Risks, Volume 10, Issue 3 (March 2022) – 24 articles

Elasticity is a very popular concept in economics and physics, recently exported and reinterpreted in the statistical field, where it has given form to the so-called elasticity function. This function has proved to be a very useful tool for quantifying and evaluating risks, with applications in disciplines as varied as public health and financial risk management. In this study, we consider the elasticity function in random terms, defining its probability distribution, which allows us to measure for each stochastic process the probability of finding elastic or inelastic situations (i.e., with elasticities greater or less than 1). This new tool, together with new results on the most notable points of the elasticity function covered in this research, offers a new approach to risk assessment, facilitating proactive risk management. The paper also includes other contributions of interest, such as new results that relate elasticity and inverse hazard functions, the derivation of the functional form of the cumulative distribution function of a probability model with constant elasticity and how the elasticities of functionally dependent variables are related. The interested reader can also find in the paper examples of how elasticity cumulative distribution functions are calculated, and an extensive list of probability models with their associated elasticity functions and distributions. Full article

The credit scoring industry has a long tradition of using statistical models for loan default probability prediction. Since this time methodology has strongly evolved, and most of the current research is dedicated to modern machine learning algorithms which contrasts with common practice in the finance industry where traditional regression models still denote the gold standard. In addition, strong emphasis is put on a preliminary binning of variables. Reasons for this may be not only the regulatory requirement of model comprehensiveness but also the possibility to integrate analysts’ expert knowledge in the modelling process. Although several commercial software companies offer specific solutions for modelling credit scorecards, open-source frameworks for this purpose have been missing for a long time. In recent years, this has changed, and today several R packages for credit scorecard modelling are available. This brings the potential to bridge the gap between academic research and industrial practice. The aim of this paper is to give a structured overview of these packages. It may guide users to select the appropriate functions for the desired purpose. Furthermore, this paper will hopefully contribute to future development activities. Full article

Rational small business management necessitates the development of a system for recording important internal information. Companies are obliged to collect statistical data that mainly serves fiscal needs. Exemplary use of such significant data entails financial liquidity (LIQt) and debt recovery efficiency (EVINDt) measures. This work presents constructions of such measures and the manner of their application when they accrue in the form of time series. Both these measures should remain in feedback. Feedback complicates the forecasting of each of the variables that make up this relationship. In the existing forecasting practice, forecasts of such variables have been estimated using empirical equations of a reduced-form model. Such forecasts—in the case of an econometric micromodel—exhibit synchronization properties. This paper presents an empirical system of interdependent equations describing the relationship between financial liquidity and debt collection efficiency. An econometric model was used to build forecasts for both of these characteristics in a small business. An iterative method of forecasting from structural-form equations was used, which guarantees synchronization of forecasts under feedback conditions. The current use of the reduced form of the model to build such forecasts results in divergent forecasts that are not useful in small business management. They can also lead to wrong decisions. In the case under consideration, the forecast value synchronization (convergence) was obtained after five to nine iterations. The more distant the forecasted period is, the greater the number of iterations required to synchronize the forecasts. Full article

Special-rate life annuities are life annuity products whose single premium is based on a mortality assumption driven (at least to some extent) by the health status of the applicant. The health status is ascertained via an appropriate underwriting step (which explains the alternative expression “underwritten life annuities”). Better annuity rates are then applied in presence of poor health conditions. The worse the health conditions, the smaller the modal age at death (as well as the expected lifetime), but the higher the variance of the lifetime distribution. The latter aspect is due to significant data scarcity as well as to the mix of possible pathologies leading to each specific rating class. A higher degree of (partially unobservable) heterogeneity inside each sub-portfolio of special-rate annuities follows, and this results in a higher variability of the total portfolio payout. The present research aims at analyzing the impact of extending the life annuity portfolio by selling special-rate life annuities. Numerical evaluations have been performed by adopting a deterministic approach as well as a stochastic one, according to diverse assumptions concerning both lifetime distributions and portfolio structure and size. Our achievements witness the possibility of extending the annuity business without taking huge amounts of risk. Hence, the risk management objective “enhancing the company market share” can be pursued without significant worsening of the annuity portfolio risk profile. Full article

This study examines the relationship between the financial performance and working capital management practices of South African retail firms listed on the Johannesburg Stock Exchange. The study sample comprised a panel of 16 South African retail firms for the period 2010–2019. A fixed-effects estimator was employed in the analysis. The working capital management was proxied by average age of inventory (AAI), average collection period (ACP), average payment period (APP), and cash conversion cycle (CCC), while the financial performance was proxied by net operating profit margin (NOPM), return on assets (ROA), and return on equity (ROE). The key findings of the study documented the following: (1) There is a negative relationship between average collection period and financial performance. (2) A negative relationship between average age of inventory and financial performance measures (NOPM and ROA) was found. (3) The average payment period was found to be negatively related to return on equity. (4) The cash conversion cycle and net operating profit margin variables were found to be negatively related. The study concludes that working capital management practices influenced the financial performance of the South African retail firms. It is recommended that South African retail firms observe prudent optimal working capital management practices, as these influence their financial performance. Full article

As a result of the COVID-19 pandemic, business and consumer behavior towards online consumption and digital payments has changed. This trend, although significant, may be observed, to a varying extent, among customers across the European Union. This study aims to investigate if, and to what extent, the COVID-19 pandemic has had a powerful impact on online consumer behavior in EU (European Union) countries. The empirical research using a soft modeling method supplements theoretical deliberations based on critical literature review. A conceptual model was adopted. Three first-order latent variables were selected for the analysis: “online customer behavior”, “online activity” and “willingness to spend online”, to which all analyzed indicators (14) were classified. The analysis of the loadings of latent variables for 2019 and 2020 allowed the impact of the pandemic on customer behavior to be observed, although this was not the same across all EU countries. Clustering performed with the hit map enabled the identification of four groups of countries. Significant changes in behavior were observed in countries such as Poland, Ireland, Romania, Hungary, Slovenia, Spain, and Finland. The results of the classification based on the values of three latent variables indicate that only the composition of one group (Bulgaria and Romania) remained unchanged during the study period. Research discussion was presented, and further fields of study were identified. Full article

The main focus of the study is to determine the financial uncertainty while examining the Sukuk bonds prices, Sukuk bond and global emerging market indices returns dynamics. The study, with a time period ranging from 2017 to 2020, applies the quantile regression technique. The study findings show that evidence of co-moment exists between the global emerging market index and Sukuk bond price returns, except the one. There is no impact of the financial uncertainty indicator reflected by the global volatility index (VIX) on the Sukuk index returns, and even this impact is negative for (VXEEM). The causal impact among the global emerging and Sukuk bond markets will help formulate future trading strategies in particular to Islamic bond markets. Full article

This paper investigates whether gender diversity in the boardroom is associated with corporate cash holdings and whether investor protection moderates the effect of corporate board gender diversity on corporate cash holdings. Using 20,750 firm-year observations from 33 countries, our analyses show that firms with high levels of corporate board gender diversity exhibit low corporate cash holdings. Furthermore, firms in countries with high levels of investor protection have low corporate cash holdings. Moreover, the negative association between board gender diversity and corporate cash holdings is weaker in high-level investor protection countries than in low-level investor protection countries. Our results are robust to various specification tests, such as the endogeneity issue, weighted least-squares regression, the global economic crisis effect, alternative measures for corporate cash holdings, and various country-level institutional features. Taken together, the findings reveal that board gender diversity and investor protection have significant influences on corporate cash holdings. These findings have significant implications for politicians, governments, and regulators in devising policies relating to the United Nations Sustainable Development Goal (SDG Number 5) on achieving gender equality and women empowerment. Full article

The rapid growth over recent decades of the impact of natural disasters on economies, especially in vulnerable areas, urges stakeholders to promote innovative solutions involving risk transfers that account for the new risk exposures. These proposed solutions are designed to optimize and expedite the indemnification process, which can ultimately be beneficial for both policyholders and insurers alike. This article explores the possibility of supplementing the current Romanian dwelling insurance protection scheme with a parametric mechanism. To determine the triggering parameter of the insurance pay-out, the authors consider various hazard scenarios developed based on historical events. This paper focuses on Probable Maximum Loss (PML) determination computed for events with epicenters in the Vrancea (a region and a mountain in the Carpathians) seismic area. This area is the most exposed in Romania to earthquakes, and it includes the capital, Bucharest, which is the urban area with the highest population concentration and, consequently, the highest exposure to the discussed risks. Full article

This paper aims to find the prospects of improving the practice of managing financial risks of sustainable development in the Decade of Action. We substantiate—based on economic and mathematical modeling based on a sample of 185 countries—that the existing (project-based) approach to managing financial risks of sustainable development, which was successfully implemented in the pre-crisis period (2015–2019), demonstrates reduced effectiveness at the beginning of the Decade of Action (2020–2021). This showed a marked increase in the overall level of financial risk, as well as an increase in the importance of private investment, in financing sustainable development in the first two years of the Decade of Action (2020–2021) compared to 2018–2019. Additionally, the features of the continents are identified: Africa, America and the Caribbean, Asia, and Europe, and specific recommendations are proposed for them on the financial risk management of sustainable development in the Decade of Action. This paper’s originality lies in the development of a new program-targeted approach to managing financial risks of sustainable development, which, due to its increased flexibility and the use of the market mechanism—is optimal for the conditions of the pandemic and will allow the ensuring of the full-scale (quantitative characteristics) financial provision of the SDGs in the Decade of Action using private investments. This paper’s novelty is also due to the recommendation on the improvement of financial risk management based on corporate social responsibility (qualitative characteristics) to support the implementation of the SDGs in the Decade of Action. Full article

This study examines the effect of the COVID-19 pandemic on the relationship between idiosyncratic volatility and expected stock returns. Using daily stock return data in the US market from the Center for Research in Security Prices (CRSP), we estimate monthly idiosyncratic volatility and investigate the effect of the COVID-19 pandemic at the portfolio and firm level. The results of portfolio analysis and cross-sectional regression show that the relationship between idiosyncratic volatility and subsequent stock returns switches from negative to positive during the pandemic period. Furthermore, we find that the relationship is robust to skewness for the “before the pandemic” and “after pandemic” periods. On the contrary, when we control for the one-month return reversal, the effect of idiosyncratic volatility on the subsequent stock returns becomes insignificant in both periods. Therefore, the short-term return reversal effect is the underlying reason for the relationship switching from negative to positive in the pandemic period. Our results are beneficial for investors and researchers. Full article

This research paper analyses the impact of COVID-19 to investigate the overconfidence bias in 12 cyclical and defensive sectors in pre- and during COVID-19 periods using daily data from 1 January 2015 to 31 December 2020. The results of VAR show that in the pre COVID-19 phase overconfidence bias is more prevalent in all the cyclical sectors; in particular, MEDIA, METAL and REALTY have highly significant coefficients . In the defensive sectors, the VAR outcomes are not as strong as we expected, except for SERVICES. During the COVID-19 period, the investor shifted their focus to COVID-19-related opportunities, leading to a surge in the IT and PHARMA sectors. In both phases, METAL, MEDIA and REALTY exhibit overconfidence-driven stock trading behaviour. ENERGY is the only sector in both the phases that does not witness overconfidence bias. Full article

Equalization reserves is an insurance liability with features of own capital. By law, Swiss reinsurance and non-life undertakings must hold equalization reserves within their statutory accounts. Regarding Swiss solvency modeling, the equalization reserves are set to zero. Swiss reinsurance and non-life undertakings define the upper limit and the corresponding transfer rule to the equalization reserves; however, this information is not disclosed. The goal of the study is to find a relationship between the equalization reserves and the publicly available technical account items, applying a generalized additive model (GAM). Thereafter, we transform the continuous variables into discrete ones, and we apply a generalized linear model (GLM). The study is based on published data from 1997 to 2018, whereby we restate the implicitly published equalization reserves. For reinsurance undertakings, the GAM model captures the relationship better than the GLM one; for non-life undertakings, the GLM model performs better. For reinsurance undertakings, the equalization reserves depend on the equalization reserves of the previous year, on the calendar year, on the legal form, on the technical result, on the administration and commission costs and on other costs. For non-life undertakings, the equalization reserves depend on the net claims payments, on the equalization reserves of the previous year, on the net change in claims reserves without change in equalization reserves, on the calendar year and on the net earned premium. Furthermore, we look at the need for equalization reserves: do the undertakings accumulate and release the equalization reserves? Further, the impact of taxes on the equalization reserves is looked at. The concept of equalization reserves avoids the misuse of tax optimization. We conclude that the discussion about disclosure of equalization reserves will restart. In addition, the definition of the upper limit of the equalization reserves could be widened by linking the equalization reserves to the insurance/reserving risk from the capital modeling. Full article

While both zero-inflation and the unobserved heterogeneity in risks are prevalent issues in modeling insurance claim counts, determination of Bayesian credibility premium of the claim counts with these features are often demanding due to high computational costs associated with a use of MCMC. This article explores a way to approximate credibility premium for claims frequency that follows a zero-inflated Poisson distribution via variational Bayes approach. Unlike many existing industry benchmarks, the proposed method enables insurance companies to capture both zero-inflation and unobserved heterogeneity of policyholders simultaneously with modest computation costs. A simulation study and an empirical analysis using the LGPIF dataset were conducted and it turned out that the proposed method outperforms many industry benchmarks in terms of prediction performances and computation time. Such results support the applicability of the proposed method in the posterior ratemaking practices. Full article

This paper aimed to assess the effect of the cryptocurrency market on firms’ market value, especially on the sectoral level, in Africa. To reach the study’s main goal, the authors adopted the Panel-Corrected Standard Errors (PCSEs) and Panel Double-Clustered Standard Errors (PDCSEs). Using firm-level data, the results of this study can be summarized as follows: (a) The cryptocurrency market hurts the firm market value in Africa. (b) The firms operating across different sectors respond disproportionally to the cryptocurrency market. For instance, the sectors that offer low returns in Africa (industrial, energy, financial) negatively respond to the cryptocurrency market, while the sectors that offer high returns (real estate and information technology) are not significantly affected. (c) The cryptocurrency market has a perverse effect on less experienced and highly indebted firms. (d) The consistent policies of governments to ban cryptocurrency do not work efficiently. Full article

The paper aims to determine the role of the financial situation of production companies in the relationship between their environmental initiatives and their factors of competitiveness. The paper takes advantage of primary and secondary statistical data. The former were gathered using the diagnostic survey method, whereas the latter were obtained from the companies’ financial statements. For the analysis of the primary data, structural modeling was applied. The data from the financial statements served to classify enterprises according to their financial situation. The classification was carried out with the use of Mączyńska’s discriminant model. The main findings highlight that more positive effects of environmental initiatives, such as companies’ increased competitiveness, were observed in cases of enterprises with good financial situations. In addition, a weaker impact of pro-environmental initiatives on the increase in companies’ competitiveness was noted in enterprises in poor financial conditions. The results of this research may be potentially applied in those production companies which build their competitiveness based on activities aiming at the protection of the natural environment. They draw attention to the key factors of the competitiveness of enterprises, which are improved as a result of actions for the protection of the natural environment. The originality of the presented research lies in determining the role of the financial situation in the development of the relationship between environmental actions and company competitiveness. Full article

In France, access to a loan requires one to obtain loan insurance and the presence of a pathology in the applicant may be a reason for refusal. Improving knowledge of health risks and pooling risks are two methods of broadening access to loans. We attempt to analyse these possibilities using open data and risk pooling scenarios. We find that the removal of medical selection can be ensured if the current framework is adjusted. We also demonstrate how to use open data to estimate loan insurance premiums for a variety of diseases. We take two examples: breast cancer and type 1 diabetes. Broadening access to borrowing would be beneficial for patients and for the development of the economy associated with these projects. Full article

This work presents a project called “ESium Project”, whose main objective is to create new spaces for social participation and a relationship between two different age groups: the young Social Education students and the elderly. It has a double purpose: to promote that reciprocal space for cooperation and interaction in a way that avoids the risk of disengagement and to promote a professional perspective. Target students will become future professionals who will also work with the elderly collective. Furthermore, a research-action method aims to make the participants protagonists of the educational actions that are carried out by using qualitative techniques as essential strategies for the work of collectives. Not only do the results regard the intergenerational stereotypes, they also show the assessment of the satisfaction by the involved participants, the international acknowledgement of the educational activity developed, and the possibility to use this in other contexts. In this way, it can be concluded that there is a need to tackle intergenerationally in teacher education from a wide-open inclusive perspective to take advantage of senior talent and innovation. Full article

Socio-ecologic, socio-economic, and socio-technical transitions are opportunities that require fundamental changes in the system. These will encounter matters associated with security, service adoption by end-users, infrastructure and availability. The purpose of this study is to examine and overcome the risks to take advantage of opportunities through the novel Risky-Opportunity Analysis Method (ROAM). A novel quantitative method is designed to determine when, after making some changes, the risks become acceptable so that the opportunity does not deviate from the objectives. The approach provided a quantitative evaluation of the possible changes in parallel with digitization, towards providing a green Service Supply Chain (SSC). The result of ROAM shows that the most cost-effective change to increase the resilience of the system is a solution (SMS) which is different from that identified by a TOPSIS multi-criteria method. Real-word decisions in change management should tackle the complexity of systems and uncertainty of events during and after transition through a careful analysis of the alternatives. A case-study was carried out to evaluate the alternatives of an ancillary service in the Payment Service Providers (PSP). The comparison of the ROAM results with the traditional TOPSIS of the case-study unveils the priority of the ROAM in practice when the alternatives are Risky-Opportunities. The existing risk assessment tools do not take advantage of risky opportunities. To this aim, the current article introduces the term Risky-Opportunity, and two indexes—Stress and Strain—of the alternatives that are designed to be employed in the new quantitative ROAM approach. Full article

We propose an accurate data-driven numerical scheme to solve stochastic differential equations (SDEs), by taking large time steps. The SDE discretization is built up by means of the polynomial chaos expansion method, on the basis of accurately determined stochastic collocation (SC) points. By employing an artificial neural network to learn these SC points, we can perform Monte Carlo simulations with large time steps. Basic error analysis indicates that this data-driven scheme results in accurate SDE solutions in the sense of strong convergence, provided the learning methodology is robust and accurate. With a method variant called the compression–decompression collocation and interpolation technique, we can drastically reduce the number of neural network functions that have to be learned, so that computational speed is enhanced. As a proof of concept, 1D numerical experiments confirm a high-quality strong convergence error when using large time steps, and the novel scheme outperforms some classical numerical SDE discretizations. Some applications, here in financial option valuation, are also presented. Full article

The paper aims to investigate the effects of financial distress risk (FDR) and related party transactions (RPT) on financial reporting quality (FRQ) in an emerging market called Iran. In this study, the ordinary least squares regression (OLS) method is employed to test the hypotheses; moreover, Jones’ discretionary accruals model is used to assess the financial reporting quality (FRQ). The results show financially distressed companies have a lower financial reporting quality because they try to mislead other stakeholders about the corporate actual performance to attract more investors and lenders. Consistent with the “tunneling” or “conflict of interests transaction” assumption, our findings confirm there is a positive association between related party transactions through loan and accrual-based profit management. In other words, Iranian managers participate in loan-related party transactions to expropriate their firm’s resources and then manipulate financial statements to mask such expropriation. Finally, additional analysis indicates that financial reporting quality is seen well among firms having higher sale growth and more institutional owners, whereas the variables of ROA and financial leverage negatively affect financial information quality. Full article

The paper is an investigation on the impact of financial markets on the volatility of the green bonds credit risk component, measured by the option-adjusted spread/swap curve (OAS) before and during the pandemic period. To this purpose, after observing the dynamic joint correlations between all the variables, we adopt Exponential and Generalized AutoRegressive Conditional Heteroskedasticity models, putting the OAS as dependent variable. Our main results show that the conditional variance parameters are significant and persistent in both times, testifying the overall impact of the other markets on the OAS. In more detail, we highlight that the gamma in the two Exponential models is positive: so, the “green” credit risk volatility is more sensitive to positive shocks than to negative ones. With reference to the conditional mean, we note that if during the non-pandemic period only the stock market is significant, during the pandemic also conventional bonds and gold are impacting. To the best of our knowledge this is the first study that analyzes the specific credit risk component of the green bond yields: we deem our findings useful to observe the change of green bonds creditworthiness in a complex market context and interesting in terms of policy implications. Full article