Statistical Modelling and Risk Analysis: Selected contributions from ICRA9, Perugia, Italy, May 25-27, 2022 (Springer Proceedings in Mathematics & Statistics, 430)

Preface
Contents
Examining the Network Effects in Bank Risk: Evidence from Liquidity Creation in Mutual Banks
	1 Introduction
	2 Methodology
		2.1 Spatial Model
		2.2 Econometric Specification
	3 Data and Results
	4 Concluding Remarks
	Appendix
	References
Teaching Note—Data Science Training for Finance and Risk Analysis: A Pedagogical Approach with Integrating Online Platforms
	1 Introduction
	2 Structure and Content of the Course
	3 Implementation Process
	4 Results
	5 Main Conclusions
	References
Analysing Misclassifications in Confusion Matrices
	1 Introduction
	2 Methodology
	3 Marginal Homogeneity
	4 Bayesian Approach
	5 Applications
		5.1 Application 1
		5.2 Application 2
	6 Conclusions and Final Comments
	References
Management Excellence Model Use: Brazilian Electricity Distributors Case
	1 Introduction
	2 Literature Review
	3 The Excellence Management Model
	4 Methodology
		4.1 Research Classification—Sample and Population
		4.2 Data Collection and Variables of Interest
	5 Data Analysis
	6 Discussion and Conclusions
	Appendix: List of Acronyms
	References
A Statistical Boost to Assess Water Quality
	1 Introduction
	2 Some Background on EU Directives and Water Quality
	3 Statistical Utilities
		3.1 Checking Independence
		3.2 Comparing Seasons
		3.3 Detecting Correlated Seasons
		3.4 Detecting and Estimating Trends
		3.5 Additional Notes and Software
	4 Analysing Water Quality in Two Study Sites
		4.1 Study Sites Description
		4.2 Statistical Changes Between the Months
		4.3 Investigating Temporal Trends
	5 Concluding Remarks and Thoughts
	References
Time Series Procedures to Improve Extreme Quantile Estimation
	1 Motivation and Introduction
	2 Main Results in Extreme Values Analysis
		2.1 Parameters of Interest
		2.2 Statistical Approaches in EVT
	3 An Overview of Time Series Modelling
	4 Application to Environmental Data
	5 Concluding Remarks and Future Work
	References
Factors Associated with Powerful Hurricanes in the Atlantic
	1 Introduction
	2 Data
	3 Logistic Regression Models, Results and Discussion
	4 Summary and Concluding Remarks
	References
Reliable Alternative Ways to Manage the Risk of Extreme Events
	1 Introduction and Scope of the Paper
		1.1 EVI-estimation of Pareto-Type Models
		1.2 Further Details on the CTE
		1.3 Scope of the Paper
	2 A Few Considerations on the Asymptotic Behaviour of the MOp CTE-estimators
	3 A Monte-Carlo Simulation Study
	4 Concluding Remarks
	References
Risk Analysis in Practice and Theory
	1 Introduction
	2 Practical Background
	3 Theoretical Inside
	4 Discussion
	Appendix 1
	Appendix 2
	References
On Some Consequences of COVID-19 in EUR/USD Exchange Rates and Economy
	1 Exchange Rates 10/13/2019–4/9/2020
	2 Forecasting EUR/US Exchange Rates
		2.1 Finding a Model for Forecasting
		2.2 Forecasting: 34 Days in the Future (Due to the Difference of Observed Data and Current Date)
	3 Discussion: What Does This Mean for the Economy?
	4 Conclusion
	References
Natural Risk Assessment of Italian Municipalities for Residential Insurance
	1 Introduction
	2 Data
	3 Earthquake Risk Assessment
	4 Flood Risk Assessment
	5 Results
	6 Conclusion
	References
Variable Selection in Binary Logistic Regression for Modelling Bankruptcy Risk
	1 Introduction
	2 Methodology and Study Design
	3 Data Description
	4 Results
		4.1 Stepwise, LASSO and Maximum Data Variance Selection Methods
		4.2 Single and Forest of Trees Methods
		4.3 Comparison Between the Best Method of Each Group
	5 Discussion
	References
Operations with Iso-structured Models with Commutative Orthogonal Block Structure: An Introductory Approach
	1 Introduction
	2 Commutative Jordan Algebras of Symmetric Matrices
	3 Models with Commutative Orthogonal Block Structure
	4 Operating Iso-structured COBS
	5 Conclusion
	References
Long and Short–Run Dynamics in Realized Covariance Matrices: A Robust MIDAS Approach
	1 Introduction
	2 A New MIDAS-Type Model
		2.1 The Hadamard Exponential Specification
		2.2 Estimation
	3 Empirical Analysis
		3.1 Dataset
		3.2 Estimation Results
		3.3 In–Sample Comparison
		3.4 Out–of–Sample Analysis
	4 Concluding Remarks
	References
Taxonomy-Based Risk Analysis with a Digital Twin
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Employing a Digital Twin for Risk Management
	4 The Smart Resort Business Case
	5 Conclusion and Future Work
	References
Advanced Lattice Rules for Multidimensional Sensitivity Analysis in Air Pollution Modelling
	1 Introduction
	2 The Stochastic Approaches
	3 Case Study: UNI-DEM Model
		3.1 Sensitivity Studies with Respect to Emission Levels
		3.2 Sensitivity Studies with Respect to Chemical Reactions Rates
	4 Conclusion
	References
On Pitfalls in Statistical Analysis for Risk Assessment of COVID-19
	1 Introduction
	2 Methods
	3 Results and Discussion
		3.1 Use of Cox and Logistic Models
			3.1.1 At Risk
			3.1.2 Censored Sample
		3.2 Analysis of Combined Samples
		3.3 Adjusting for Confounder
		3.4 Correction for Selection Bias
		3.5 Measurement Error
			3.5.1 Biases Due to Measurement Error/Misclassification
			3.5.2 Reliability Ratio
			3.5.3 Adjusting for Unbalanced Confounder
			3.5.4 Decreasing Power
			3.5.5 Sensitivity and Specificity
			3.5.6 22 Misclassification Model
	4 Conclusion
	References