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Impact of the Coronavirus Crisis on Insurance and Financial Mathematics...
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Impact of the Coronavirus Crisis on Insurance and Financial Mathematics and Risk Analysis

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

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 14303

Special Issue Editors

Prof. Dr. Angelos Dassios

E-Mail Website
Guest Editor
Department of Statistics, London School of Economics, Houghton Street, London WC2A 2AE, UK
Interests: insurance mathematics; ruin theory; path dependent options; point processes; financial mathematics; excursion theory
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Florin Avram

E-Mail Website
Guest Editor
Laboratoire de Mathématiques Appliquées, Université de Pau, 64000 Pau, France
Interests: stochastic processes; risk; mathematical finance; inventory; queueing and population dynamics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Corina Constantinescu

E-Mail Website
Guest Editor
Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
Interests: actuarial science; risk theory; dependence structures; heavy-tailed distributions; bonus-malus systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The emergence of the COVID-19 pandemic is bound to have an influence on insurance and financial mathematics. One obvious effect is that the independence assumptions in many models used are no longer valid. New models will be needed for assessing the impact of the pandemic in insurance, finance, and related fields. The purpose of this Issue is for researchers to propose stochastic models describing this impact. Papers that involve point processes or small Monte Carlo simulation studies are particularly welcome. Papers that propose novel stochastic models for the spread of the pandemic are also welcome.

Prof. Dr. Angelos Dassios
Prof. Dr. Florin Avram
Prof. Dr. Corina Constantinescu
Guest Editors

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

  • insurance mathematics
  • financial mathematics
  • point processes
  • Monte Carlo simulation
  • risk analysis

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Published Papers (3 papers)

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Research

33 pages, 947 KiB  
Article
Assessing the Impact of the COVID-19 Shock on a Stochastic Multi-Population Mortality Model
by Jens Robben, Katrien Antonio and Sander Devriendt
Risks 2022, 10(2), 26; https://doi.org/10.3390/risks10020026 - 21 Jan 2022
Cited by 3 | Viewed by 5102
Abstract
We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality projection model and its resulting projections for future mortality rates. Throughout the paper, we put focus on the Li and Lee mortality model, which [...] Read more.
We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality projection model and its resulting projections for future mortality rates. Throughout the paper, we put focus on the Li and Lee mortality model, which has become a standard for projecting mortality in Belgium and the Netherlands. We calibrate this mortality model on annual death counts and exposures at the level of individual ages. This type of mortality data are typically collected, produced and reported with a significant delay of—for some countries—several years on a platform such as the Human Mortality Database. To enable a timely evaluation of the impact of a pandemic data point, we have to rely on other data sources (e.g., the Short-Term Mortality Fluctuations Data series) that swiftly publish weekly mortality data collected in age buckets. To be compliant with the design and calibration strategy of the Li and Lee model, we transform the weekly mortality data collected in age buckets to yearly, age-specific observations. Therefore, our paper constructs a protocol to ungroup the death counts and exposures registered in age buckets to individual ages. To evaluate the impact of a pandemic shock, like COVID-19 in the year 2020, we weigh this data point in either the calibration or projection step. Obviously, the more weight we place on this data point, the more impact we observe on future estimated mortality rates and life expectancies. Our paper allows for quantifying this impact and provides actuaries and actuarial associations with a framework to generate scenarios of future mortality under various assessments of the pandemic data point. Full article
(This article belongs to the Special Issue Impact of the Coronavirus Crisis on Insurance and Financial Mathematics and Risk Analysis)
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13 pages, 415 KiB  
Article
Examining the Effects of Gradual Catastrophes on Capital Modelling and the Solvency of Insurers: The Case of COVID-19
by Muhsin Tamturk, Dominic Cortis and Mark Farrell
Risks 2020, 8(4), 132; https://doi.org/10.3390/risks8040132 - 6 Dec 2020
Cited by 3 | Viewed by 3289
Abstract
This paper models the gradual elements of catastrophic events on non-life insurance capital with a particular focus on the impact of pandemics, such as COVID-19. A combination of actuarial and epidemiological models are handled by the Markovian probabilistic approach, with Feynman’s path calculation [...] Read more.
This paper models the gradual elements of catastrophic events on non-life insurance capital with a particular focus on the impact of pandemics, such as COVID-19. A combination of actuarial and epidemiological models are handled by the Markovian probabilistic approach, with Feynman’s path calculation and Dirac notations, in order to observe how a pandemic risk may affect an insurer via reduced business. We also examine how the effects of a pandemic can be taken into account both during and at the end of the process. Examples are also provided showing the potential effects of a pandemic on different types of insurance product. Full article
(This article belongs to the Special Issue Impact of the Coronavirus Crisis on Insurance and Financial Mathematics and Risk Analysis)
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26 pages, 2988 KiB  
Article
First Quarter Chronicle of COVID-19: An Attempt to Measure Governments’ Responses
by Şule Şahin, María del Carmen Boado-Penas, Corina Constantinescu, Julia Eisenberg, Kira Henshaw, Maoqi Hu, Jing Wang and Wei Zhu
Risks 2020, 8(4), 115; https://doi.org/10.3390/risks8040115 - 3 Nov 2020
Cited by 6 | Viewed by 4352
Abstract
The crisis caused by the outbreak of COVID-19 revealed the global unpreparedness for handling the impact of a pandemic. In this paper, we present a first quarter chronicle of COVID-19 in Hubei China, Italy and Spain, particularly focusing on infection speed, death and [...] Read more.
The crisis caused by the outbreak of COVID-19 revealed the global unpreparedness for handling the impact of a pandemic. In this paper, we present a first quarter chronicle of COVID-19 in Hubei China, Italy and Spain, particularly focusing on infection speed, death and fatality rates. By analysing the parameters of the best fitting distributions of the available data for the three rates in each of the three regions, we illustrate the pandemic’s evolution in relation to government measures. We compared the effectiveness of lockdown measures by observing the true situation in each dataset, without proposing a mathematical model. The feasibility of obtaining a firm conclusion in regard to the best solution for containing COVID-19 is limited, with a universal solution failing to exist due to globally varying culture, mentality and behaviours. Our method provides valid insights into the individual and national actions implemented and adhered to in order to slow the effect of the pandemic during the first-wave of COVID-19. Full article
(This article belongs to the Special Issue Impact of the Coronavirus Crisis on Insurance and Financial Mathematics and Risk Analysis)
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