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Risks, Volume 10, Issue 8 (August 2022) – 25 articles

Cover Story (view full-size image): How to consider the a priori risks in experience-rating models has been questioned in the actuarial community for a long time. Classic past-claim-rating models normalize the past experience of those insured before applying claim penalties. Despite the quality of predictions of the BMS models, this experience-rating model could appear unfair to many of those insured and regulators because it does not recognize the initial risk of the insured. In this paper, we propose the creation of different BMSs for each type of insured using recursive partitioning methods. We apply this approach to real data for the farm insurance product of a major Canadian insurance company with widely varying sizes of those insured. View this paper
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Article
Understanding of Macro Factors That Affect Yield of Government Bonds
Risks 2022, 10(8), 166; https://doi.org/10.3390/risks10080166 - 18 Aug 2022
Viewed by 351
Abstract
Government bonds are one of the safest and most attractive instruments in the investment portfolio for private investors and investment funds. Although bonds are perceived as an alternative to bank deposits, a number of macroeconomic factors influence their yield. The goal of the [...] Read more.
Government bonds are one of the safest and most attractive instruments in the investment portfolio for private investors and investment funds. Although bonds are perceived as an alternative to bank deposits, a number of macroeconomic factors influence their yield. The goal of the research is to investigate the relationship between macroeconomic factors and the yield of government bonds. We use regression models on a dataset of 22 countries with post-industrial economics for ten years. The main criteria for selecting countries are membership in the Organization for Economic Cooperation and Development and inclusion in the Top-25 countries on the competitiveness index. The results revealed a negative association between the yield of government bonds and gold. Moreover, we indicate a positive association between the yield of government bonds and the following indicators—inflation, oil prices, and GDP per capita. In the case of the influence of population savings and the uncertainty index, we obtain inconclusive results. The study contributes to ongoing research in the field of financial management with respect to investigating determinants of the yield of government bonds. Full article
(This article belongs to the Special Issue Risk Analysis and Management in the Digital and Innovation Economy)
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Article
Information Security Risk Assessment Using Situational Awareness Frameworks and Application Tools
Risks 2022, 10(8), 165; https://doi.org/10.3390/risks10080165 - 17 Aug 2022
Viewed by 377
Abstract
This paper describes the development of situational awareness models and applications to assess cybersecurity risks based on Annex ISO 27001:2013. The risk assessment method used is the direct testing method, namely audit, exercise and penetration testing. The risk assessment of this study is [...] Read more.
This paper describes the development of situational awareness models and applications to assess cybersecurity risks based on Annex ISO 27001:2013. The risk assessment method used is the direct testing method, namely audit, exercise and penetration testing. The risk assessment of this study is classified into three levels, namely high, medium and low. A high-risk value is an unacceptable risk value. Meanwhile, low and medium risk values can be categorized as acceptable risk values. The results of a network security case study with security performance index indicators based on the percentage of compliance with ISO 27001:2013 annex controls and the value of the risk level of the findings of the three test methods showed that testing with the audit method was 38.29% with a moderate and high-risk level. While the test results with the tabletop exercise method are 75% with low and moderate risk levels. On the other hand, the results with the penetration test method are 16.66%, with moderate and high-risk levels. Test results with unacceptable risk values or high-risk corrective actions are taken through an application. Finally, corrective actions have been verified to prove there is an increase in cyber resilience and security. Full article
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Article
Time Restrictions on Life Annuity Benefits: Portfolio Risk Profiles
Risks 2022, 10(8), 164; https://doi.org/10.3390/risks10080164 - 12 Aug 2022
Viewed by 345
Abstract
Due to the increasing interest in several markets in life annuity products with a guaranteed periodic benefit, the back-side effects of some features that may prove to be critical either for the provider or the customer should be better understood. In this research, [...] Read more.
Due to the increasing interest in several markets in life annuity products with a guaranteed periodic benefit, the back-side effects of some features that may prove to be critical either for the provider or the customer should be better understood. In this research, we focus on the time frames defined by the policy conditions of life annuities. While the payment phase coincides with the post-retirement period in the traditional annuity product, arrangements with alternative time frames are being offered in the market. Time restrictions, in particular, could be welcomed both by customers and providers, as they result in a reduction in expected costs and equivalence premiums. However, due to the different impact of longevity risk on different age ranges, time restrictions could increase risks to the provider, at least in relative terms. On the other hand, time restrictions reduce the duration of the provider’s liability, which should therefore be less exposed to financial risk. We focus on this issue, examining the probability distribution of the total portfolio payout resulting from alternative time frames for life annuity arrangements, first addressing longevity risk only, and then including also financial risk. The discussion is developed in view of understanding whether a reduction in the equivalence premium implied by time restrictions should be matched by higher premium loading and required capital rates. Full article
(This article belongs to the Special Issue Longevity Risk Modelling and Management)
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Article
Risks of Entrepreneurship amid the COVID-19 Crisis
Risks 2022, 10(8), 163; https://doi.org/10.3390/risks10080163 - 11 Aug 2022
Viewed by 347
Abstract
The COVID-19 crisis is unique in that it is caused by a pandemic and has created a special context for entrepreneurship in 2020. The motivation for this study is, firstly, to concretise and accurately quantify the impacts of the pandemic on entrepreneurship. Secondly, [...] Read more.
The COVID-19 crisis is unique in that it is caused by a pandemic and has created a special context for entrepreneurship in 2020. The motivation for this study is, firstly, to concretise and accurately quantify the impacts of the pandemic on entrepreneurship. Secondly, to clearly identify the specific business risks emerging or intensifying in the context of the pandemic; and thirdly, to distinguish between the impact of the economic crisis and the pandemic on entrepreneurship. This paper aims at studying the risks of entrepreneurship amid the COVID-19 pandemic and crisis. The paper’s sample consists of the top 10 countries that are leaders by the COVID-19 case rate in the world, starting 22 October 2020 up to 22 February 2022. The method of trend analysis is used to find and quantitatively measure the manifestations of the pandemic (case rate and mortality) on the entrepreneurial risks. Economic and mathematical modelling, with the help of correlation and regression analysis, showed that healthcare factors—the COVID-19 case rate and mortality—are not the key reasons for high entrepreneurial risks in 2020 and have a small influence on them. This paper’s contribution to the literature consists in specifying the cause-and-effect links between the COVID-19 pandemic and crisis and entrepreneurial risks. The theoretical significance of the results obtained consists in their proving the uniqueness of the COVID-19 crisis from the position of entrepreneurial risks. The paper’s originality consists in specifying the influence of the COVID-19 pandemic on entrepreneurial risks, explaining—thoroughly and in detail—the essence of these risks, and opening possibilities for highly-effective risk management. Full article
(This article belongs to the Special Issue The COVID-19 Crisis: Datasets and Data Analysis to Reduce Risks)
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Article
Factors of Risk Analysis for IoT Systems
Risks 2022, 10(8), 162; https://doi.org/10.3390/risks10080162 - 10 Aug 2022
Viewed by 428
Abstract
The increasing rate at which IoT technologies are being developed has enabled smarter and innovative solutions in the sectors of health, energy, transportation, etc. Unfortunately, some inherent characteristics of these technologies are compromised to attack. Naturally, risk analysis emerges, as it is one [...] Read more.
The increasing rate at which IoT technologies are being developed has enabled smarter and innovative solutions in the sectors of health, energy, transportation, etc. Unfortunately, some inherent characteristics of these technologies are compromised to attack. Naturally, risk analysis emerges, as it is one of many steps to provide a reliable security strategy. However, the methodologies of any risk analysis must first adapt to the dynamics of the IoT system. This article seeks to shed light on whatever factors are part of an IoT system and thus contribute to security risks, IoT device vulnerabilities, susceptibility due to the application domain, attack surfaces, and interdependence as a product of the interconnection between IoT devices. Consequently, the importance of these factors in any risk evaluation is highlighted, especially the interdependence generated by IoT systems, which can cause the generation of an uncontrollable cascade of effects that can occur under certain conditions of any systematic risk event. Full article
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Article
A New Mortality Framework to Identify Trends and Structural Changes in Mortality Improvement and Its Application in Forecasting
Risks 2022, 10(8), 161; https://doi.org/10.3390/risks10080161 - 10 Aug 2022
Viewed by 316
Abstract
We construct a new age-specific mortality framework and implement an exemplar (DLGC) that provides an excellent fit to data from various countries and across long time periods while also providing accurate mortality forecasts by projecting parameters with ARIMA models. The model parameters have [...] Read more.
We construct a new age-specific mortality framework and implement an exemplar (DLGC) that provides an excellent fit to data from various countries and across long time periods while also providing accurate mortality forecasts by projecting parameters with ARIMA models. The model parameters have clear and reasonable interpretations that, after fitting, show stable time trends that react to major world mortality events. These trends are similar for countries with similar life-expectancies and capture mortality improvement, mortality structural change, and mortality compression over time. The parameter time plots can also be used to improve forecasting accuracy by suggesting training data periods and appropriate stochastic assumptions for parameters over time. We also give a quantitative analysis on what factors contribute to increased life expectancy and gender mortality differences during different age periods. Full article
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Article
Optimal Liquidation, Acquisition and Market Making Problems in HFT under Hawkes Models for LOB
Risks 2022, 10(8), 160; https://doi.org/10.3390/risks10080160 - 09 Aug 2022
Viewed by 342
Abstract
The present paper is focused on the solution of optimal control problems such as optimal acquisition, optimal liquidation, and market making in relation to the high-frequency trading market. We have modeled optimal control problems with the price approximated by the diffusion process for [...] Read more.
The present paper is focused on the solution of optimal control problems such as optimal acquisition, optimal liquidation, and market making in relation to the high-frequency trading market. We have modeled optimal control problems with the price approximated by the diffusion process for the general compound Hawkes process (GCHP), using results from the work of Swishchuk and Huffman. These problems have been solvedusing a price process incorporating the unique characteristics of the GCHP. The GCHP was designed to reflect important characteristics of the behaviour of real-world price processes such as the dependence on the previous process and jumping features. In these models, the agent maximizes their own utility or value function by solving the Hamilton–Jacobi–Bellman (HJB) equation and designing a strategy for asset trading. The optimal solutions are expressed in terms of parameters describing the arrival rates and the midprice process from the price process, modeled as a GCHP, allowing such characteristics to influence the optimization process, aiming towards the attainment of a more general solution. Implementations of the obtained results were carried out using real LOBster data. Full article
(This article belongs to the Special Issue Stochastic Modeling and Computational Statistics in Finance)
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Article
Investor Segments by Perceived Project Risk and Their Characteristics Based on Primary Research Results
Risks 2022, 10(8), 159; https://doi.org/10.3390/risks10080159 - 04 Aug 2022
Viewed by 406
Abstract
Our research focuses on investment initiatives. The perceived risks are analysed from the consumer’s viewpoint, i.e., the client’s perspective, from the standpoint of the project. In the literature, there are several risk interpretations and classifications. We assumed it could be interesting and valuable [...] Read more.
Our research focuses on investment initiatives. The perceived risks are analysed from the consumer’s viewpoint, i.e., the client’s perspective, from the standpoint of the project. In the literature, there are several risk interpretations and classifications. We assumed it could be interesting and valuable to approach investment projects from a consumer-oriented viewpoint, considering that the perceived and consumer-identified set of risks is a major determinant of the outcome of a decision. In addition to relevant secondary sources, we also present partial results of our primary research project. A pre-tested, standardised online questionnaire was employed in the primary study, using a snowball sampling approach generating 1545 evaluable questionnaires. As a result of the research, we were able to segment the customer (investor) target groups into various categories depending on the perceived project risk. We have established the orientation directions along which these segments may well be meaningfully described in terms of perceived investment risk concerns and socio-demographic characteristics that influence cluster membership. In our opinion, the findings may be a useful source of information for investment project developers looking to identify consumer groups based on risk perception and build project solutions for them. Full article
(This article belongs to the Special Issue Quantitative Risk Management in Agribusiness)
Article
Predicting Co-Movement of Banking Stocks Using Orthogonal GARCH
Risks 2022, 10(8), 158; https://doi.org/10.3390/risks10080158 - 02 Aug 2022
Viewed by 379
Abstract
This study investigates the application of orthogonal generalized auto-regressive conditional heteroscedasticity (OGARCH) in predicting the co-movement of banking sector stocks in Indonesia. All state-owned banking sector stocks in Indonesia were studied using daily data from January 2013 to December 2019. The findings indicate [...] Read more.
This study investigates the application of orthogonal generalized auto-regressive conditional heteroscedasticity (OGARCH) in predicting the co-movement of banking sector stocks in Indonesia. All state-owned banking sector stocks in Indonesia were studied using daily data from January 2013 to December 2019. The findings indicate that the OGARCH method can simplify the covariance matrix. Most state-owned banking stocks in the banking sector have a similar principal component influencing their conditional variance. Nonetheless, one stock has different principal components. The findings imply that combining the state-owned banking stocks with different principal components effectively reduces the risk of state-owned banking stock portfolios. Full article
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Article
Impact of Capital Structure on Profitability: Panel Data Evidence of the Telecom Industry in the United States
Risks 2022, 10(8), 157; https://doi.org/10.3390/risks10080157 - 02 Aug 2022
Viewed by 448
Abstract
Debt finance, when considered a source of finance, always leads to financial risk; however, it is also considered a source of increased profitability in the normal business scenario. It has always been challenging to find the correct debt equity combination. In the discussed [...] Read more.
Debt finance, when considered a source of finance, always leads to financial risk; however, it is also considered a source of increased profitability in the normal business scenario. It has always been challenging to find the correct debt equity combination. In the discussed sample of the telecom industry in the USA, an abnormally high total liability-to-total assets ratio was observed. Thus, it is inclined to investigate the capital structure (CapSt) effect on firms’ profitability. By taking annual data of the telecom industry from 2012 to 2020 in the USA, unbalanced cross-sectional data (panel data) comprising 421 firm-year observations for 72 firms were studied using pooled panel regression, univariate analysis, correlation, and descriptive statistics models. We decided to test the impact of CapSt (Total Liabilities to Total Assets (TLsTAs) and Total Equity to Total Assets (TETAs)) on the profitability (Return on Assets (ROA) and Return on Equity (ROE)) of firms in the telecommunication industry in the USA. The results reveal that the ratio of TLsTAs has a significant impact on ROA, and TETAs has a significant impact on ROA. However, TLsTAs and TETAs have no impact on ROE. Full article
Article
Probability Density of Lognormal Fractional SABR Model
Risks 2022, 10(8), 156; https://doi.org/10.3390/risks10080156 - 02 Aug 2022
Viewed by 301
Abstract
Instantaneous volatility of logarithmic return in the lognormal fractional SABR model is driven by the exponentiation of a correlated fractional Brownian motion. Due to the mixed nature of driving Brownian and fractional Brownian motions, probability density for such a model is less studied [...] Read more.
Instantaneous volatility of logarithmic return in the lognormal fractional SABR model is driven by the exponentiation of a correlated fractional Brownian motion. Due to the mixed nature of driving Brownian and fractional Brownian motions, probability density for such a model is less studied in the literature. We show in this paper a bridge representation for the joint density of the lognormal fractional SABR model in a Fourier space. Evaluating the bridge representation along a properly chosen deterministic path yields a small time asymptotic expansion to the leading order for the probability density of the fractional SABR model. A direct generalization of the representation of joint density often leads to a heuristic derivation of the large deviations principle for joint density in a small time. Approximation of implied volatility is readily obtained by applying the Laplace asymptotic formula to the call or put prices and comparing coefficients. Full article
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Review
How Do Life Insurers Respond to a Prolonged Low Interest Rate Environment? A Literature Review
Risks 2022, 10(8), 155; https://doi.org/10.3390/risks10080155 - 02 Aug 2022
Viewed by 528
Abstract
Life insurers, whose contractual liabilities include providing minimum guaranteed interest rates to policyholders, are significantly affected by persistently low interest rates. Hence, this study reviews the literature on the prolonged low interest rate environment and its impact on the life insurance industry, incorporating [...] Read more.
Life insurers, whose contractual liabilities include providing minimum guaranteed interest rates to policyholders, are significantly affected by persistently low interest rates. Hence, this study reviews the literature on the prolonged low interest rate environment and its impact on the life insurance industry, incorporating multiple perspectives and practices in different countries. The effect of low interest rates on life insurance products depends on the sensitivity of the interest rate of each product type and the level of minimum interest rate guarantee. In addition, their impacts on the valuation of life insurance companies depend on shifts in the valuation interest rate, which is used to discount the present value of future benefits, as well as the financial and solvency issues faced by insurers. Overall, the literature suggests that insurers need both short- and long-term solutions to respond to a prolonged low interest rate environment. Full article
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Article
Robust Classification via Support Vector Machines
Risks 2022, 10(8), 154; https://doi.org/10.3390/risks10080154 - 01 Aug 2022
Viewed by 468
Abstract
Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data uncertainty via [...] Read more.
Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data uncertainty via two probabilistic arguments. The first classifier, Single Perturbation, reduces the local effect of data uncertainty with respect to one given feature and acts as a local test that could confirm or refute the presence of significant data uncertainty for that particular feature. The second classifier, Extreme Empirical Loss, aims to reduce the aggregate effect of data uncertainty with respect to all features, which is possible via a trade-off between the number of prediction model violations and the size of these violations. Both methodologies are computationally efficient and our extensive numerical investigation highlights the advantages and possible limitations of the two robust classifiers on synthetic and real-life insurance claims and mortgage lending data, but also the fairness of an automatized decision based on our classifier. Full article
(This article belongs to the Special Issue Data Science in Insurance)
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Article
A Comparison of Macaulay Approximations
Risks 2022, 10(8), 153; https://doi.org/10.3390/risks10080153 - 29 Jul 2022
Viewed by 353
Abstract
We discuss several known formulas that use the Macaulay duration and convexity of commonly used cash flow streams to approximate their net present value, and compare them with a new approximation formula that involves hyperbolic functions. Our objective is to assess the reliability [...] Read more.
We discuss several known formulas that use the Macaulay duration and convexity of commonly used cash flow streams to approximate their net present value, and compare them with a new approximation formula that involves hyperbolic functions. Our objective is to assess the reliability of each approximation formula under different scenarios. The results in this note should be of interest to actuarial candidates and educators as well as analysts working in all areas of actuarial practice. Full article
(This article belongs to the Special Issue Actuarial Mathematics and Risk Management)
Article
Multiple Bonus–Malus Scale Models for Insureds of Different Sizes
Risks 2022, 10(8), 152; https://doi.org/10.3390/risks10080152 - 28 Jul 2022
Cited by 1 | Viewed by 312
Abstract
How to consider the a priori risks in experience-rating models has been questioned in the actuarial community for a long time. Classic past-claim-rating models, such as the Buhlmann–Straub credibility model, normalize the past experience of each insured before applying claim penalties. On the [...] Read more.
How to consider the a priori risks in experience-rating models has been questioned in the actuarial community for a long time. Classic past-claim-rating models, such as the Buhlmann–Straub credibility model, normalize the past experience of each insured before applying claim penalties. On the other hand, classic Bonus–Malus Scales (BMS) models generate the same surcharges and the same discounts for all insureds because the transition rules within the class system do not depend on the a priori risk. Despite the quality of prediction of the BMS models, this experience-rating model could appear unfair to many insureds and regulators because it does not recognize the initial risk of the insured. In this paper, we propose the creation of different BMSs for each type of insured using recursive partitioning methods. We apply this approach to real data for the farm insurance product of a major Canadian insurance company with widely varying sizes of insureds. Because the a priori risk can change over time, a study of the possible transitions between different BMS models is also performed. Full article
(This article belongs to the Special Issue Data Science in Insurance)
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Article
An Efficient Method for Pricing Analysis Based on Neural Networks
Risks 2022, 10(8), 151; https://doi.org/10.3390/risks10080151 - 28 Jul 2022
Viewed by 348
Abstract
The revolution in neural networks is a significant technological shift. It has an impact on not only all aspects of production and life, but also economic research. Neural networks have not only been a significant tool for economic study in recent years, but [...] Read more.
The revolution in neural networks is a significant technological shift. It has an impact on not only all aspects of production and life, but also economic research. Neural networks have not only been a significant tool for economic study in recent years, but have also become an important topic of economics research, resulting in a large body of literature. The stock market is an important part of the country’s economic development, as well as our daily lives. Large dimensions and multiple collinearity characterize the stock index data. To minimize the number of dimensions in the data, multiple collinearity should be removed, and the stock price can then be forecast. To begin, a deep autoencoder based on the Restricted Boltzmann machine is built to encode high-dimensional input into low-dimensional space. Then, using a BP neural network, a regression model is created between low-dimensional coding sequence and stock price. The deep autoencoder’s capacity to extract this feature is superior to that of principal component analysis and factor analysis, according to the findings of the experiments. Utilizing the coded data, the proposed model can lower the computational cost and achieve higher prediction accuracy than using the original high-dimensional data. Full article
(This article belongs to the Special Issue Data Analysis for Risk Management – Economics, Finance and Business)
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Article
The Determinant of Sukuk Rating: Agency Theory and Asymmetry Theory Perspectives
Risks 2022, 10(8), 150; https://doi.org/10.3390/risks10080150 - 27 Jul 2022
Viewed by 363
Abstract
This research aims to develop a determinant variable of the Sukuk rating derived from agency and asymmetry theories. This research is essential because Sukuk or Islamic Bonds is needed in Indonesia, with 85% of its population out of 320 million people being Muslim. [...] Read more.
This research aims to develop a determinant variable of the Sukuk rating derived from agency and asymmetry theories. This research is essential because Sukuk or Islamic Bonds is needed in Indonesia, with 85% of its population out of 320 million people being Muslim. Many studies on the determinants of Sukuk ratings have been conducted and are still trending research. However, they are rarely observed from the perspective of agency and asymmetry theories, which are the basis for the relationship between principals and investors. The relationship produces three primary variables in the Sukuk rating determinants, namely financial disclosure quality (FDQ), accounting-based risks (ABRs), and earnings management (EM). This research used 570 panel annual reports from 2018 to 2020 and involved 190 firm-issued Sukuk. Meanwhile, the variables’ reflection used several indicators. SEM (structural equation modeling) was used for the statistical analysis with the help of PLS—primarily smart PLS version. The results exposed that FDQ, ABRs, and EM derived from the two theories are affected significantly by the determinant of the Sukuk rating. In comparison, earnings management successfully moderates the FDQ and Sukuk rating variables but fails to moderate the ABRs to the Sukuk rating. The conclusion also revealed that these relationship theories are fundamental in developing the Sukuk rating. However, the variables should be more complex for future research. With significant results, the agency and asymmetry theories proxied by three variables can explain the Sukuk rating. Accordingly, these theories are relevant as approaches in determining important factors of the Sukuk rating. Full article
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Article
Accounting Beta as an Indicator of Risk Measurement: The Case of the Casablanca Stock Exchange
Risks 2022, 10(8), 149; https://doi.org/10.3390/risks10080149 - 26 Jul 2022
Viewed by 427
Abstract
The problem of determining the cost of equity is crucial to the development of organizations. It is an essential means of calculating value creation. The financial literature has proposed several models for estimating the cost of equity, such as the capital asset pricing [...] Read more.
The problem of determining the cost of equity is crucial to the development of organizations. It is an essential means of calculating value creation. The financial literature has proposed several models for estimating the cost of equity, such as the capital asset pricing model (CAPM). However, this model is only used for listed companies, and cannot be used for unlisted companies. To remedy this situation, alternative measures of the cost of equity have emerged, such as accounting beta. The main objective of this research was to explore the relationship between market beta and accounting beta calculated using ROA, ROE and net income to demonstrate the ability of accounting beta to measure risk for unlisted companies. To carry out this study, we exploited data from a sample of 49 companies listed on the Casablanca Stock Exchange during the period of 2015–2019. We used panel data econometrics to empirically test the research hypotheses. The results show that the accounting beta calculated using ROA and ROE significantly represents the market beta and is a satisfactory solution to calculate the cost of equity of unlisted firms. The results of the study contribute to the existing literature on the cost of capital by reinforcing the role of accounting beta as a solution for determining the cost of equity and therefore the creation of value for the organization. Full article
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Article
Pricing Energy Derivatives in Markets Driven by Tempered Stable and CGMY Processes of Ornstein–Uhlenbeck Type
Risks 2022, 10(8), 148; https://doi.org/10.3390/risks10080148 - 26 Jul 2022
Viewed by 336
Abstract
In this study, we consider the pricing of energy derivatives when the evolution of spot prices follows a tempered stable or a CGMY-driven Ornstein–Uhlenbeck process. To this end, we first calculate the characteristic function of the transition law of such processes in closed [...] Read more.
In this study, we consider the pricing of energy derivatives when the evolution of spot prices follows a tempered stable or a CGMY-driven Ornstein–Uhlenbeck process. To this end, we first calculate the characteristic function of the transition law of such processes in closed form. This result is instrumental for the derivation of nonarbitrage conditions such that the spot dynamics is consistent with the forward curve. Moreover, we also conceive efficient algorithms for the exact simulation of the skeleton of such processes and propose a novel procedure when they coincide with compound Poisson processes of Ornstein–Uhlenbeck type. We illustrate the applicability of the theoretical findings and the simulation algorithms in the context of pricing different contracts, namely strips of daily call options, Asian options with European style and swing options. Full article
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Article
A New Fourier Approach under the Lee-Carter Model for Incorporating Time-Varying Age Patterns of Structural Changes
Risks 2022, 10(8), 147; https://doi.org/10.3390/risks10080147 - 25 Jul 2022
Viewed by 319
Abstract
The prediction of future mortality improvements is of substantial importance for areas such as population projection, government welfare policies, pension planning and annuity pricing. The Lee-Carter model is one of the widely applied mortality models proposed to capture and predict the trend in [...] Read more.
The prediction of future mortality improvements is of substantial importance for areas such as population projection, government welfare policies, pension planning and annuity pricing. The Lee-Carter model is one of the widely applied mortality models proposed to capture and predict the trend in mortality reductions. However, some studies have identified the presence of structural changes in historical mortality data, which makes the forecasting performance of mortality models sensitive to the calibration period. Although some attention has been paid to investigating the time or period effects of structural shifts, the potential time-varying age patterns are often overlooked. This paper proposes a new approach that applies a Fourier series with time-varying parameters to the age sensitivity factor in the Lee-Carter model to study the evolution of age effects. Since modelling the age effects is separated from modelling the period effects, the proposed model can incorporate these two sources of structural changes into mortality predictions. Our backtesting results suggest that structural shifts are present not only in the Lee-Carter mortality index over time, but also in the sensitivity to those time variations at different ages. Full article
(This article belongs to the Special Issue Risks: Feature Papers 2022)
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Article
The Credit Risk Problem—A Developing Country Case Study
Risks 2022, 10(8), 146; https://doi.org/10.3390/risks10080146 - 22 Jul 2022
Viewed by 396
Abstract
Crediting represents one of the biggest risks faced by the banking sector, and especially by commercial banks. In the literature, there have been a number of studies concerning credit risk management, often involving credit scoring systems making use of machine learning (ML) techniques. [...] Read more.
Crediting represents one of the biggest risks faced by the banking sector, and especially by commercial banks. In the literature, there have been a number of studies concerning credit risk management, often involving credit scoring systems making use of machine learning (ML) techniques. However, the specificity of individual banks’ datasets means that choosing the techniques best suited to the needs of a given bank is far from straightforward. This study was motivated by the need by Credins Bank in Tirana for a reliable customer credit scoring tool suitable for use with that bank’s specific dataset. The dataset in question presents two substantial difficulties: first, a high degree of imbalance, and second, a high level of bias together with a low level of confidence in the recorded data. These shortcomings are largely due to the relatively young age of the private banking system in Albania, which did not exist as such until the early 2000s. They are shortcomings not encountered in the more conventional datasets that feature in the literature. The present study therefore has a real contribution to make to the existing corpus of research on credit scoring. The first important question to be addressed is the level of imbalance. In practice, the proportion of good customers may be many times that of bad customers, making the impact of unbalanced data on classification models an important element to be considered. The second question relates to bias or incompleteness in customer information in emerging and developing countries, where economies tend to function with a large amount of informality. Our objective in this study was identifying the most appropriate ML methods to handle Credins Bank’s specific dataset, and the various tests that we performed for this purpose yielded abundant numerical results. Our overall finding on the strength of these results was that this kind of dataset can best be dealt with using balanced random forest methods. Full article
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Article
Chain Reaction of Behavioral Bias and Risky Investment Decision in Indonesian Nascent Investors
Risks 2022, 10(8), 145; https://doi.org/10.3390/risks10080145 - 22 Jul 2022
Viewed by 342
Abstract
Early investors possess unique sets of decision-making characteristics. They are more open to experience and eager to face risks. However, to the best of the authors’ knowledge, the discussions of nascent investors upon making the investment decision and its eroding biases were still [...] Read more.
Early investors possess unique sets of decision-making characteristics. They are more open to experience and eager to face risks. However, to the best of the authors’ knowledge, the discussions of nascent investors upon making the investment decision and its eroding biases were still elusive. The vital role of emotion as a bias in decision making was also inadequately addressed. This study enhanced behavioral finance knowledge by examining emotion’s role in regulating the illusion of control, overconfidence, and investors’ decision making. In total, 456 initial investors in Indonesia participated in online questionnaires, forming the data for covariance-based structural model analysis. This study found that emotion significantly increased the illusion of control, but not overconfidence or decision making, contrary to the bulk of previous studies. The illusion of control exhibited a substantial significant effect of as much as 86.4% toward overconfidence, followed by a considerable increase in decision making. The results of our study also pointed to the unique chain effects of biases affecting the decision-making process of nascent investors in the emerging market. This finding implied they possessed a unique bias mechanism in constructing their decision. Full article
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Article
Bivariate Copula Trees for Gross Loss Aggregation with Positively Dependent Risks
Risks 2022, 10(8), 144; https://doi.org/10.3390/risks10080144 - 22 Jul 2022
Viewed by 591
Abstract
We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula families are studied. At every branching node, the distribution of a [...] Read more.
We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula families are studied. At every branching node, the distribution of a sum of risks is obtained by discrete copula convolution. This approach is compared to approximation by a weighted average of independent and comonotonic distributions. The weight is a measure of positive dependence through variance of the aggregate risk. During gross loss accumulation, the marginals are distorted by application of insurance financial terms, and the value of the mixing weight is impacted. To accelerate computations, we capture this effect using the ratio of standard deviations of pre-term and post-term risks, followed by covariance scaling. We test the performance of our algorithms using three examples of complex insurance portfolios subject to hurricane and earthquake catastrophes. Full article
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Review
The Effect of Option Grants on Managerial Risk Taking: A Review
Risks 2022, 10(8), 143; https://doi.org/10.3390/risks10080143 - 22 Jul 2022
Viewed by 411
Abstract
This article presents a systematic review of the theoretical and empirical literature on option grants and managerial risk taking. One of the objectives is the motivation of further research on the topic. Risk-averse managers hold less diversified portfolios and, thus, tend to take [...] Read more.
This article presents a systematic review of the theoretical and empirical literature on option grants and managerial risk taking. One of the objectives is the motivation of further research on the topic. Risk-averse managers hold less diversified portfolios and, thus, tend to take less risk than optimal for shareholders. More option grants may encourage risk taking and result in higher firm value or alternatively increase the sensitivity of wealth to stock-price fluctuations mitigating overall risk-taking incentives. The net effect of options on risk-taking behavior is, therefore, ambiguous and calls for more empirical investigation. This is crucial for fiscal policymaking and regulation reforms. Yet, establishing a causal link between option granting and managerial risk taking has been challenging due to reverse causality, omitted correlated variables and measurement errors. In this review, we revisit the VegaDelta question by synthesizing the relevant research in economics, finance and accounting. We find that the empirical literature has successfully utilized natural experiments (e.g., regulation changes) to better establish causality, even though some mixed results are also documented. Finally, we also emphasize potential future research avenues especially relating to accounting disclosure, earnings management and tax policy. Full article
Article
Equivalent Risk Indicators: VaR, TCE, and Beyond
Risks 2022, 10(8), 142; https://doi.org/10.3390/risks10080142 - 22 Jul 2022
Cited by 2 | Viewed by 475
Abstract
While a lot of research concentrates on the respective merits of VaR and TCE, which are the two most classic risk indicators used by financial institutions, little has been written on the equivalence between such indicators. Further, TCE, despite its merits, may not [...] Read more.
While a lot of research concentrates on the respective merits of VaR and TCE, which are the two most classic risk indicators used by financial institutions, little has been written on the equivalence between such indicators. Further, TCE, despite its merits, may not be the most accurate indicator to take into account the nature of probability distribution tails. In this paper, we introduce a new risk indicator that extends TCE to take into account higher-order risks. We compare the quantiles of this indicator to the quantiles of VaR in a simple Pareto framework, and then in a generalized Pareto framework. We also examine equivalence results between the quantiles of high-order TCEs. Full article
(This article belongs to the Special Issue Actuarial Mathematics and Risk Management)
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