New Perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance

The scientific exchange between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results. This volume includes a selection of papers presented at the Workshop New perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance. 
The workshop was a two-day study activity aimed at presenting new ideas and innovative lines of research in mathematical and statistical methods for insurance and finance, both from a theoretical and applied point of view. It was organized by the Department of Economics and Statistics of the University of Salerno and was held from 27 to 28 June 2025 in Salerno (Italy).
This book covers a wide variety of subjects, among others: Social well-being, Artificial intelligence and Machine learning in Insurance and Finance, Silver Economy and Insurance, Climate-related Risks and Insurance, Insurtech and Fintech, Catastrophe Risks, Cyber Risk.
This volume is a valuable resource for academics, PhD students, practitioners, professional and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.

List of contents

Towards Fairer Sanction Systems: Income-Based Models with Aggregation Functions.- Multidimensional inequality and measurement of Social Well-Being.- A neural network model approach to longevity risk management.- Climate-related Extensions of the Lee-Carter Model.- Quantification of Operational Flexibility in Wastewater Treatment Projects.- Roughness in VIX Index and in Realized Volatility: Rolling Window Estimation by Randomized Kolmogorov-Smirnov Distribution.- A Comparison of Data-driven Synthetic Performance Indicators for Default Prediction.- Rethinking the Indexation of Retirement Age: Cohort vs. Period Life Expectancy.- Temperature forecast for weather derivatives with Neural Network.- Modeling Health and Disability Trajectories in Later Life: A Multi-State Approach Using HRS Data.- Backtesting Expected Shortfall for Bitcoin: A Joint Combined LSTM-Based Approach.- Reverse mortgages: Exploring the impact of risk factors by source.- Understanding and attitudes toward Reverse Mortgage in Italy: cognitive dissonance and future concerns.- Climate Litigation Risk: Comparing Linear and Non Linear Losses of Insurances.- Option Hedging Through Reinforcement Learning.- Parameter Stability in Yield Curve Fitting.- Deep Learning for Tabular Data: Application to Credit Risk Modeling.- Modeling economic recovery via diffusion processes with multisigmoidal logistic mean subject to random catastrophes.- Scaling the Tails: Intraday Quantiles for forecasting Value-at-Risk and Expected Shortfall.- High-Profile GDPR Fines and their financial impact on listed firms: an exploratory analysis.- Delay-Adjusted Modeling of Cybersecurity Breaches Using INLA: Evidence from State Attorney General Data.- Addressing Long-Term Care Risk through Pension-Linked Insurance: A Stochastic Approach Using Severance Pay Scheme.

About the author

Michele La Rocca
is a Full Professor of Statistics at the University of Salerno in Italy. His research areas include empirical likelihood, nonlinear time series, neural networks and deep learning, and resampling techniques, which he has applied to biological and financial data. A crucial aspect of his research is building bridges between data analysis, statistics, and machine learning methods. He is an elected member of ISI and the Charting Committee of the International Symposia on Nonparametric Statistics (ISNPS), an IMS group. He has served as Associate Editor of Computational Statistics and Data Analysis and is now Associate Editor of Statistical Methods and Applications, the journal of the Italian Statistical Society.

Massimiliano Menzietti
is Associate Professor of Mathematical Methods for Economics, Finance and Actuarial Sciences at the Department of Economics and Statistics of the University of Salerno (Italy). He got a master degree (cum laude) in Economics at “LUISS - Guido Carli” University of Rome in 1995 and a PhD in Actuarial Science at “Sapienza” University of Rome in 2002.


His primary areas of research are: automatic balance mechanisms in PAYG pension systems; actuarial models for health insurance and health funds, modelling and management of 


biometric risks (disability and longevity); pricing of mortality and longevity linked securities; solvency capital requirements for life insurance and pension funds.

Cira Perna
is full professor of Statistics at the Department of Economics and Statistics of the University of Salerno (Italy). She was Head of the Department from 2009 to 2018, member of the 


Board of Directors of the University of Salerno from 2018 to 2022, and elected member of the Steering committee of the Italian Statistical Society from 2018 to 2020. Since the first edition of the 


Conference, in 2004, she is chair of the international conference MAF and guest editor of the associated international journals. Since 2006 she is Editor of the Springer books MAF. Her research 


work mainly focuses on non-linear time series, artificial neural network models and resampling techniques. On these topics, she has published numerous papers in national and international 


journals. She has participated in several research projects, both at national and international level and she has been a member of several scientific committees of national and international conferences.

Marilena Sibillo
is full professor of Mathematical Methods for Economics, Finance and Actuarial Sciences at the University of Salerno and at present adjunct professor of Financial Mathematics at Luiss University in Rome. In 2012 she was awarded as Highly Commended Award Winner at the Literati Network Awards for Excellence and since 2013 she is a Paul Harris Fellow. She had national and international awards related to teaching. Since 2006 she is Editor of the Springer books MAF, and guest editor of international journals, since 2004 chair of the international conference MAF and since 2016 chair of the UNISActuarial School. She is author of more than 100 papers published in international journals and books. Her scientific activity mainly deals with Risk Theory, Analysis and control of the interactions between financial and demographic risks, Variable annuities, Stochastic mortality, Innovative pension contracts, Sustainability in insurance.

Summary

The scientific exchange between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results. This volume includes a selection of papers presented at the Workshop New perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance. 
The workshop was a two-day study activity aimed at presenting new ideas and innovative lines of research in mathematical and statistical methods for insurance and finance, both from a theoretical and applied point of view. It was organized by the Department of Economics and Statistics of the University of Salerno and was held from 27 to 28 June 2025 in Salerno (Italy).
This book covers a wide variety of subjects, among others: Social well-being, Artificial intelligence and Machine learning in Insurance and Finance, Silver Economy and Insurance, Climate-related Risks and Insurance, Insurtech and Fintech, Catastrophe Risks, Cyber Risk.
This volume is a valuable resource for academics, PhD students, practitioners, professional and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.

Product details

• Assisted by: Michele La Rocca (Editor), Massimiliano Menzietti (Editor), Cira Perna (Editor), Cira Perna et al (Editor), Marilena Sibillo (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Release: 12.12.2025
• EAN: 9783032055507
• ISBN: 978-3-0-3205550-7
• No. of pages: 261
• Illustrations: VIII, 261 p. 78 illus., 35 illus. in color.
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; Nachhaltigkeit, Sustainability, Künstliche Intelligenz, machine learning, Maschinelles Lernen, Artificial Intelligence, Wahrscheinlichkeitsrechnung und Statistik, blockchain technology, Actuarial Mathematics, Mathematical statistics, Silver Economy, Gender analysis, Behavioral finance and insurance, Policy indications