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Risks
Special Issues
Advancements in Actuarial Mathematics and Risk Theory
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Advancements in Actuarial Mathematics and Risk Theory

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 5062

Special Issue Editor

Prof. Dr. Dimitrios G. Konstantinides

E-Mail Website
Guest Editor
Department Statistics and Actuarial—Financial Mathematics, University of the Aegean, GR 83200 Samos, Greece
Interests: risk theory; actuarial science; macroeconomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Actuarial Mathematics are a hot topic, and not only for the Insurance Industry. The understanding of risk procedures is a prerequisite for any human activity. Keeping in mind classical risk models and taking into consideration the increasing interest in emerging risks such as those pertaining to the climate, in cyber sectors, or pandemics, we expect to receive original papers on the discipline “risk theory without borders”. I am sure that the dependence of risk brings new ideas and methods to approach real problems and to reach efficient solutions. Furthermore, dependence models in economic transactions adequately represent social evolution.

Prof. Dr. Dimitrios G. Konstantinides
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Risks is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • actuarial risk
  • stochastic analysis
  • asymptotic approximation
  • dependence modeling
  • ruin probability
  • heavy-tailed distributions
  • extremal events
  • risk-averse strategy
  • stochastic equilibrium

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Published Papers (3 papers)

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Research

16 pages, 725 KiB  
Article
Cyber Risk in Insurance: A Quantum Modeling
by Claude Lefèvre, Muhsin Tamturk, Sergey Utev and Marco Carenzo
Risks 2024, 12(5), 83; https://doi.org/10.3390/risks12050083 - 20 May 2024
Viewed by 1130
Abstract
In this research, we consider cyber risk in insurance using a quantum approach, with a focus on the differences between reported cyber claims and the number of cyber attacks that caused them. Unlike the traditional probabilistic approach, quantum modeling makes it possible to [...] Read more.
In this research, we consider cyber risk in insurance using a quantum approach, with a focus on the differences between reported cyber claims and the number of cyber attacks that caused them. Unlike the traditional probabilistic approach, quantum modeling makes it possible to deal with non-commutative event paths. We investigate the classification of cyber claims according to different cyber risk behaviors to enable more precise analysis and management of cyber risks. Additionally, we examine how historical cyber claims can be utilized through the application of copula functions for dependent insurance claims. We also discuss classification, likelihood estimation, and risk-loss calculation within the context of dependent insurance claim data. Full article
(This article belongs to the Special Issue Advancements in Actuarial Mathematics and Risk Theory)
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13 pages, 419 KiB  
Article
Robust Estimation of the Tail Index of a Single Parameter Pareto Distribution from Grouped Data
by Chudamani Poudyal
Risks 2024, 12(3), 45; https://doi.org/10.3390/risks12030045 - 1 Mar 2024
Viewed by 1513
Abstract
Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to a MLE become significantly limited when dealing with grouped loss severity data, with [...] Read more.
Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to a MLE become significantly limited when dealing with grouped loss severity data, with only a handful of methods, like least squares, minimum Hellinger distance, and optimal bounded influence function, available. This paper introduces a novel robust estimation technique, the Method of Truncated Moments (MTuM), pecifically designed to estimate the tail index of a Pareto distribution from grouped data. Inferential justification of the MTuM is established by employing the central limit theorem and validating it through a comprehensive simulation study. Full article
(This article belongs to the Special Issue Advancements in Actuarial Mathematics and Risk Theory)
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31 pages, 771 KiB  
Article
Stochastic Chain-Ladder Reserving with Modeled General Inflation
by Massimo De Felice and Franco Moriconi
Risks 2023, 11(12), 221; https://doi.org/10.3390/risks11120221 - 18 Dec 2023
Viewed by 1839
Abstract
We consider two possible approaches to the problem of incorporating explicit general (i.e., economic) inflation in the non-life claims reserve estimates and the corresponding reserve SCR, defined—as in Solvency II—under the one-year view. What we call the actuarial approach provides a simplified solution [...] Read more.
We consider two possible approaches to the problem of incorporating explicit general (i.e., economic) inflation in the non-life claims reserve estimates and the corresponding reserve SCR, defined—as in Solvency II—under the one-year view. What we call the actuarial approach provides a simplified solution to the problem, obtained under the assumption of deterministic interest rates and absence of inflation risk premia. The market approach seeks to eliminate these shortcomings by combining a stochastic claims reserving model with a stochastic market model for nominal and real interest rates. The problem is studied in details referring to the stochastic chain-ladder provided by the Over-dispersed Poisson model. The application of the two approaches is illustrated by a worked example based on market data. Full article
(This article belongs to the Special Issue Advancements in Actuarial Mathematics and Risk Theory)
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