Journal of Risk and Financial Management

The financial stability of the commercial banking sector remains one of the critical responsibilities of the Reserve Bank of India (RBI). Weak banks cause instability in the financial system, triggering depositor runs. While several studies covered the prompt corrective action framework (PCA) for identifying weak banks, very few delve into the simplification of the same. This paper debates the opportunities to simplify using new parameters that reflect signs of weakness in a commercial bank. The PCA framework introduced in December 2002 marked a paradigm shift in the RBI’s supervision mechanism. At its inception, the RBI used three parameters (capital to risk-weighted assets, net non-performing assets, and return on assets) to identify weak banks. In 2017, the RBI added two more parameters (tier-1 leverage, common tier-1 equity) to build rigour in the framework. Banks that breach the threshold in any of these financial parameters could come under the RBI’s lenses. Under such a situation, the bank has to operate under constraints imposed on expansion, managerial compensation, raising deposits, and dividends distribution. This article explores new ratios and establishes their application in PCA using “linear discriminant analysis”. We debate reducing the number of parameters from five to two, and conclude that only coverage ratio (new) and credit-to-deposit ratio (new) could simplify PCA without diluting its effectiveness. Full article

The aim of this study was to ascertain what can be done by the informal finance sector to close the credit gap in order to improve access to finance by SMEs. SMEs are the backbone of many economies as a result of generating employment and improving GDP. Despite playing such a major role in African economies, SMEs have been excluded from the financial systems. The informal finance sector plays a vital role by providing finance to small businesses. The study employed a literature survey with a primary focus on empirical studies that have been conducted in the African context. The study found that, generally, there are two circumstances under which most small businesses depend on informal finance. Firstly, informal finance is used as a last resort by SMEs that fail to access credit from the formal finance sector, owing to, among other issues, information asymmetry, lack of collateral security and perceived high default rates. Further, low financial literacy and the absence of credit bureaus in developing countries also contribute to the failure to access finance from formal institutions. Secondly, some entrepreneurs opt for informal finance even if they are eligible for formal finance as a result of its flexibility, convenience and simple administrative procedures. Notwithstanding the above benefits of informal finance, informal lenders are regarded as exploiting the clients by charging high interest rates. In addition, this sector suffers from limited resources; hence, it fails to fully service SMEs that require larger funding and are not eligible for formal finance. Invariably, all the studies that have been carried out confirm that access to finance is a major obstacle to the growth and development of SMEs. The development and empowerment of SMEs cannot be ignored as an important driver of the developmental agenda of most economies globally. The main policy recommendations that flow from this study, based on the policy syndrome of improving access to finance (financial inclusion) by the SME sector, include (1) the establishment of a suitable regulatory framework which will nurture the informal finance sector while promoting consumer protection, and (2) linking the formal and informal sector. On the other hand, SMEs should improve their risk management practices and also embrace FinTech platforms in order to access credit. Full article

The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in every field. For the automatic targeting of customers in a banking telemarketing campaign, the use of ML-based approaches in previous work has not been able to show transparency in the processing of heterogeneous data, achieve optimal performance or use minimal resources. In this paper, we introduce a class membership-based (CMB) classifier which is a transparent approach well adapted to heterogeneous data that exploits nominal variables in the decision function. These dummy variables are often either suppressed or coded in an arbitrary way in most works without really evaluating their impact on the final performance of the models. In many cases, their coding either favours or disfavours the learning model performance without necessarily reflecting reality, which leads to over-fitting or decreased performance. In this work, we applied the CMB approach to data from a bank telemarketing campaign to build an optimal model for predicting potential customers before launching a campaign. The results obtained suggest that the CMB approach can predict the success of future prospecting more accurately than previous work. Furthermore, in addition to its better performance in terms of accuracy (97.3%), the model also gives a very close score for the AUC (95.9%), showing its stability, which would be very unfavourable to over-fitting. Full article

This study investigates the interactive effect of ownership structure on the relationship between annual board report readability and stock price crash risk in companies listed on the Tehran Stock Exchange (TSE). The negative skewness model was used to measure the crash risk of stock prices and the Fog index was used for determining the readability of the board of directors’ report. The ownership structure is examined in institutional ownership, significant managerial ownership, and family ownership. The data of companies listed on the TSE from 2013 to 2019 have been used. The statistical method of this research is multiple regressions and, to test the research hypotheses, the data panel model and the ordinary least squares method have been employed. Overall, this study provides new evidence to explain the reporting quality and the crash risk of stock prices from the lenses of the agency theory. It further investigates the interactive effect of ownership structure on the relationship between annual board report readability and stock price crash risk. The results show a significant correlation between the readability of the board of directors’ report and the crash risk of stock prices. Furthermore, the relationship between the readability of the board report and stock price crash risk is not affected by the ownership structure, including institutional ownership, significant managerial ownership, and family ownership. It can be inferred that an ownership structure, which includes institutional shareholders, significant shareholders, and family ownership, increases the supervision of managers and their reports, so they cannot keep adverse information from being released. This will ultimately improve the readability of their reports and reduce the risk of stock price crashes. Full article

Using the same data set, a researcher can obtain very different reduced form estimates just by assuming different macroeconomic models. Reiterative Truncated Projected Least Squares (RTPLS) or Variable Slope Generalized Least Squares (VSGLS) can be used to estimate total derivatives that are not model dependent. These estimates can be used to pick between competing macro models, improve current models, or create new models. A selected survey of RTPLS estimates in the literature reveals several common patterns: (1) as income inequality has surged around the world, the effect of changes in government spending (G), exports (X), and money supply (M-1) on Gross Domestic Product (GDP) have plummeted, (2) decreases in G, X, and M-1 cause GDP to fall more than equal increases in G, X, and M-1 cause GDP to rise, and (3) unusually large increases in G and M-1 cause their effect on GDP to plummet. These common patterns fit with a global glut of savings hypothesis, which predicts that an increase in savings will not cause an increase in production expanding investment. An appropriate model could be built around the idea that investors have a choice between investing to increase production or investing to earn rent or interest. Full article

The effectiveness of government policies and economic stimuli during the 2007 financial crisis and the COVID-19 pandemic are compared in this study. While the 2007 financial crisis started in the real estate market and spread through the contagion effect to other sectors, the pandemic halted the all sectors of the global economy simultaneously. In the United States, where the social safety net is not as strong as other advanced economies, the unemployment rate skyrocketed and many families lost income. The federal government countered with various relief packages, which have been, unlike the rounds of quantitative easing prevalent after the 2007 financial crisis, direct payments to households and businesses. The Agent Instability Indicator and default elasticity coefficient are used to quantitatively assess the financial instability and default risk of subgroups of United States households classified by percentile of income and net worth. It turns out that the financial instability level of the United States household during the pandemic has not been as high as that during the 2007 crisis and the Great Recession. It is concluded that the direct handout of cash—so called helicopter money—is more effective at preventing financial collapse and stabilizing the economy than quantitative easing through asset purchase. Full article

Banking risk management is considered weak compared to rapid changes in financial markets. In light of the recent global financial crisis, banking risk management has become a significant concern of banking regulators and government agencies. This work aims to build a model for assessing banking risks. The primary study method is economic–mathematical modeling based on the standardized model of the Basel Committee for Operational Risk Management, the modified CAPM model, and the model developed by Shapiro and Cornell for currency risk management. The information base was the financial statements of Bank Credit Agricole (Poland). As a result, an economic–mathematical model is built, which is the optimal combination of operational, currency, and credit risk management models. This model calculates the optimal values of bank balance sheet items, which allows for making the right management decisions. It allowed adjusting the value of the bank profit by 3.6 million US dollars. In conclusion, considering the results of banking risk modeling, the need to build a strategy for the bank’s development is determined. Full article

The aim of this article is to reveal the connection and significance of the concepts of dark tourism and sustainable tourism for the sustainable development of tourism, especially for regional tourism growth. The article discusses the theoretical aspects of dark tourism and details the aspects of this tourism industry as part of cultural tourism. The article also analyses principles and models of sustainable tourism development, with a stronger focus on the integrated development paradigm. As a relatively significant part of the research and analysis of sustainable tourism is more focused on the challenges posed by global mass tourism, this article focuses on the issues of sustainable development of niche tourism in relation to regional tourism. The article presents the analysis of Lithuanian dark tourism resources, presents the most common dark (dissonant) heritage objects, as well as the evaluation of resources according to the spectrum of dark tourism and the comparative analysis of the country’s most popular dark tourism objects from the point of view of sustainable tourism. A qualitative study revealed that regional tourism in Lithuania (especially niche, such as dark tourism) lacks integrity among different stakeholders, especially in involving the local community in the processes of cultural heritage protection and cultural tourism development and in developing more intensive links with the private sector. On the other hand, the analysis also revealed that there is an ambiguous public opinion regarding the dark heritage, which does not contribute to the sustainable development of tourism and the actualization of such heritage. The article also discusses the models of sustainable development of dark tourism and invites to discuss how to encourage greater public involvement in the development of dark tourism as part of cultural tourism, so that the principle of sustainable tourism does not remain an empty declaration. Full article

Disasters are often followed by a large-scale stimulus supporting the economy through the built environment, which can last years. During this time, official economic indicators tend to suggest the economy is doing well, but as activity winds down, the sentiment can quickly change. In response to the damaging 2011 earthquakes in Canterbury, New Zealand, the regional economy outpaced national economic growth rates for several years during the rebuild. The repair work on the built environment created years of elevated building activity. However, after the peak of the rebuilding activity, as economic and employment growth retracts below national growth, we are left with the question of how the underlying economy performs during large scale stimulus activity in the built environment. This paper assesses the performance of the underlying economy by quantifying the usual, demand-driven level of building activity at this time. Applying an Input–Output approach and excluding the economic benefit gained from the investment stimulus reveals the performance of the underlying economy. The results reveal a strong growing underlying economy, and while convergence was expected as the stimulus slowed down, the results found that growth had already crossed over for some time. The results reveal that the investment stimulus provides an initial 1.5% to 2% growth buffer from the underlying economy before the growth rates cross over. This supports short-term economic recovery and enables the underlying economy to transition away from a significant rebuild stimulus. Once the growth crosses over, five years after the disaster, economic growth in the underlying economy remains buoyant even if official regional economic data suggest otherwise. Full article

This study investigates the impact of COVID-19 exposure on corporate cash holdings using firm data across sixteen developing and developed economies. The results show that firms reserve more cash when their exposure to COVID-19 increases. We also find a cash burn effect during the COVID-19 pandemic, meaning that the cash holdings are drained when firm exposure to the pandemic exceeds a tipping point. The effect is more pronounced in larger firms and firms with less cash reserve. Further analyses reveal that the cash burn effect tends to be stronger in countries with a high level of individualism and weaker in countries with high levels of risk aversion, masculinity, and long-term orientation. The findings provide fresh insights into the connections among corporate cash holdings, national cultures, and firm-level exposure to COVID-19. Full article

In an international setting of developing countries, applying advanced statistical estimation approaches such as the system generalized method of moments (GMM), two-stage least square (2SLS) regressions, and cluster analysis, this paper revisits the impact of macro-level governance quality and the corruption index on the economic growth rate. We use cross-country panel data for 40 sub-Saharan and the Middle Eastern and North African (MENA) countries over the period of 2009–2020. The empirical results document the positive and negative effects of the national governance index and the corruption index on the economic growth rate. Additionally, foreign direct investment and population have a positive impact on the economic growth rate and trade openness has a negative impact. The study evaluates the robustness of these associations through a series of tests. These findings have important policy implications for policymakers and regulators in developing countries. In particular, the study recommends the implementation of an anti-corruption campaign and improving country-level governance quality that could encourage increased foreign direct investment for an accelerated economic growth rate. These will further enhance accountability, transparency, the rule of law, social responsibility, the public voice, and government effectiveness. Full article

Tweets seem to impact diverse assets, especially during stressful periods. However, their interrelations during stressful events may change. Cryptos are apparently more sensitive to the sentiment spread by tweets. Therefore, a construct could be formed to study such complex interrelation during stressful events. This study found an interesting outcome while investigating three major asset classes (namely, Equity, Gold and Bond) alongside negative sentiment (derived from tweets of Elon Musk) and Dogecoin (an emerging asset class) from 1 June 2015 to 20 February 2022. Negative sentiment emerged as the significant risk transmitter, while Gold emerged as the significant net recipient of shocks (risk). Interestingly, Dogecoin was found to be less impacted and not impactful (not transmitting shock and receiving tiny shocks) at the same time. In fact, the interconnectedness between negative sentiment (percolated through Twitter) and Dogecoin prices was found to be rather feeble. Further, the study showed that the COVID-19 breakout and Brexit referendum in 2016 were less stressful events compared to the Greek debt crisis back in 2015. Full article

Privatization has played an important role in national economic reform in Vietnam. However, unlike other transitional countries in Central and Eastern Europe, Vietnam has chosen a partial and gradual privatization where the government still holds significant ownership in most privatized firms. Whether partial privatization can enhance privatized firms’ performance or full privatization should have been implemented is a critical question that needs to be answered. This paper utilizes semiparametric regressions to study the relationship between residual state ownership and firm performance. The results indicate an inverted U relationship between state ownership and firm performance. We show that the performance of privatized firms improves with an increase in the level of state ownership until around 40%, after which the effect of state ownership on firm performance tends to decline. This demonstrates that in a transitional context, relinquishing governmental control via privatization can significantly benefit privatized firm performance. However, further reduction of state ownership may decrease the performance of privatized firms. Overall, the study contributes significantly to the growing body of evidence on the nonlinear effects of state ownership. This suggests that in the transitional context of Vietnam, due to weak corporate governance and limited protection of minority shareholders, there could be a temporary optimal position where state and private investors hold balanced ownership to simultaneously supervise operations and promote the performance of privatized firms. Full article

This paper aims to evaluate Pension Benefit Guaranty Corporation (PBGC) insurance values through regime-switching models. We separate periods of the economy with faster growth from those with slower growth to observe long-term trends in the economy. We derive a fair PBGC insurance pricing formula under distress termination and intervention termination using regime-switching processes. We set parameters by estimating the S&P 500 index and one-year treasury bills via expectation maximization particle swarm optimization (EM-PSO)-Gradient, which is an extension of the EM-Gradient method. Then, we conduct sensitivity analysis to investigate the impact of model parameters on insurance values. According to the maximum likelihood estimation results, the Akaike information criterion (AIC) and Bayesian information criterion (BIC) estimators show that the regime-switching process has better goodness of fit than the geometric Brownian motion. Scenario analysis also supports the adequacy of our pricing formula. Full article

The focus of this paper is placed on the role of emotions in consumer behavior, specifically in the process of purchasing dietary supplements during the COVID-19 pandemic. The theoretical part is based on current knowledge from relevant Croatian and foreign scientific and professional literature on dietary supplements, the COVID-19 pandemic, consumer behavior, decision-making and the impact of emotions on it, while the empirical research portion of this paper details the attitudes of consumers who buy food supplements, the role and importance of different emotions that have a greater or a lesser impact on the purchase of food supplements, with special reference to the timing of the COVID-19 pandemic, and the factors that make consumers decide to purchase food supplements. This research was conducted in the form of a survey that included 257 respondents who were actual users of dietary supplements. It showed that the main drive for buying dietary supplements during the COVID-19 pandemic is the emotion of fear, as the consumers perceived this new disease as a threat to their health and life. Full article

The Taiwanese government altered its corporate social responsibility (CSR) report management policy from voluntary disclosure and assurance of CSR reports to partial mandatory disclosure and partial mandatory assurance. This paper examines this policy’s effects on analyst forecast. The empirical results showed that the mandatory disclosure policy on CSR reports significantly increased analyst forecast accuracy and reduced analyst forecast dispersion. Furthermore, the study found that analyst forecast accuracy was further increased when CSR reports were forced to undergo accountant assurance than those without mandatory accountant assurance which means that the mandatory assurance policy on CSR reports significantly further increased analyst forecast accuracy. Full article

The importance of constant consumer testing is emphasized in order for companies to deliver the highest value for the quality of products and services. To explain the psychological impact of price on product selection, and other factors that determine consumer behavior, a survey method was applied. When deciding to buy a product, the consumer’s perception of the value of selected re-search products (clothing, footwear, children’s equipment) is crucial and it can often differ from the value derived from the price set by the seller. The conducted research proved that sellers can really influence consumers’ decision to buy a product with their price, and that a large number of consumers perceive the price incorrectly and thus buy more than they planned. Having in mind the subject of this paper, the basic scientific goal was to define a consumer model that integrates factors (variables) influencing consumer behavior to answer the question of how and why con-sumers react to rising product prices, how much they use the importance of information about product quality as a parameter of the decision, and how much consumers when choosing a product notice the price ending in a different number from the number of zeros. As consumer behavior is strongly influenced by a number of factors, it can be defined that the consumer’s response to selected activities: price increases, lack of product information and numerical way of expressing product prices may not contain all factors and their relationships and simplifies the picture of the consumer model. In order to test hypotheses about the extent to which customers are sensitive and willing to replace a product with certain substitutes, i.e., how willing they are to conclude about a product they buy based on price if they do not have enough information about the product and how much zeros are favored by consumers when shopping, an empirical study was conducted on a sample of 214 respondents. The results of the research indicate that in moments when respondents do not have enough information about the product, they are not inclined to draw conclusions solely on the basis of price, and prices ending in odd numbers or non-zero are not more attractive than those ending in zero. Full article

This study examines the effect of economic policy uncertainty (EPU) on sustainable investment returns by using panel data of stock market returns and the EPU index from twelve countries for the period from April 2015 to December 2020. In addition, precious metal prices, energy prices, and cryptocurrency prices are used as control variables. To do so, we investigate the impact of EPU, gold prices, oil prices, and Bitcoin prices on stock market returns by using the panel autoregressive distributed lag (ARDL) model to examine both the long-run correlation and short-run effect. Our findings show that EPU, gold prices, oil prices, and Bitcoin prices have a time-varying significant impact on sustainable stock market returns. We discovered that EPU has a significantly negative impact on the returns of the sustainable stocks in the markets over the long run. In contrast, the rise of the gold price, oil price, and Bitcoin price have a significantly positive impact on the returns of the sustainable stocks in the twelve sustainable markets in the long run. On the other hand, EPU in Singapore, Spain, the Netherlands, and Russia has a significant short-run impact on market returns in each country. Based on the findings, managers and investors in the sustainable stock markets are highly recommended to pay more attention to the volatility of EPU, gold prices, oil prices, and Bitcoin prices in the short run to control the risk of returns in the sustainable stock market. Furthermore, policymakers must closely monitor the movement of the EPU index, as it is a major driver of sustainable stock market returns. Full article

The global financial crisis of 2008, triggered by the collapse of Lehman Brothers, highlighted a banking system that was widely exposed to systemic risk. The minimization of the systemic risk via a close and detailed monitoring of the entire banking network became a priority. This is a complex and demanding task considering the size of the banking systems; in the US and the EU they include more than 10,000 institutions. In this paper, we introduce a methodology which identifies a subset of banks that can: (a) efficiently represent the behavior of the whole banking system, and (b), provide, in the case of a failure, a plausible range of the crisis dispersion. The proposed methodology can be used by the regulators as an auxiliary monitoring tool to identify groups of banks that are potentially in distress and try to swiftly remedy their problems and minimize the propagation of the crisis by restricting contagion. This methodology is based on graph theory, and more specifically, complex networks. We termed this setting a “multivariate Threshold–Minimum Dominating Set” (mT-MDS), and it is an extension of the Threshold–Minimum Dominating Set methodology. The method was tested on a dataset of 570 U.S. banks, including 429 solvent ones and 141 failed ones. The variables used to create the networks were as follows: the total interest expense; the total interest income; the tier 1 (core) risk-based capital; and the total assets. The empirical results reveal that the proposed methodology can be successfully employed as an auxiliary tool for the efficient supervision of a large banking network. Full article