Risks

20 pages, 1324 KiB

Open AccessArticle

by Blanka Horvath, Josef Teichmann and Žan Žurič

Risks 2021, 9(7), 138; https://doi.org/10.3390/risks9070138 - 20 Jul 2021

Cited by 9 | Viewed by 3286

We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular, we analyse the hedging performance of the original architecture under rough volatility models in view of existing theoretical results for those. Furthermore, we [...] Read more.

We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular, we analyse the hedging performance of the original architecture under rough volatility models in view of existing theoretical results for those. Furthermore, we suggest parsimonious but suitable network architectures capable of capturing the non-Markoviantity of time-series. We also analyse the hedging behaviour in these models in terms of Profit and Loss (P&L) distributions and draw comparisons to jump diffusion models if the rebalancing frequency is realistically small. Full article

(This article belongs to the Special Issue Machine Learning in Finance, Insurance and Risk Management)

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18 pages, 488 KiB

Open AccessArticle

A Priori Ratemaking Selection Using Multivariate Regression Models Allowing Different Coverages in Auto Insurance

by Emilio Gómez-Déniz and Enrique Calderín-Ojeda

Risks 2021, 9(7), 137; https://doi.org/10.3390/risks9070137 - 20 Jul 2021

Cited by 8 | Viewed by 2457

Abstract

A comprehensive auto insurance policy usually provides the broadest protection for the most common events for which the policyholder would file a claim. On the other hand, some insurers offer extended third-party car insurance to adapt to the personal needs of every policyholder. [...] Read more.

A comprehensive auto insurance policy usually provides the broadest protection for the most common events for which the policyholder would file a claim. On the other hand, some insurers offer extended third-party car insurance to adapt to the personal needs of every policyholder. The extra coverage includes cover against fire, natural hazards, theft, windscreen repair, and legal expenses, among some other coverages that apply to specific events that may cause damage to the insured’s vehicle. In this paper, a multivariate distribution, based on a conditional specification, is proposed to account for different numbers of claims for different coverages. Then, the premium is computed for each type of coverage separately rather than for the total claims number. Closed-form expressions are given for moments and cross-moments, parameter estimates, and for a priori premiums when different premiums principles are considered. In addition, the severity of claims can be incorporated into this multivariate model to derive multivariate claims’ severity distributions. The model is extended by developing a zero-inflated version. Regression models for both multivariate families are derived. These models are used to fit a real auto insurance portfolio that includes five types of coverage. Our findings show that some specific covariates are statistically significant in some coverages, yet they are not so for others. Full article

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24 pages, 515 KiB

Open AccessReview

Machine Learning Applied to Banking Supervision a Literature Review

by Pedro Guerra and Mauro Castelli

Risks 2021, 9(7), 136; https://doi.org/10.3390/risks9070136 - 19 Jul 2021

Cited by 13 | Viewed by 6447

Abstract

Machine learning (ML) has revolutionised data analysis over the past decade. Like innumerous other industries heavily reliant on accurate information, banking supervision stands to benefit greatly from this technological advance. The objective of this review is to provide a comprehensive walk-through of how [...] Read more.

Machine learning (ML) has revolutionised data analysis over the past decade. Like innumerous other industries heavily reliant on accurate information, banking supervision stands to benefit greatly from this technological advance. The objective of this review is to provide a comprehensive walk-through of how the most common ML techniques have been applied to risk assessment in banking, focusing on a supervisory perspective. We searched Google Scholar, Springer Link, and ScienceDirect databases for articles including the search terms “machine learning” and (“bank” or “banking” or “supervision”). No language, date, or Journal filter was applied. Papers were then screened and selected according to their relevance. The final article base consisted of 41 papers and 2 book chapters, 53% of which were published in the top quartile journals in their field. Results are presented in a timeline according to the publication date and categorised by time slots. Credit risk assessment and stress testing are highlighted topics as well as other risk perspectives, with some references to ML application surveys. The most relevant ML techniques encompass k-nearest neighbours (KNN), support vector machines (SVM), tree-based models, ensembles, boosting techniques, and artificial neural networks (ANN). Recent trends include developing early warning systems (EWS) for bankruptcy and refining stress testing. One limitation of this study is the paucity of contributions using supervisory data, which justifies the need for additional investigation in this field. However, there is increasing evidence that ML techniques can enhance data analysis and decision making in the banking industry. Full article

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20 pages, 3016 KiB

Open AccessEditor’s ChoiceArticle

Sustainable Risk Management in IT Enterprises

by Mateusz Trzeciak

Risks 2021, 9(7), 135; https://doi.org/10.3390/risks9070135 - 15 Jul 2021

Cited by 9 | Viewed by 4427

Abstract

A synthesis of literature studies covering the determinants of agile project management methods, risk management processes as well as factors influencing the shaping of project success and failure clearly indicates that in most publications on risk in agile managed projects, the human factor [...] Read more.

A synthesis of literature studies covering the determinants of agile project management methods, risk management processes as well as factors influencing the shaping of project success and failure clearly indicates that in most publications on risk in agile managed projects, the human factor is heavily underestimated at the expense of often excessive favoring of procedures. Meanwhile, after analyzing the risk factors that arise in agile-managed IT projects, it became apparent that in addition to aspects such as technology, hardware, system, or even project schedule and cost, the project team is highlighted, which is also the second concept with the GPM P5 Standard for Sustainability in Project Management. Thus, the purpose of this article is to develop a model for risk management in IT projects. As a result of the empirical research carried out by means of an expert interview (108 experts) and a questionnaire survey (123 respondents), a risk management model was developed and six original risk management areas were identified, describing 73.92% of all risk factors that may occur during the implementation of an IT project. Furthermore, empirical studies confirm that basic processes such as risk factor identification, impact assessment, and key risk factor management are used by managers and/or team leaders during the implementation of IT projects. Full article

(This article belongs to the Special Issue Advances in Sustainable Risk Management)

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21 pages, 2660 KiB

Open AccessReview

Reputational Risk and Sustainability: A Bibliometric Analysis of Relevant Literature

by Haitham Nobanee, Maryam Alhajjar, Ghada Abushairah and Safaa Al Harbi

Risks 2021, 9(7), 134; https://doi.org/10.3390/risks9070134 - 14 Jul 2021

Cited by 16 | Viewed by 5311

Abstract

This study aims to conduct a bibliometric analysis of reputational risk and sustainability. The research was conducted using the Scopus database, which returned 88 publications published during 2001–2020, revealing that the amount of research output within this field is limited, and more research [...] Read more.

This study aims to conduct a bibliometric analysis of reputational risk and sustainability. The research was conducted using the Scopus database, which returned 88 publications published during 2001–2020, revealing that the amount of research output within this field is limited, and more research output should be conducted in the field of reputational risk and sustainability. We identified nine research streams: reputation risk, reputation risk and sustainability, supply chain management, social responsibility, reputation risk management, strategic approach, sustainable development, corporate sustainability and risk assessment. This bibliometric analysis provides managerial and policy implications for sustainability consideration of reputational risk with perceptions to advance knowledge in this important research field. Full article

(This article belongs to the Special Issue Risk Management Models with Applications to Economic, Social and Natural Environment Sustainability)

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13 pages, 1043 KiB

Open AccessArticle

Mathematical Model for Choosing Counterparty When Assessing Information Security Risks

by Andrey Koltays, Anton Konev and Alexander Shelupanov

Risks 2021, 9(7), 133; https://doi.org/10.3390/risks9070133 - 13 Jul 2021

Cited by 1 | Viewed by 2116

Abstract

The need to assess the risks of the trustworthiness of counterparties is increasing every year. The identification of increasing cases of unfair behavior among counterparties only confirms the relevance of this topic. The existing work in the field of information and economic security [...] Read more.

The need to assess the risks of the trustworthiness of counterparties is increasing every year. The identification of increasing cases of unfair behavior among counterparties only confirms the relevance of this topic. The existing work in the field of information and economic security does not create a reasonable methodology that allows for a comprehensive study and an adequate assessment of a counterparty (for example, a developer company) in the field of software design and development. The purpose of this work is to assess the risks of a counterparty’s trustworthiness in the context of the digital transformation of the economy, which in turn will reduce the risk of offenses and crimes that constitute threats to the security of organizations. This article discusses the main methods used in the construction of a mathematical model for assessing the trustworthiness of a counterparty. The main difficulties in assessing the accuracy and completeness of the model are identified. The use of cross-validation to eliminate difficulties in building a model is described. The developed model, using machine learning methods, gives an accurate result with a small number of compared counterparties, which corresponds to the order of checking a counterparty in a real system. The results of calculations in this model show the possibility of using machine learning methods in assessing the risks of counterparty trustworthiness. Full article

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15 pages, 1041 KiB

Open AccessArticle

Scoring Models and Credit Risk: The Case of Cooperative Banks in Poland

by Krzysztof Kil, Radosław Ciukaj and Justyna Chrzanowska

Risks 2021, 9(7), 132; https://doi.org/10.3390/risks9070132 - 13 Jul 2021

Cited by 3 | Viewed by 4492

Abstract

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in [...] Read more.

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in Polish cooperative banks on the example of banks belonging to the BPS S.A. association in the period between 2004 and 2020. We used a variety of research methods for this purpose including a depth review of the literature, analysis of statistical data regarding the sector of Polish cooperative banks, analysis of financial data of cooperative banks, construction of an econometric panel model, and the designing a questionnaire (which was later sent to the management board of selected cooperative banks). Our research confirmed the significant impact of the use of scoring models in lending activities on the value of the NPL ratio in cooperative banks. The analysed cooperative banks, which used the scoring models proposed by BIK in their lending activity, showed significantly lower values of the NPL ratio in each analysed year than banks that used other scoring models. Our study also confirmed the different direction of the impact of the models offered by BIK and individual scoring models on the value of the NPL ratio. We have also shown that the scoring models proposed by BIK have a statistically significant negative impact on the level of the NPL ratio, and the banks’ own scoring models have a statistically significant positive impact on the level of the NPL ratio. Full article

(This article belongs to the Special Issue Credit Risk Management)

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16 pages, 872 KiB

Open AccessArticle

A New Tool for Covering Risk in Agriculture: The Revenue Insurance Policy

by Angelo Frascarelli, Simone Del Sarto and Giada Mastandrea

Risks 2021, 9(7), 131; https://doi.org/10.3390/risks9070131 - 12 Jul 2021

Cited by 5 | Viewed by 3084

Abstract

Over the last years, the agricultural sector has faced increasing risks related not only to production activities, but also to climate adversity and a higher frequency of extreme events. These factors, combined with increased price volatility in the markets, have caused greater exposure [...] Read more.

Over the last years, the agricultural sector has faced increasing risks related not only to production activities, but also to climate adversity and a higher frequency of extreme events. These factors, combined with increased price volatility in the markets, have caused greater exposure to risk for farmers. For this reason, risk management in agriculture has taken on an important role within the Common Agricultural Policy. However, in recent years, gradual disaffection of farmers, low penetration of insurance in the arable sector, and a greater need for insurance coverage against market risks have characterised the subsidised risk management system. For all these reasons, starting in 2017, the National Agricultural Insurance Plan has provided new possibilities for covering risks. This paper aims to contribute to the debate on risk management linked to the revenue insurance policy recently adopted in Italy. Using data from the Italian Farm Accountancy Data Network, we simulate the application of the revenue insurance policy with a sample of Italian farms operating in the common and durum wheat sectors. The main findings show that the revenue insurance policy stipulation is, overall, sustainable for both farms and insurance companies. Full article

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19 pages, 1778 KiB

Open AccessArticle

Risk Factors Affecting Bancassurance Development in Poland

by Adam Śliwiński, Joanna Dropia and Norbert Duczkowski

Risks 2021, 9(7), 130; https://doi.org/10.3390/risks9070130 - 07 Jul 2021

Cited by 3 | Viewed by 3513

Abstract

The aim of the article is to identify the risk factors affecting bancassurance development in Poland. The development is understood here as a change of gross written premiums obtained through banks in Poland. The group of risk factors selected in a survey conducted [...] Read more.

The aim of the article is to identify the risk factors affecting bancassurance development in Poland. The development is understood here as a change of gross written premiums obtained through banks in Poland. The group of risk factors selected in a survey conducted among financial sector employees was subject to statistical verification. The analysis used both variables directly related to the insurance product (e.g., a regulatory restriction of insurance acquisition costs) as well as those resulting from the specificity of the bancassurance channel, such as the sales of banking products, i.e., cash loans, housing loans and the value of funds placed by customers on deposits. The study was conducted on the basis of data on the gross premiums written in Poland in the years 2004–2019. The result of the applied model confirms the assumptions and the importance of insurance distribution in banks. Significant risk factors (statistically significant) which determine gross premiums written in the bancassurance channel are: the size of policyholder’s family (number of children, dependants) represented by the average number of people in a household in Poland, demand on mortgage loans represents by bank housing loans for households and agent’s commission, represented by the ratio of acquisition costs to gross written premium. The results of the econometric model obtained are consistent with expectations arising from the principles and practice of cooperation between banks and insurers as well as the specificity of insurance products distribution (also local) in the bancassurance channel. Full article

(This article belongs to the Special Issue Data Analysis for Risk Management – Economics, Finance and Business)

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46 pages, 2383 KiB

Open AccessArticle

Reliability of Seismic Performance Assessments for Individual Buildings and Portfolios

by Charles C. Thiel, Jr., Theodore C. Zsutty and Yajie J. Lee

Risks 2021, 9(7), 129; https://doi.org/10.3390/risks9070129 - 06 Jul 2021

Cited by 3 | Viewed by 2248

Abstract

Seismic performance and loss assessments are required in areas of Insurance, Finance and Public Policy. Providers are Structural Engineers and Risk Management Firms. There are no current procedures to evaluate the epistemic and aleatory uncertainties for such assessments. The essential issue is whether [...] Read more.

Seismic performance and loss assessments are required in areas of Insurance, Finance and Public Policy. Providers are Structural Engineers and Risk Management Firms. There are no current procedures to evaluate the epistemic and aleatory uncertainties for such assessments. The essential issue is whether or not there is sufficient reliability in the result to use the result as the basis for risk management decisions and actions. For a single building this may be whether or not a prescribed earthquake performance level is met, life safety or if a portfolio’s vulnerability level is acceptable, whether the. loss for a given time period is less than a stated value. A method based in part on Federal Emergency Management Agency P-695, is developed for evaluating the reliability of performance and/or loss assessments for both individual and portfolios of buildings. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the building evaluation, the technical validity of the assessment procedure or model and what computational reliabilities are presented. The method characterizes the uncertainty of each component of the assessment procedure for each building by qualitative determined assignments. The resulting reliability measure is likely to be most useful for determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low loss risk over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment. Full article

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20 pages, 5473 KiB

Open AccessReview

A Bibliometric Analysis of Objective and Subjective Risk

by Haitham Nobanee, Maryam Alhajjar, Mohammed Ahmed Alkaabi, Majed Musabah Almemari, Mohamed Abdulla Alhassani, Naema Khamis Alkaabi, Saeed Abdulla Alshamsi and Hanan Hamed AlBlooshi

Risks 2021, 9(7), 128; https://doi.org/10.3390/risks9070128 - 04 Jul 2021

Cited by 5 | Viewed by 10946

Abstract

In relation to “objective risk” or “subjective risk”, a bibliometric analysis was performed using documents found in the Scopus database. A search for related documents was narrowed down to 192 documents and these were considered in this study. The results of this study [...] Read more.

In relation to “objective risk” or “subjective risk”, a bibliometric analysis was performed using documents found in the Scopus database. A search for related documents was narrowed down to 192 documents and these were considered in this study. The results of this study suggest that the use of the ranking method and descriptive statistics is not sufficient in presenting a concise bibliometric analysis. To create a more in-depth bibliometric analysis, the results of this study have to be analyzed together with a visualization map using VOSviewer software. This way, researchers can easily locate a specific gap in the literature, understand the relation between the papers on the same subject, and cite the literature studies based on their effectiveness. Full article

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19 pages, 390 KiB

Open AccessArticle

Progressive Pension Formula and Life Expectancy Heterogeneity

by Keivan Diakite and Pierre Devolder

Risks 2021, 9(7), 127; https://doi.org/10.3390/risks9070127 - 03 Jul 2021

Cited by 5 | Viewed by 2418

Abstract

An increasing number of empirical studies have shown a positive relationship between lifetime income and life expectancy at retirement. One’s income during the active part of one’s career translates into the amount of retirement benefits one might receive, leading to actuarial unfairness inside [...] Read more.

An increasing number of empirical studies have shown a positive relationship between lifetime income and life expectancy at retirement. One’s income during the active part of one’s career translates into the amount of retirement benefits one might receive, leading to actuarial unfairness inside cohorts of retirees. In order to discuss unfairness and sustainability issues, the Belgium pension reform committee issued a proposal for a point system designed to be both sustainable and adequate. In this paper, we use a similar defined benefit framework in order to set out a compensation mechanism linked to life expectancy heterogeneity during the active part of the career, aiming to reduce unfairness once reaching retirement. This method is based on the progressivity of pension benefit formulae. We implement these ideas in a simple demographic context in order to capture the constraints related to the model. Full article

(This article belongs to the Special Issue Pension Design, Modelling and Risk Management)

21 pages, 825 KiB

Open AccessArticle

Improving Explainability of Major Risk Factors in Artificial Neural Networks for Auto Insurance Rate Regulation

by Shengkun Xie

Risks 2021, 9(7), 126; https://doi.org/10.3390/risks9070126 - 02 Jul 2021

Cited by 5 | Viewed by 2645

Abstract

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model explainability [...] Read more.

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model explainability may be essential to meet insurance pricing transparency for rate regulation purposes. This requirement may imply the need for estimating or evaluating the variable importance when complicated models are used. Furthermore, from both rate-making and rate-regulation perspectives, it is critical to investigate the impact of major risk factors on the response variables, such as claim frequency or claim severity. In this work, we consider the modelling problems of how claim counts, claim amounts and average loss per claim are related to major risk factors. ANN models are applied to meet this goal, and variable importance is measured to improve the model’s explainability due to the models’ complex nature. The results obtained from different variable importance measurements are compared, and dominant risk factors are identified. The contribution of this work is in making advanced mathematical models possible for applications in auto insurance rate regulation. This study focuses on analyzing major risks only, but the proposed method can be applied to more general insurance pricing problems when additional risk factors are being considered. In addition, the proposed methodology is useful for other business applications where statistical machine learning techniques are used. Full article

(This article belongs to the Special Issue Risks: Feature Papers 2021)

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21 pages, 2298 KiB

Open AccessArticle

The Combined Stop-Loss and Quota-Share Reinsurance: Conditional Tail Expectation-Based Optimization from the Joint Perspective of Insurer and Reinsurer

by Khreshna Syuhada, Arief Hakim and Suci Sari

Risks 2021, 9(7), 125; https://doi.org/10.3390/risks9070125 - 01 Jul 2021

Cited by 2 | Viewed by 3395

Abstract

In the presence of reinsurance, an insurer may effectively reduce its (aggregated) loss by partially ceding such a loss to a reinsurer. Stop-loss and quota-share reinsurance contracts are commonly agreed between these two parties. In this paper, we aim to explore a combination [...] Read more.

In the presence of reinsurance, an insurer may effectively reduce its (aggregated) loss by partially ceding such a loss to a reinsurer. Stop-loss and quota-share reinsurance contracts are commonly agreed between these two parties. In this paper, we aim to explore a combination of these contracts. The survival functions of the ceded loss and the retained loss are firstly investigated. Optimizing such a reinsurance design is then carried out from the joint perspective of the insurer and the reinsurer. Specifically, we explicitly derive optimal retentions under a criterion of minimizing a convex combination of conditional tail expectations of the insurer’s total loss and the reinsurer’s total loss. In addition, an estimation procedure and more explanations on numerical examples are also presented to find their estimated values. Full article

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29 pages, 5306 KiB

Open AccessArticle

Systemic Illiquidity Noise-Based Measure—A Solution for Systemic Liquidity Monitoring in Frontier and Emerging Markets

by Ewa Dziwok and Marta A. Karaś

Risks 2021, 9(7), 124; https://doi.org/10.3390/risks9070124 - 01 Jul 2021

Cited by 4 | Viewed by 2412

Abstract

The paper presents an alternative approach to measuring systemic illiquidity applicable to countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize [...] Read more.

The paper presents an alternative approach to measuring systemic illiquidity applicable to countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize the curve-fitting error as an indicator of financial system illiquidity. We empirically apply our method to a set of 10 divergent Central and Eastern Europe countries—Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia—in the period of 2006–2020. The results show three periods of increased risk in the sample period: the global financial crisis, the European public debt crisis, and the COVID-19 pandemic. They also allow us to identify three divergent sets of countries with different systemic liquidity risk characteristics. The analysis also illustrates the impact of the introduction of the euro on systemic illiquidity risk. The proposed methodology may be of consequence for financial system regulators and macroprudential bodies: it allows for contemporaneous monitoring of discussed risk at a minimal cost using well-known models and easily accessible data. Full article

(This article belongs to the Special Issue Data Analysis for Risk Management – Economics, Finance and Business)

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16 pages, 7212 KiB

Open AccessArticle

Bibliometric Analysis of the Literature on Measuring Techniques for Manipulating Financial Statements

by Ioana Lavinia Safta, Andrada-Ioana Sabău (Popa) and Neli Muntean

Risks 2021, 9(7), 123; https://doi.org/10.3390/risks9070123 - 01 Jul 2021

Cited by 4 | Viewed by 3340

Abstract

Creative accounting has its background since early studies in 1975, until the present time. It continues to be a subject of great interest for the companies and interested parties. Thus, the current paper will aim to answer the following proposed research questions: 1. [...] Read more.

Creative accounting has its background since early studies in 1975, until the present time. It continues to be a subject of great interest for the companies and interested parties. Thus, the current paper will aim to answer the following proposed research questions: 1. Which are the most used methods for detecting the manipulation of financial statements in the literature? 2. Which are the terms that are most frequently encountered in the literature associated with “creative accounting? 3. Which are the journals that have the highest frequency of articles written on the topic “creative accounting”? 4. Over time, how did research evolve in the field of creative accounting? 5. Which countries are most preoccupied in publishing regarding this topic? To answer the research question 1, the models published in the literature for measuring manipulation techniques through creative accounting were reviewed and analyzed. For the remaining research questions, a bibliometric analysis for the publications in this area was performed. For collecting the sample, articles on this topic were selected from the international Web of Science database. Following this, a bibliometric analysis of the articles was performed, using the VOSviewer program. A total of 4045 publications on creative accounting were identified. Through the bibliometric analysis we have answered research question 2, by identifying the key words that have the closest proximity to creative accounting. To answer the remaining research questions, we identified the journals with the highest frequency of publication and the countries with the highest interest on the topic. It is especially important to evaluate the quality of this many research papers and to obtain valuable information. Full article

(This article belongs to the Special Issue Economic and Financial Crimes)

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22 pages, 461 KiB

Open AccessArticle

Asymptotic Tail Probability of the Discounted Aggregate Claims under Homogeneous, Non-Homogeneous and Mixed Poisson Risk Model

by Franck Adékambi and Kokou Essiomle

Risks 2021, 9(7), 122; https://doi.org/10.3390/risks9070122 - 30 Jun 2021

Cited by 3 | Viewed by 1597

Abstract

In this paper, we derive a closed-form expression of the tail probability of the aggregate discounted claims under homogeneous, non-homogeneous and mixed Poisson risk models with constant force of interest by using a general dependence structure between the inter-occurrence time and the claim [...] Read more.

In this paper, we derive a closed-form expression of the tail probability of the aggregate discounted claims under homogeneous, non-homogeneous and mixed Poisson risk models with constant force of interest by using a general dependence structure between the inter-occurrence time and the claim sizes. This dependence structure is relevant since it is well known that under catastrophic or extreme events the inter-occurrence time and the claim severities are dependent. Full article

19 pages, 3540 KiB

Open AccessArticle

Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods

by Beata Bieszk-Stolorz and Krzysztof Dmytrów

Risks 2021, 9(7), 121; https://doi.org/10.3390/risks9070121 - 22 Jun 2021

Cited by 8 | Viewed by 2361

Abstract

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of [...] Read more.

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of rise of the indices were: Kaplan–Meier estimator, logit model, and the Cox proportional hazards model. We observed the highest intensity of decline in the European stock exchanges, followed by the American and Asian plus Australian ones (after the fourth and eighth week since the peak). The highest risk of decline was in America, then in Europe, followed by Asia and Australia. The lowest risk was in Africa. The intensity of increase was the highest in the fourth and eleventh week since the minimal value had been reached. The highest odds of increase were in the American stock exchanges, followed by the European and Asian (including Australia and Oceania), and the lowest in the African ones. The odds and intensity of increase in the stock exchange indices varied from continent to continent. The increase was faster than the initial decline. Full article

(This article belongs to the Special Issue Financial Stability and Systemic Risk in Times of Pandemic)

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Risks, Volume 9, Issue 7 (July 2021) – 18 articles

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