Risks, Volume 10, Issue 2 (February 2022) – 22 articles

This paper’s goal is to develop a scientific methodology of financial risk management of ecologically responsible entrepreneurship for the sustainable development of the green economy. The originality of this paper is due to the fact that, for the first time, the financial risks of the green economy are considered through the prism of its sustainability. The paper’s novelty is due to the modelling and quantitative measuring of the impact of the COVID-19 pandemic and the financial and economic crisis on the financial risks to the green economy’s sustainability, in addition to the development of precise quantitative recommendations for financial risk management of the green economy. This enables an increase in its sustainability and reduces ecological disproportion in regions of the world (reducing the differences in the green economy’s sustainability among regions of the world through the management of green investments). The paper’s contribution to the literature consists of specifying the theory of financial risks to the green economy. According to the specified fundamental provisions of this theory, the essence of the process of green economy development is clarified (the “black box” is opened) as the increase in its contribution to sustainable development. As the indicator of achieving this development, an increase in the green economy’s sustainability is offered. A new source of achieving the goal is proposed, consisting of a financial risk management of ecologically responsible entrepreneurship based on (private) green investments. Full article

In this study, we investigated the impact of COVID-19 investor sentiment (CS), number of cases (CC), and deaths (CD) on bank stock returns in 16 MENA countries. In addition, we examined the interaction effects of CS with CC and CD on bank stock returns. Lastly, we looked at whether Islamic banks outperformed conventional banks during the pandemic. Based on monthly data from the Middle East and North Africa (MENA) countries from February 2020 to July 2021, we used the clustered standard error fixed effect estimation on Islamic and conventional bank stock market returns. The results suggest that CC and CD have negative impacts on bank stock market returns while CS has no effect, except for the lagged value. The interaction effect of CS with CC and CD on stock returns proved to strengthen the link in the current month and weaken the link in the previous month. Full article

This paper demonstrates that the level of financial risks and the impact of the COVID-19 pandemic and crisis on them are high. The existing approach to financial risk management is not very effective and does not allow coping with financial risks in entrepreneurship, not even in a certain category of countries. As a prospective alternative, we offer a new socially-oriented approach. The theoretical value of the paper lies in the offering and scientific substantiation of a new hypothesis: that the SDGs could and should be constantly supported by business in their financial risk management with the help of the socially-oriented approach, which is available and expedient for use under the conditions of economic crisis. The practical value of the received results is as follows: the developed new (alternative) socially-oriented approach to financial risk management in entrepreneurship allows increasing the effectiveness of financial risk management in entrepreneurship and raising its robustness against the current COVID-19 crisis. The social importance of the obtained conclusions and results is that the developed approach allows for and stimulates continuous support for the SDGs in entrepreneurship. Full article

In the past 30 years, as sponsors of defined benefit (DB) pension plans were facing more severe underfunding challenges, pension de-risking strategies have become prevalent for firms with DB plans to reduce pension-related risks. However, it remains unclear how pension de-risking activities affect firms’ performance, partially due to the lack of de-risking data. In this study, we develop a multi-phase methodology to build a de-risking database for the purpose of investigating impacts of firms’ pension risk transfer activities. We extract company filings between 1993 and 2018 from the SEC EDGAR database to identify different “de-risking” strategies that US-based companies have used. A combination of text mining, machine learning, and natural language processing methods is applied to the textual data for automated identification and classification of de-risking strategies. The contribution of this study is three-fold: (1) the design of a multi-phase methodology that identifies and extracts hidden information from a large amount of textual data; (2) the development of a comprehensive database for pension de-risking activities of US-based companies; and (3) valuable insights to companies with DB plans, pensioners, and practitioners in pension de-risking markets through empirical analysis. Full article

Life insurance profitability depends on reliable mortality risk projections and pricing. While the COVID-19 pandemic has caused disruptions around the world, this is a temporary mortality shock likely to dissipate. In this paper, we investigate the long-run impact of COVID-19 on life insurance profitability. Due to the long-run dynamics of the mortality characterised by a decreasing effect of the COVID-19 mortality acceleration, we suggest proactive mortality risk management by implementing prompt premium adjustments, in order to increase the resilience of the business. Full article

Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirement years, mostly betting on stocks or indexes with low risk/low volatility. However, every stock-based investment portfolio has an inherent risk to lose money through negative progression and crash. This study presents a novel technique to predict such rare negative events in financial time series (e.g., a drop in the S&P 500 by a certain percent in a designated period of time). We use a time series of approximately seven years (2517 values) of the S&P 500 index stocks with publicly available features: the high, low and close price (HLC). We utilize a Siamese type neural network for pattern recognition in images followed by a bootstrapped image similarity distribution to predict rare events as they pertain to financial market analysis. Extending on literature about rare event classification and stochastic modeling in financial analytics, the proposed method uses a sliding window to store the input features as tabular data (HLC price), creates an image of the time series window, and then uses the feature vector of a pre-trained convolutional neural network (CNN) to leverage pre-event images and predict rare events. This research does not just indicate that our proposed method is capable of distinguishing event images from non-event images, but more importantly, the method is effective even when only limited and strongly imbalanced data is available. Full article

The automation of manufacturing processes as a result of the Fourth Industrial Revolution, rendered faster under the influence of the COVID-19 pandemic, leads to a question as to whether small enterprises, and in particular microenterprises, will still be financially self-sufficient. The literature on the subject so far has not provided an answer to this question, and limited access to financial data concerning microenterprises, as well as data on the robotification of labour in these companies, leads to this problem becoming a research niche. Therefore, this paper aims to assess the attractiveness of the operation of microenterprises that provide financial advisory services in the situation of replacing human labour with robots. For that purpose, we performed a simulation of the state of the microenterprise before and after introducing the robotification of services, taking into account the extra tax on robotification. The findings indicate that anticipating the improvement of financial results following the automation of financial services requires taking into account the replaceability of employees in a particular unit, the form of acquiring a robot and a potential increase in the tax burden (with a tax compensating for the lost state income). Full article

We compare parametric and machine learning techniques (namely: Neural Networks) for in–sample modeling of the yield curve of the BRICS countries (Brazil, Russia, India, China, South Africa). To such aim, we applied the Dynamic De Rezende–Ferreira five–factor model with time–varying decay parameters and a Feed–Forward Neural Network to the bond market data of the BRICS countries. To enhance the flexibility of the parametric model, we also introduce a new procedure to estimate the time varying parameters that significantly improve its performance. Our contribution spans towards two directions. First, we offer a comprehensive investigation of the bond market in the BRICS countries examined both by time and maturity; working on five countries at once we also ensure that our results are not specific to a particular data–set; second we make recommendations concerning modelling and estimation choices of the yield curve. In this respect, although comparing highly flexible estimation methods, we highlight superior in–sample capabilities of the neural network in all the examined markets and then suggest that machine learning techniques can be a valid alternative to more traditional methods also in presence of marked turbulence. Full article

This paper aims to study the perspectives of sustainable development amid the COVID-19 pandemic and crisis in 2021, backed by financial risk management and corporate social responsibility. To achieve this goal, the authors use the methods of regression analysis, horizontal and trend analysis, and variation analysis. As a result, it is proven—for the first time—that in isolation, investments and corporate social responsibility do not contribute positively to sustainable development. In addition, the authors determine the absence of the outflow of investments from the world economy during crises. Based on this, a new approach to crisis management of sustainable development is developed—it is based on stimulating corporate social responsibility, for which the complex recommendations in the sphere of state management are offered. The theoretical significance of the conclusions made consists in specifying the essence of financial risk management of sustainable development, which has to be conducted with a strict connection to and based on corporate social responsibility. The practical significance of the developed new approach and offered recommendations on its practical implementation consists of strengthening the scientific and methodological provision of economic crisis management of COVID-19 and the maximization of its contribution to sustainable development to support the Decade of Action. Full article

Purpose: Bring to light the risks of smart cities and the perspectives of their management. It has been discovered that smart cities are created and developed under the impact of not only technological factors but also social factors. The connection between smart cities and quality of life is systemic (direct and reverse)—the quality of life also specifies the creation and development of smart cities. The impact of the COVID-19 pandemic on the development of smart cities is almost null (smart cities do not depend on the implementation of SDG 3). This paper’s originality lies in the description of a new angle of studying smart cities—from the position of risks, and in the determination of the current level of these risks and the dynamics of their change during systematisation and description of the wide international experience of creation and development of smart cities. This paper’s uniqueness lies in the development of a new approach to managing the creation and development of smart cities, which is based on corporate social responsibility, thus specifying and ensuring the involvement and important role of the subjects of entrepreneurship in this process. It is proved that the contribution of smart cities to the implementation of the SDGs is much wider and goes beyond the limits of SDG 9—it also extends to SDG 1 and SDGs 11–13. Full article

Every financial crisis triggers some regulatory and supervisory changes related to the ensuing threats. These regulations usually address specific types of risks and reduce them but do not protect the entire system from another crisis. The aim of this study was to develop a conceptual framework of financial system resilience based on the theoretical approach of complex system theory and its explanation of these systems’ self-adaptation. Our analysis embraces the time since the 2008+ financial crisis in the United States. We argue that the digitalization of financial markets may contribute to the greater safety of the banking sector. We adopted blockchain technology for the pattern of self-modification mechanisms of the financial system. The main findings highlight that the blockchain technology incorporated into the system approach and applied to financial regulation and supervision can significantly improve the safety of the financial markets. Full article

China has accelerated its banking sector reform in recent years, paying particular attention to non-performing loans (NPLs). The paper’s scope is to analyse the relationship between NPLs and macroeconomic variables in China using quarterly data from 2008/Q1 to 2021/Q1 applying wavelet analysis, which allows the study to scan both short- and long-term causal relationships and connections. The analysis produces interesting results. The GDP does not appear to be as important and as much of a driving force in the dynamics of NPLs as in other emerging countries. On the other hand, inflation shows a highly dynamic dependence on NPLs as it varies over time; however, the most interesting data is the relationship between NPLs and economic policy uncertainty. In the short term, the variables are in phase. In the long term, an increase of EPU has a reduction effect on NPLs, indicating that it affects commercial bank loan sizes by reducing enterprise demand for and bank supply of credit resources. Full article

This article introduces a new approach for dealing with the diversification/concentration risk of fixed income assets. Because Government bonds, corporate bonds, and mortgage backed securities constitute a large proportion of the assets of institutional investors in most countries, it is important to be able to determine the number of lines/issuers of such assets, not only for portfolio management but also for risk management purposes. The approach that I introduce shows the dependence of the critical number of lines of fixed income assets on the main interest rate risk and credit risk drivers. Specifically, I examine the importance of volatility risk, force of mean reversion, default risk, recovery risk, and default dependence risk on the critical number of assets in a fixed income portfolio. The methodology in this paper relies on the use of the coefficient of variation for the computation of the critical number of credit-sensitive securities in a fixed income portfolio. To the best of my knowledge, this paper is the first to develop such an approach. Full article

This research examines the relationship between the risk management committee and textual risk disclosure. Textual risk disclosure is measured using the use of a risk-contained tone in the annual report. We employed empirical analysis for the Indonesian listed firms for the period 2010 to 2018. The findings of this research suggest that the existence of the risk management committee gives more risk disclosure. This finding implicates that firms with a risk management committee will give more risk disclosure, because they have a specific committee which have abilities concerning firm risk. The first additional analysis suggests that the results are more pronounced for firms within the period after the regulation to have a risk management committee was applied in Indonesia. We also make second additional analysis for different level of technology within industry. The existence of risk management committee for managing risk disclosure is more pronounced for company within high level of technology industry. We provide several contributions to the users of the financial statements such as shareholders and other stakeholders, especially regulatory bodies in Indonesia. Full article

This paper examines the poverty perceptions of retired women by assessing the extent to which demographic characteristics, economic considerations, household adequacy levels and satisfaction measures influence perceptions of poverty. Based on data from a South African national survey, binomial logistic regression models were employed, whereby demographic characteristics (first level variables) were assessed relative to the respondents’ poverty perceptions. Thereafter, economic considerations (second level variables) were included in the model to draw more inferences on the conditions leading to poverty perceptions. Finally, respondents’ household adequacy levels and satisfaction measures (third level variables) were nested into the model for a complete investigation of the antecedents of poverty perceptions. Many of the retired women in this study perceive themselves to be impoverished or at risk of poverty. The results indicate that marital status and education levels have a significant influence on perceptions of poverty. Furthermore, the study found that monetary measures do not sufficiently explain the pathway leading to retirement poverty perceptions. Instead, perceptions of financial security and the satisfaction with one’s standard of living influence gendered poverty perceptions. This study advances our understanding of the conditions influencing the poverty perceptions of retired women. As most of the respondents in this sample rely on the government for financial support, this study provides pertinent suggestions to government agencies on the conditions associated with gendered poverty perceptions at retirement. Full article

Astonishingly little attention has been paid in academic literature to the 2008–2009 foreign exchange (FX) options debacle in Poland, the scale of which was unheard of. It affected not only an individual organization but a significant part of economy, being an example of a situation in which operational risk at the company level could have impacted systemic risk. The research provides evidence of the dark side of financial innovations through an analysis of a countrywide case on an emerging market, utilizing a primary qualitative content analysis (QCA) of over 750 documents (including press releases, public authorities’ accounts, and corporate statements). It documents that the FX options debacle was caused by financial institutions which shrouded some aspects of innovative securities or took advantage of information asymmetry to exploit uninformed clients. The study concludes that both adequate legal regulations and proper operational risk management are crucial to avoid similar corporate failures. Full article

The research problem is that the COVID-19 pandemic has become a threat to the sustainable development of the EEU and caused uncertainty in terms of the management of corporate social responsibility. This paper is aimed at identifying the impact of the COVID-19 pandemic on sustainable development of the EEU from the perspective of the interaction of the member states of the integration association and their mutual trade risks through the prism of the management of corporate social responsibility. The methodological foundation of the research is composed of the provisions of a comprehensive approach that has been used as a basis for determining the cause-and-effect relationship between the member states of the integration association and their mutual trade risks in the age of the COVID-19 pandemic in 2020. The analysis of statistical data is based on the methodology of econometric theory; in particular, the methods of horizontal and trend analysis. This paper analyzes the measures that were taken by the EEU member states to fight the pandemic of a new coronavirus infection both at the national level and at the level of the EEU institutions. The authors showed the asynchronous nature of measures introduced at the national level, while in certain circumstances the economic inefficiency of the introduction of measures, taken at the supranational level, and the impact of imposed restrictions on the current situation with mutual trade in goods and services, and free movement of workers. It has been substantiated that the examination of the economic interaction of the EEU member states in the period of restrictions dictated by a new coronavirus infection has revealed several endemic problems and had a major impact on the achievement of the main objectives of the integration association, transforming the terms for the management of corporate social responsibility. The originality of the paper is that the unique experience of the integration association of the EEU is for the first time studied from the perspective of the impact of the risks of mutual trade during a pandemic on it through the prism of the management of corporate social responsibility. Full article

We aim to assess the impact of a pandemic data point on the calibration of a stochastic multi-population mortality projection model and its resulting projections for future mortality rates. Throughout the paper, we put focus on the Li and Lee mortality model, which has become a standard for projecting mortality in Belgium and the Netherlands. We calibrate this mortality model on annual death counts and exposures at the level of individual ages. This type of mortality data are typically collected, produced and reported with a significant delay of—for some countries—several years on a platform such as the Human Mortality Database. To enable a timely evaluation of the impact of a pandemic data point, we have to rely on other data sources (e.g., the Short-Term Mortality Fluctuations Data series) that swiftly publish weekly mortality data collected in age buckets. To be compliant with the design and calibration strategy of the Li and Lee model, we transform the weekly mortality data collected in age buckets to yearly, age-specific observations. Therefore, our paper constructs a protocol to ungroup the death counts and exposures registered in age buckets to individual ages. To evaluate the impact of a pandemic shock, like COVID-19 in the year 2020, we weigh this data point in either the calibration or projection step. Obviously, the more weight we place on this data point, the more impact we observe on future estimated mortality rates and life expectancies. Our paper allows for quantifying this impact and provides actuaries and actuarial associations with a framework to generate scenarios of future mortality under various assessments of the pandemic data point. Full article

The aim of this study was to examine the impact of adopting information and communication technologies (ICT) on the development of African stock exchanges. The study examined a panel of 11 African stock exchanges for the period 2008–2017 and employed the generalised method of moments (GMM) to estimate the results. The results of the study documented that ICT adoption had a positive impact on stock market development in African countries. Firstly, it was found that the stock market traded volume and mobile–telephone user variables were positively related. Secondly, a positive relationship was also proven between the stock market traded volume and the broadband user variable. Thirdly, a positive relationship was documented between the stock market capitalisation variable and the fixed telephone user variable. Fourthly, the research findings confirmed a positive relationship between the stock market turnover ratio and the fixed telephone user variable. The findings of this study imply that policymakers should be more resolute when formulating ICT policies. ICT adoption can spur stock market development which in turn can propel economic growth, resulting in the economic prosperity of the African countries. Moreover, ICT adoption could enhance the integration of African stock exchanges, further buttressing the drive towards the common market areas in various regions. Full article

This paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances is uncertain. The change of the macroeconomic and microeconomic situation of households requires searching for better and more precise methods. The research relies on four samples of households: two learning samples (imbalanced and balanced) and two testing samples (imbalanced and balanced) from the Survey of Consumer Finances (SCF) which was conducted in the United States. The results show that the predictive performance of the logit model based on a balanced sample is more effective compared to the one based on an imbalanced sample. Furthermore, mortgage debt to assets ratio, age, being married, having credit constraints, payday loans or payments more than 60 days past due in the last year appear to be predictors of consumer bankruptcy which increase the risk of becoming bankrupt. Moreover, both the ratio of credit card debt to overall debt and owning a house decrease the risk of going bankrupt. Full article

Central banks have been pursuing an expansionary monetary policy since before the pandemic, although the health and economic crisis of COVID-19 has boosted asset purchase programmes. After the Great Recession, a new phase began, characterised by low interest rates and liquidity injections. These policies spilled over into financial markets and are leading to higher inflation. These policies stabilised the situation in the short term, but if they continue indefinitely there is a risk of debt overhang, investment mistakes and high inflation in the future. The aim of this article is to analyse monetary policy developments from the Great Recession to the COVID-19 crisis. Correlations between different macroeconomic variables will be shown through IBM SPSS Statistics. For this purpose, bi-variate correlations were used. For the predictions and confidence of the model data, Tableau Desktop Edition was used, which in turn was used for the generation of the graphs. There is a strong correlation between the growth of monetary aggregates and public debt and stock market capitalisation for the selected indicators. The main contribution of this research is the analysis of the long-term effects of a monetary policy. Full article