in the range of 0.75–0.94 compared to 2009. Quintiles of regions with different levels of pediatric dermatological morbidity were singled out. Conclusion. The incidence of skin and subcutaneous tissue diseases in children aged 0–14 years in the territorial entities of the Russian Federation during 2009–2015 had a pronounced variability. Regions had a stable preference for a certain ranking place. The division of territorial entities of the Russian Federation into groups of pediatric dermatological morbidity are presented.

Product Flexibility Strategy Under Supply and Demand Risk

2021 ◽  
Author(s):  
Yimin Wang ◽  
Scott Webster
Keyword(s):  
Supply Chain ◽  
Supply And Demand ◽  
Problem Definition ◽  
Base Case ◽  
Supply Network ◽  
Aggregation Effect ◽  
Risk Aggregation ◽  
Managerial Implications ◽  
Product Flexibility ◽  
Global Uncertainty

Problem definition: With heightened global uncertainty, supply chain managers are under increasing pressure to craft strategies that accommodate both supply and demand risks. Although product flexibility is a well-understood strategy to accommodate risk, there is no clear guidance on the optimal flexibility configuration of a supply network that comprises both unreliable primary suppliers and reliable backup suppliers. Academic/practical relevance: Existing literature examines the value of flexibility with primary and backup suppliers independently. For a risk-neutral firm, research shows that (a) incorporating flexibility in a primary supplier by replacing two dedicated ones (in absence of backup supply) is always beneficial and that (b) adding flexibility to a reliable backup supplier (in absence of product flexibility in primary suppliers) is always valuable. It is unclear, however, how flexibility should be incorporated into a supply network with both unreliable primary suppliers and reliable backup suppliers. This research studies whether flexibility should be incorporated in a primary supplier, a backup supplier, or both. Methodology: We develop a normative model to analyze when flexibility benefits and when it hurts. Results: Compared with a base case of no flexibility, we prove that incorporating flexibility in either primary or backup suppliers is always beneficial. However, incorporating flexibility in both primary and backup suppliers can be counterproductive because the supply chain performance can decline with saturated flexibility, even if flexibility is costless. A key reason is that the risk-aggregation effect of consolidating flexibility in an unreliable supplier becomes more salient when flexibility is already embedded in a backup supplier. Managerial implications: This research refines the existing understanding of flexibility by illustrating that flexibility is not always beneficial. When there is a choice, a firm should prioritize incorporating flexibility in a reliable backup supplier.

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 Robust risk aggregation with neural networks

2020 ◽  
Author(s):  
Stephan Eckstein ◽  
Michael Kupper ◽  
Mathias Pohl
Keyword(s):  
Neural Networks ◽  
Risk Aggregation

Multi-unit risk aggregation with consideration of uncertainty and bias in risk metrics

2019 ◽  
Vol 188 ◽  
pp. 473-482 ◽  
Author(s):  
Taotao Zhou ◽  
Mohammad Modarres ◽  
Enrique López Droguett
Keyword(s):  
Unit Risk ◽  
Risk Aggregation
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