Special Issue "Computational Issues in Insurance and Finance"

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Engineering".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 4845

Special Issue Editors

Prof. Dr. Cira Perna
E-Mail Website
Guest Editor
Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Interests: non-linear time series; artificial neural networks; resampling techniques
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marilena Sibillo
E-Mail Website
Guest Editor
Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Interests: stochastic processes; stochastic models; financial and insurance risk; risk management
Special Issues, Collections and Topics in MDPI journals
Dr. Bimonte Giovanna
E-Mail Website
Co-Guest Editor
Department of Economics and Statistics, University of Salerno - Fisciano (Italia)
Interests: Game Theory, Cooperative games (TU and NTU), Public and Global Goods, Private and Public R&D investments and Knowledge Spillovers in Pharmaceutical Industry, Environmental Agreement, Spatial competition, Voronoi diagram and its applications, Optimization problems, Experimental Economics, Experimental learning in game theory, economics and finance Mathematics and Economics Education, General Equilibrium Model.
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Naimoli
E-Mail Website
Co-Guest Editor
Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy
Interests: time series; financial econometrics; risk management

Special Issue Information

Dear Colleagues,

This Special Issue will publish a set of selected papers from MAF2022—Mathematical and Statistical Methods for Actuarial Sciences and Finance—to be held on 20–22 April 2022 at the University of Salerno (Italy). This Special Issue will focus on computational mathematics and statistics in various fields of Actuarial Sciences and Finance, with a particular focus on interdisciplinary interactions as a source of new knowledge.

The Special Issue is reserved for papers presented at the MAF2022 conference. Interested authors can submit their work for publication in the SI from April 20 and by October 31.

Topics of interest include, but are not limited to, actuarial models, analysis of high-frequency financial data, Behavioural finance, carbon and green finance, Credit risk methods and models, dynamic optimization in finance, financial econometrics, forecasting of dynamical actuarial and financial phenomena, fund performance evaluation, insurance portfolio risk analysis, interest rate models, longevity risk, machine learning and soft-computing in finance, management in the insurance business, models and methods for financial time series analysis, models for financial derivatives, multivariate techniques for financial markets analysis, neural networks in insurance, optimization in insurance, pricing, probability in actuarial sciences, insurance and finance, real-world finance, risk management, solvency analysis, sovereign risk, static and dynamic portfolio selection and management, trading systems.

Prof. Dr. Cira Perna
Prof. Dr. Marilena Sibillo
Prof. Dr. Giovanna Bimonte
Dr. Antonio Naimoli
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. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. 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.

Published Papers (5 papers)

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Research

Article
Some Remarks on Malicious and Negligent Data Breach Distribution Estimates
Computation 2022, 10(12), 208; https://doi.org/10.3390/computation10120208 - 30 Nov 2022
Viewed by 666
Abstract
Digitization offers great opportunities as well as new challenges. Indeed, these opportunities entail increased cyber risks, both from deliberate cyberattacks and from incidents caused by inadvertent human error. Cyber risk must be mastered, and to this aim, its quantification is an urgent challenge. [...] Read more.
Digitization offers great opportunities as well as new challenges. Indeed, these opportunities entail increased cyber risks, both from deliberate cyberattacks and from incidents caused by inadvertent human error. Cyber risk must be mastered, and to this aim, its quantification is an urgent challenge. There is a lot of interest in this topic from the insurance community in order to price adequate coverage to their customers. A key first step is to investigate the frequency and severity of cyber incidents. On the grounds that data breaches seem to be the main cause of cyber incidents, the aim of this paper is to give further insights about the frequency and severity statistical distributions of malicious and negligent data breaches. For this purpose, we refer to a publicly available dataset: the Chronology of Data Breaches provided by the Privacy Rights Clearinghouse. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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Article
Deep Neural Network Algorithms for Parabolic PIDEs and Applications in Insurance and Finance
Computation 2022, 10(11), 201; https://doi.org/10.3390/computation10110201 - 10 Nov 2022
Viewed by 656
Abstract
In this paper we study deep neural network algorithms for solving linear and semilinear parabolic partial integro-differential equations with boundary conditions in high dimension. Our method can be considered as an extension of the deep splitting method for PDEs to equations with non-local [...] Read more.
In this paper we study deep neural network algorithms for solving linear and semilinear parabolic partial integro-differential equations with boundary conditions in high dimension. Our method can be considered as an extension of the deep splitting method for PDEs to equations with non-local terms. To show the viability of our approach, we discuss several case studies from insurance and finance. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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Article
Factors Affecting Demand and Supply in the Housing Market: A Study on Three Major Cities in Turkey
Computation 2022, 10(11), 196; https://doi.org/10.3390/computation10110196 - 02 Nov 2022
Cited by 2 | Viewed by 1098
Abstract
This paper aims to identify the economic factors that significantly affect the demand for and supply of housing in three major cities in Turkey, such as Istanbul, Ankara, and Izmir. This study uses monthly data ranges from January 2010 to December 2020 because [...] Read more.
This paper aims to identify the economic factors that significantly affect the demand for and supply of housing in three major cities in Turkey, such as Istanbul, Ankara, and Izmir. This study uses monthly data ranges from January 2010 to December 2020 because of the limited housing price data from each city. For smooth measurement, the logarithm of all data except measurements of nominal interest rate, real interest rate and inflation is used. This research uses the Co-integration Analysis and Vector Error Correction Model (VECM) to investigate the macroeconomic variables’ effects on the demand and supply. Mortgage credit volume, as a dependent variable, is influenced by real per capita GDP, real house prices, projected inflation, and nominal interest rates. On the contrary, the building site is used as a dependent variable on the supply side that is determined by the real housing price, the real interest rate, and the real cost of construction. In the VECM model, the mortgage credit volume and constriction cost were dominated by error correction variables, showing the adjustment of disequilibrium towards an equilibrium point. In the case of Ankara, supply-side variables have a long-term relationship. Both housing demand and supply-related factors have a long-term impact on the housing market in Istanbul and Izmir. Given a significant p-value, the coefficient of C1 derived from system equations is negative. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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Article
On Barrier Binary Options in the Telegraph-like Financial Market Model
Computation 2022, 10(9), 163; https://doi.org/10.3390/computation10090163 - 17 Sep 2022
Viewed by 599
Abstract
The article continues the study of the market model based on jump-telegraph processes. It is assumed that the price of a risky asset follows the stochastic exponential of a piecewise linear process, equipped with jumps that occur at the moments of a pattern [...] Read more.
The article continues the study of the market model based on jump-telegraph processes. It is assumed that the price of a risky asset follows the stochastic exponential of a piecewise linear process, equipped with jumps that occur at the moments of a pattern change. In this case, the standard option pricing formula was derived previously, while exotic options for this model have not yet been explored. Within this framework, we are developing procedures for pricing binary barrier options. This article concerns the “cash-(at hit)-or-nothing” binary barrier option. The main tools of this analysis are methods developed for first-pass probabilities. Some known results related to the ruin probabilities follow directly from these settings. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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Article
Credit Spreads, Leverage and Volatility: A Cointegration Approach
Computation 2022, 10(9), 155; https://doi.org/10.3390/computation10090155 - 05 Sep 2022
Viewed by 649
Abstract
This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread [...] Read more.
This work documents the existence of a cointegration relationship between credit spreads, leverage and equity volatility for a large set of US companies. It is shown that accounting for the long-run equilibrium dynamic between these variables is essential to correctly explain credit spread changes. Using a novel structural model in which equity is modeled as a compound option on the firm’s assets, a new methodology for estimating the unobservable market value of the firm’s assets and volatility is developed. The proposed model allows to significantly reduce the pricing errors in predicting credit spreads when compared with several structural models. In terms of correlation analysis, it is shown that not accounting for the long-run equilibrium equation embedded in an error correction mechanism (ECM) results into a misspecification problem when regressing a set of explanatory variables onto the spread changes. Once credit spreads, leverage and volatility are correctly modeled, thus allowing for a long-run equilibrium, the fit of the regressions sensibly increases if compared to the results of previous research. It is further shown that most of the cross-sectional variation of the spreads appears to be more driven by firm-specific characteristics rather than systematic factors. Full article
(This article belongs to the Special Issue Computational Issues in Insurance and Finance)
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