J. Risk Financial Manag., Volume 14, Issue 7 (July 2021) – 56 articles

One of the notable features of bitcoin is its extreme volatility. The modeling and forecasting of bitcoin volatility are crucial for bitcoin investors’ decision-making analysis and risk management. However, most previous studies of bitcoin volatility were founded on econometric models. Research on bitcoin volatility forecasting using machine learning algorithms is still sparse. In this study, both conventional econometric models and a machine learning model are used to forecast the bitcoin’s return volatility and Value at Risk. The objective of this study is to compare their out-of-sample performance in forecasting accuracy and risk management efficiency. The results demonstrate that the RNN outperforms GARCH and EWMA in average forecasting performance. However, it is less efficient in capturing the bitcoin market’s extreme events. Moreover, the RNN shows poor performance in Value at Risk forecasting, indicating that it could not work well as the econometric models in explaining extreme volatility. This study proposes an alternative method of bitcoin volatility analysis and provides more motivation for economic researchers to apply machine learning methods to the less volatile financial market conditions. Meanwhile, it also shows that the machine learning approaches are not always more advanced than econometric models, contrary to common belief. Full article

The dynamics of the interconnected global market and consumption behavior has recently changed considerably. Using a sample of 28 nations within the European Union, the study examined the degree to which economic growth and inflation impacted economic sentiment and household consumption during the time frame of December 2019 up to October 2020. The results estimated via panel generalized method of moments and panel least squares (with cross-section weights, time fixed effects) showed that economic sentiment and household consumption were significantly shaped by the proxies of economic growth and inflation. Moreover, in the case of economic sentiment, the negative impact of inflation was much stronger than the positive impact of economic growth. The reverse applied in the case of household consumption. The study draws policy implications regarding the strategies that public authorities, companies, and individual consumers could apply for stimulating national economies amid challenging times. Full article

The debate about whether or not a growth imperative exists in debt-based, interest-bearing monetary systems has not yet been settled. It is the goal of this paper to introduce a new perspective in this discussion. For that purpose, an SFC computational model is constructed that simulates a post-Keynesian endogenous money system without including economic parameters such as production, wages, consumption and savings. The case is made that isolating the monetary system allows for better analysis of the inherent properties of such a system. Loan demands, which are assumed to happen, are the driving force of the model. Simulations can be run in two modes, each based on a different assumption. Either the growth rate of the money stock is assumed to be constant or the loan ratio, expressed as a percentage of the money stock, is assumed to be constant. Simulations with varying parameters were run in order to determine the conditions under which the model converges to stability, which is defined as converging to a bounded debt ratio. The analysis showed that the stability of the model is dependent on net bank profit ratios, expressed relative to their debt assets, remaining below the growth rate of the money stock. Based on these findings, it is argued that the question about the existence of a growth imperative in debt-based, interest-bearing monetary systems needs to be reframed. The question becomes whether a steady-state economy can realistically support such a system without destabilising it. In order to answer this question, the real-world behaviour of economic actors must be included in the model. It was concluded that there are indications that it might not be feasible for a steady-state economy to support a stable debt-based, interest-bearing monetary system without strong interventions. However, more research is necessary for a definite answer. Real-world observable data should be analysed through the lens of the presented model to bring more clarity. Full article

We estimate how an acquiring firm’s risk changes depending on whether the market initially judges the acquisition to be neutral, strongly negative, or strongly positive for the shareholders of the acquiring firm. We found that for an average neutral acquisition, the annualized standard deviation of an acquiring firm’s total return declines by 5%. In contrast, acquisitions judged negatively by the market result in a 5% increase in total risk, while acquisitions judged positively by the market feature a 30-basis-point increase in total risk. We found the median acquisition to be value creating, not value destructive. Value destruction tends to be concentrated among large firms and to be associated with extreme negative outliers. Acquiring firms with longholder CEOs are more prone to undertake acquisitions and more prone to take on risk, but are less prone to engage in value-destructive acquisitions than acquiring firms with non-longholder CEOs. In this respect, acquiring firms with non-longholder CEOs are more apt to undertake risky bad acquisitions, especially when their prior returns lie above the industry average. In addition, acquiring firms with non-longholder CEOs are less prone to take on good acquisitions that are high in risk. As a general matter, firms with longholder CEOs are less risk sensitive to changes in prior returns than firms with non-longholder CEOs. Full article

The study aimed to investigate the role of non-financial measures in predicting corporate financial distress in the Indian industrial sector. The proportion of independent directors on the board and the proportion of the promoters’ share in the ownership structure of the business were the non-financial measures that were analysed, along with ten financial measures. For this, sample data consisted of 82 companies that had filed for bankruptcy under the Insolvency and Bankruptcy Code (IBC). An equal number of matching financially sound companies also constituted the sample. Therefore, the total sample size was 164 companies. Data for five years immediately preceding the bankruptcy filing was collected for the sample companies. The data of 120 companies evenly drawn from the two groups of companies were used for developing the model and the remaining data were used for validating the developed model. Two binary logistic regression models were developed, M1 and M2, where M1 was formulated with both financial and non-financial variables, and M2 only had financial variables as predictors. The diagnostic ability of the model was tested with the aid of the receiver operating curve (ROC), area under the curve (AUC), sensitivity, specificity and annual accuracy. The results of the study show that inclusion of the two non-financial variables improved the efficacy of the financial distress prediction model. This study made a unique attempt to provide empirical evidence on the role played by non-financial variables in improving the efficiency of corporate distress prediction models. Full article

To date, measuring innovation has not been an exact science. As in many areas of organizational life, errors in measuring innovation are a recurring fact. Innovation researchers and practitioners alike have become increasingly interested in understanding the occurrence of organizational errors and how these errors affect innovation and its measurement. This empirical study aims to address this under-explored area by utilizing a qualitative in-depth case study at the innovation department of an organization with production sites and sales organizations worldwide. A total of 28 semi-structured interviews at several organizational levels were conducted, with innovation managers, project managers, senior managers, and staff. Based on the findings in this case study, three explanations are presented on how organizational errors occur when using innovation KPIs (key performance indicators). The first explanation can be connected to the increasing complexity of innovation and its intangible nature. Another explanation can be traced to the difference between innovation strategy and innovation KPIs. Lastly, room for organizational errors can be related to the multitude of individuals and organizational levels involved in innovation and its measurement. The implications for practitioners are that innovation KPIs are not precise metrics but should be seen as estimates with organizational errors. Whether or not these innovation KPIs can be used as tools to turn innovation into competitive advantages largely depends on whether wrong is right. Future research should focus on the metrics that are implemented and actually in use, as this future path would highlight the function and dysfunction that organizational errors in innovation KPIs can have. Full article

This study attempts to evaluate the energy and carbon footprint within the framework of international environmental treaties and the efforts made by 11 large polluting countries to mitigate climate change. The econometric methodology accounts for the presence of cross-sectional dependence while it employs second-generation panel unit root tests and cointegrated relationships. To secure the robustness of our findings, we conduct an ARDL approach employing dynamic panel data techniques. Dynamic OLS is also applied to verify the validity of the empirical results. The empirical analysis supports that the reduction in CO₂ emissions can be achieved without a slowdown in economic activity for the sample countries. The findings suggest insightful policy implications for policymakers and government officials. Full article

This paper explores price spillover effects around the COVID-19 pandemic market meltdown between the S&P 500 index, five other financial markets, and the VIX. Frequency domain causalities are estimated for the January–May 2020 time period on a high-frequency data set at five-minute intervals. The results reveal that price movements in the S&P 500 generally caused price movements in other financial markets before the market meltdown; however, a large number of bi-directional causalities emerged during the market meltdown. During the market recovery, S&P 500 price movements were more likely to be caused by other financial markets’ price movements. The VIX, exchange rate, and gold returns had the most prominent influence on the S&P 500 returns in the market recovery. Full article

In this study, we propose a wavelet-copula-GARCH procedure to investigate the occurrence of cross-market linkages during the COVID-19 pandemic. To explore cross-market linkages, we distinguish between regular interdependence and pure contagion, and associate changes in the correlation between stock market returns at higher frequencies with contagion, whereas changes at lower frequencies are associated with interdependence that relates to spillovers of shocks resulting from the normal interdependence between markets. An empirical analysis undertaken on six major stock markets reveals evidence of long-run interdependence between the markets under consideration before the start of the COVID-19 pandemic in December 2019. However, after the health crisis began, strong evidence of pure contagion among stock markets was detected. Full article

In this paper, we extend corporate disclosure and corporate cash holdings literature by testing whether corporate voluntary risk disclosure affects corporate cash holdings for a sample of Tunisian non-financial listed companies. As a measure of risk disclosure, we use manual content analysis to count the number of risk-related sentences in the narrative sections of corporate annual reports. As a measure of corporate cash holdings, we use the ratio of cash and cash equivalent over the total assets. Using a sample of 140 firm-year observations for the period of 2008–2013, we find that corporate risk disclosure has a negative impact on corporate cash holdings. Our results are consistent with agency, legitimacy and impression management theories. Our paper adds to the existing literature by being the first empirical evidence for the impact of risk disclosure on cash holdings. Our findings offer policy implications relevant for the current debate on the reliability of narrative risk disclosure and whether managers inform or obfuscate stakeholders by disclosing more risk-related information in their annual report narratives. Full article

The value of the company is influenced by a large group of factors that experts should take into account, in the evaluation process, and incorporate into their calculations. The paper is based on the knowledge and experience gained from more than 15 years of forensic practice and more than 60 expert opinions related to determining the value of the company. It clearly states, in selected two representative companies, how significantly creative accounting can influence the final value of the company. Therefore, it is necessary to think about how to eliminate these possible interventions in the process of valuing the company. Background: Creative accounting is an important issue that is being addressed worldwide. It can have significant impacts in many areas, but in the article, we focus specifically on the area of determining the value of the company in the companies of the Slovak Republic. Methods: Several methods are used, such as specifically selected methods of creative accounting, methods of determining the general value of the company’s assets, specifically the property method, and the business method were applied to companies. Subsequently, selected methods of determining creative accounting were used in the work. The Beneish model and the Piotroski model were selected for the needs of the expert’s methodological procedures. Results: From all the findings in our study, it follows that interventions in accounting can have a significant impact on the resulting value of the company. It depends on what kind of intervention is applied to the accounts and whether the expert is able to detect it. Conclusions: The result of the research, which is described in the article, is a proposal for the use of selected methods of detection of creative accounting by experts in the evaluation process. The paper proposes a coefficient of creative accounting, which adjusts the resulting value of the company. It is the first design created by longer-term research. In the process of determining the value of the company in the conditions of the Slovak Republic, interventions of this kind have not yet been applied to the final value. The proposed coefficient is one of several proposals that were the result of the dissertation. Full article

Barren ground and sites with low coverage by vegetation (e.g., dunes, soil surfaces, dry lakes, and riverbeds) are the main source areas of sand and dust storms (SDS). The understanding of causes, processes (abrasion, deflation, transport, deposition), and influencing factors of sandy and dusty particles moving by wind both in the boundary layer and in the atmosphere are basic prerequisites to distinguish between SDS. Dust transport in the atmosphere modulates radiation, ocean surface temperature, climate, as well as snow and ice cover. The effects of airborne particles on land are varied and can cause advantages and disadvantages, both in source areas and in sink or deposition areas, with disturbances of natural environments and anthropogenic infrastructure. Particulate matter in general and SDS specifically can cause severe health problems in human respiratory and other organs, especially in children. Economic impacts can be equally devastating, but the costs related to SDS are not thoroughly studied. The available data show huge economic damages caused by SDS and by the mitigation of their effects. Management of SDS-related hazards utilizes remote sensing techniques, on-site observations, and protective measures. Integrated strategies are necessary during both the planning and monitoring of these measures. Such integrated strategies can be successful when they are developed and implemented in close cooperation with the local and regional population and stakeholders. Full article

Entering a foreign market is challenging given the fierce competition posed by local incumbents. The literature suggests that when entering a foreign market, it is advantageous to locate where there are agglomeration benefits. Given the dynamic nature of regional development, foreign firms have multiple location options. While the literature has primarily focused on developed country multinationals’ (DMNEs) location decisions, emerging market multinationals (EMNEs) are increasingly becoming influential in high-tech industries. Due to differences in DMNE and EMNE resource endowments, they may consider alternative options when locating abroad and, thus, we examine these nuances. Using multinomial logistic regression, we investigate domestic and foreign location patterns of firms within the U.S. biopharmaceutical industry as of 2018. We constructed a unique dataset of 19,962 U.S. locations and examined the location patterns of DMNEs and EMNEs from 61 countries and territories. Given the heterogeneity of regional development in the U.S., we developed a typology that stratifies regions into four categories (developed, growth, transitioning, and nascent). Counterintuitively, we find that foreign multinationals are more likely to be attracted to less developed regions than domestic firms and have different location patterns, not only compared to domestic firms, but also with respect to each other. Full article

This paper investigates high-performance athletes’ development of their financial literacy and self-management skills and the related organisational support available to them during their athletic careers. The data were collected from 20 retired high-performance athletes (10 male and 10 female) representing six different countries (Japan, Mexico, Portugal, Singapore, South Korea, and the UK). Thematic analysis was applied to the processing of the data and five themes emerged: (1) Funding battles: financial challenges and misjudgements; (2) Coping Strategies; (3) Support from sponsors, parents, and sport organisations; (4) Development of Financial Literacy; and (5) Life After Sport. The data indicates that athletes experienced financial challenges due to a lack of organisational support, reduced or terminated funding, and limited opportunities to access sponsorship. Typically, athletes developed their financial literacy and self-management skills by ‘self-help’ or ‘trial and error’. The findings contribute to both literature and practice by providing empirical evidence on the coping strategies adopted by athletes in order to overcome financial challenges and on the methods used in order to develop their financial literacy and self-management skills. These findings inform sport organisations and governing bodies to develop support schemes for high-performance athletes as well as deepen our knowledge of athletes’ career development and transitions focusing on the financial aspect. Full article

This paper studies the role of budgets in implementing the systems integration strategies in an Australian post-acquisition case of two organisations and reducing its associated often-regarded high risks. It attempts a fresh narrative approach to examine the evolution of accounting and its effects on the challenges of post-acquisition integration processes by using the performative approach such as the sociotechnical networks of Actor Network Theory in a broader analytical framework as a possible solution to reducing the risks inherent in systems integration. The methodology of the case study is based on Callon’s model of Four-Moment translation where integration strategy and budgets are regarded as social practice and defined relationally as bundles of activities and take form in and through practice and interaction between diverse actors and actants. A qualitative approach is adopted in the examination of the systems integration networks in an Australian post-acquisition case. Data was collected and analysed using semi-structured interviews. It was found, through the examination of the routine practices of systems integration strategy making and how people enact and draw on a certain financial report on a daily basis to perform systems integration network strategies, that material forms of accounting act as a powerful structuring and inscription tool in integration activities, thus shaping integration strategic options and post-acquisition economic conditions of the organisation. The result shows how the risk could be reduced in the post-acquisition system integration. The research contributes to the risk, change, and accounting literatures by providing insights into the mundane and ordinary practices of different aspects of integration strategy making, and the way employees enact and draw on accounting numbers on a day-to-day basis to perform systems integration network strategies. This case study facilities this research to be further developed and broadened in terms of other cases, industries, and countries. Full article

This paper proposes an approximation method to create an optimal continuous-time portfolio strategy based on a combination of neural networks and Monte Carlo, named NNMC. This work is motivated by the increasing complexity of continuous-time models and stylized facts reported in the literature. We work within expected utility theory for portfolio selection with constant relative risk aversion utility. The method extends a recursive polynomial exponential approximation framework by adopting neural networks to fit the portfolio value function. We developed two network architectures and explored several activation functions. The methodology was applied on four settings: a 4/2 stochastic volatility (SV) model with two types of market price of risk, a 4/2 model with jumps, and an Ornstein–Uhlenbeck 4/2 model. In only one case, the closed-form solution was available, which helps for comparisons. We report the accuracy of the various settings in terms of optimal strategy, portfolio performance and computational efficiency, highlighting the potential of NNMC to tackle complex dynamic models. Full article

In an exchange economy with endowment inequality, we investigate how preferences with external habits affect the equity risk premium. We show that the dynamics of external additive habits with wealth inequality are complex when a background risk is present. It is ambiguous whether wealth inequality will increase or decrease the equity premium even when the income uncertainty is low. This result extends literature by suggesting that wealth inequality has a small role in explaining asset pricing puzzles. Full article

The main objective of this paper is to investigate the determining factors of loan delinquencies from the perspective of borrower attributes and loan characteristics. Empirical results indicated that the borrower-lender distance factor, collateral, education levels as well as availability of a monthly budget are having significant effects on loan delinquencies. On the other hand, level of income and gender have no significant impact on repayment behaviour. Credit is good as it allows the borrowers financial flexibility, however, debt is viewed as bad if it was not managed properly. Therefore, a correct attitude towards credit management and self-discipline can be encouraged to reduce loan default rates. Full article

The Prebisch-Singer (PS) hypothesis, which postulates the presence of a downward secular trend in the price of primary commodities relative to manufacturers, remains at the core of a continuing debate among international trade economists. The reason is that the results of testing the PS hypothesis depend on the starting point of the technical analysis, i.e., stationarity, nonlinearity, and the existence of structural breaks. The objective of this paper is to appraise the PS hypothesis in the short- and long-run by employing a novel multiresolution wavelets decomposition to a unique data set of commodity prices. The paper also seeks to assess the impact of the terms of trade (also known as Incoterms) on the test results. The analysis reveals that the PS hypothesis is not supported in the long run for the aggregate commodity price index and for most of the individual commodity price series forming it. Furthermore, in addition to the starting point of the analysis, the results show that the PS test depends on the term of trade classification of commodity prices. These findings are of particular significance to international trade regulators and policymakers of developing economies that depend mainly on primary commodities in their exports. Full article

We examine the financial performance of the forest products industry in the initial phase of the COVID-19 pandemic, employing data for publicly trading companies in the industry globally. We first examine the market investor reaction to the declaration of a pandemic by the World Health Organization (WHO) in March 2020 by conducting an event-study analysis. Then, we analyze medium-term changes in stock returns and their systematic risk by an econometric estimation of the capital asset pricing model. Our event-study analysis of the forest products industry shows that the forestry subsector was impacted more than the paper subsector when the WHO declared the pandemic. The effect was most prominent in North America. We find that the systematic risk for the forestry subsector tended to increase during 2020, until October. Again, this effect was most clear in North America. Conversely, the impact on the paper subsector was more stable. Full article

Despite that the relationship between corporate social responsibility activities and real estate operations seems relevant, only some studies have been conducted to explore the reasons that drive these activities in real estate companies. This work presents the relationship between CEO personality traits and corporate social responsibility (CSR) and shows whether corporate governance (CG) practices mitigate or enhance this relationship. This study uses a sample of 420 firm-year-observations using a sample of European real estate firms indexed on Stoxx Europe 600 Index from 2010 to 2019. To test the developed hypotheses, feasible generalized least square (FGLS) regression is applied. The results show that increased confidence in CEOs is an important factor in determining corporate incentives to undertake social responsibility activities. In addition, it has been shown that effective corporate governance practices lead significantly to moderate CEO behavior with regard to corporate social responsibility sharing. Since corporate governance can have a significant impact on CEOs’ behavior in relation to corporate social responsibility, the author recommends firms to improve corporate governance in listed European real estate companies. Full article

Using cross-sectional data from a nation-wide survey of American head-of-households conducted in the spring of 2010, we examined the ameliorating effects of economic literacy on the probability of specific household financial outcomes resulting from the 2008 financial crisis and the associated Great Recession. A series of probit regressions were estimated to capture the impact of economic literacy on the probability that households experienced job loss, delinquent mortgage payments, delinquent credit card payments, delinquent auto loan payments, loss of home, and personal bankruptcy. The head-of-household’s economic literacy was measured by the level of formal education received in economics and by the score achieved on an in-survey quiz of basic economic concepts and principles. The results indicate that realized quiz scores were correlated with the mitigation of job loss, late payment behavior, and personal bankruptcy, ceteris paribus. However, the results for the impact of formal economic coursework in school were mixed. Full article

Despite the potential importance of crime rates in investments, there are no indices dedicated to evaluating the financial impact of crime in the United States. As such, this paper presents an index-based insurance portfolio for crime in the United States by utilizing the financial losses reported by the Federal Bureau of Investigation. The objective of our paper is to introduce new risk hedging financial contracts for crime, consistent with dynamic asset pricing. Underlying the index, we hedge the investments by issuing marketable European call and put options and providing risk budgets. These budgets show that real estate, ransomware, and government impersonation are the main risk contributors in our index. Next, we evaluate the performance of our index via stress testing to determine its resilience to economic crisis. Of all the factors considered in this study, unemployment rate has the potential to demonstrate the highest systemic risk to the portfolio. Our portfolio will help investors envision risk exposure in the market, gauge investment risk based on their desired risk level, and hedge strategies for potential losses due to economic crashes. In conclusion, we provide a basis for the securitization of insurance risk from certain crimes that could forewarn investors to transfer their risk to capital market investors. Full article

This paper studies the effect of COVID-19 on the volatility of Australian stock returns and the effect of negative and positive news (shocks) by investigating the asymmetric nature of the shocks and leverage impact on volatility. We employ a generalised autoregressive conditional heteroskedasticity (GARCH) model and extend the analysis using the exponential GARCH (EGARCH) model to capture asymmetry and allegedly leverage. We proxy the news related to the negative effect of COVID-19 on the Australian health system and its economy as bad news, and on the other hand, measures taken by government economic stimulus packages through their monetary and fiscal policies as good news. The S&P ASX200 (ASX-200) index is used as a proxy to the Australian stock market, and we use value-weighted returns of the stocks listed on ASX-200 for the period 27 January 2020 to 29 December 2020. The empirical results suggest the EGARCH model fits better in capturing asymmetry and leverage than the GARCH model in estimating the volatility of the Australian stock returns. However, another interesting finding is that the EGARCH model with volatility equation without news demonstrates a larger (smaller) leverage effect of the negative (positive) shocks on the conditional volatility compared to its variant with the news. Full article

This study is the first to investigate the efficient market hypothesis in its weak form and the random walk behaviour of globally listed private equity (LPE) markets represented by nine global, regional, and style indices based on weekly data covering the period from January 2004 to December 2020. Autocorrelation tests, variance ratio tests, and a non-parametric runs test are employed. The results of the autocorrelation tests and the variance ratio tests tend to correspond for all indices, and they reject the random walk hypothesis for the returns of all LPE indices under investigation. In contrast, the runs test for direct weak-form market efficiency cannot reject the null hypothesis of a random walk process for almost all LPE indices under investigation. Furthermore, there is no evidence that the market efficiency of globally listed private equity markets has improved after the global financial crisis. Due to the fact that the rapidly growing asset class of LPE as a form of private equity is still relatively unknown, the implications of the results of our paper are relevant for investors, policy makers, and academics alike. In addition, the results provide valuable insights to better understand the emerging asset class of LPE. Full article

The purpose of this article is to develop a bank-oriented rating approach, tailored by incorporating the various heterogeneity dimensions characterizing financial institutions, named “Bank-Tailored Integrated Rating” (BTIR). BTIR is able to catch the financial cycle, including the pandemic crisis, and the ongoing change in banking normative from a microeconomic perspective, and it is inherently coherent with the challenging frontier of forecasting tail risk in financial markets in similar ways as in De Nicolò and Lucchetta (2017), although their approach is macroeconomic) since it considers the downside risk in the theoretical framework. The method employed was an innovative integrated rating (IR) statistical and econometrical panel pre-selection analysis that takes into account the characteristics of risk and the greater heterogeneity of the banks. The result is a challenge rating procedure delivering forward-looking preselection requested by the new International Financial Reporting Standard (IFRS-9). The future direction is extremely promising given the increase in idiosyncratic and systemic risks in financial markets. Full article

The COVID-19 pandemic has been shown dire consequences for the global economy, not only in the past and present but also in the future. These consequences are not only humanitarian but also financial and economic. This article raises the question of whether the state of the health system is a factor that determines the direction of changes in consumer and business sentiment during the COVID-19 or whether other factors are more significant. The goal is to find out whether there is real progress in the national health system of a particular country or a regression and on this base to answer the question: What is more important for the expectations of the population and industry during the spread of the pandemic; the dynamics of the development of the health system or other factors? To assess the dynamics of the development of the health care system in different countries, we used the annual data on individual health indicators of the OECD countries for 2006–2019. There were identified countries with dynamic development and a slowing/deteriorating health system. Based on Granger’s approach in EViews, we used the Augmented Dickey–Fuller test and admit that health care systems are not a determining factor in consumer and business sentiment during a pandemic, i.e., only economic factors. The research contributes to the developed COVID-19 research by examining the impact of the changes in the mutual influence of Confidence indexes and macro indicators during the pandemic. Full article

Risk is inevitable in business. For large companies, risk management is formalised and structured through compliance with industry standards. However, small and medium-sized businesses (SMEs) rarely have adequate resources to develop their own standards or conform to pre-established criteria. This results in an increased vulnerability to risk, which tends to undermine SMEs’ sustainability. The primary reasons for the low adoption rate of risk management are related to the tremendous initial difficulty in orientating the business concerning risk and the significant investment of the workforce in developing and implementing a structured managerial process. The objective of this paper is to produce a guided process tool for small and medium-sized businesses with which they can identify, evaluate, and appropriately address risks from an SME perspective. Moreover, this intervention would offer enhancements at no cost beyond the time of its implementation. In order to identify what constitutes holistic risk management, document analysis was applied, which utilised risk management standards, academic articles, books, and regulatory policy and strategy documentation. The identified elements were integrated with a tool that improves business owners’ capacity to position themselves in context with their daily risk management challenges. Full article

This study examines the effect of geographic scope in mitigating the adverse impact of the COVID-19 pandemic in the real estate sector. Utilizing the Chinese setting over the two-month period in 2020 from the beginning of the outbreak to the successful containment of the spread of virus, we show that while the pandemic has negatively impacted real estate firm returns, firms with broader geographic scope and more geographically diversified property allocations have managed to better endure the crisis. We further find that firms with higher leverage report lower returns during the pandemic irrespective of their geographic scope, but larger firms can lessen the adverse impact of the pandemic only if they have adopted a more diversified strategy. Overall, our study provides novel evidence on the benefit of diversification by demonstrating the importance of geographic scope and diversification at times of crises. Specifically, we show corporate diversification could be especially useful to mitigate the negative stock market reactions resulting from the pandemic. Moreover, diversification could even become essential for larger firms that are expected by the market to be more diversified. Full article

In recent years, the attention of investors, practitioners and academics has grown in cryptocurrency. Initially, the cryptocurrency was designed as a viable digital currency implementation, and subsequently, numerous derivatives were produced in a range of sectors, including nonmonetary activities, financial transactions, and even capital management. The high volatility of exchange rates is one of the main features of cryptocurrencies. The article presents an interesting way to estimate the probability of cryptocurrency volatility clusters. In this regard, the paper explores exponential hybrid methodologies GARCH (or EGARCH) and through its portrayal as a financial asset, ANN models will provide analytical insight into bitcoin. Meanwhile, more scalable modelling is needed to fit financial variable characteristics such as ANN models because of the dynamic, nonlinear association structure between financial variables. For financial forecasting, BP is contained in the most popular methods of neural network training. The backpropagation method is employed to train the two models to determine which one performs the best in terms of predicting. This architecture consists of one hidden layer and one input layer with N neurons. Recent theoretical work on crypto-asset return behavior and risk management is supported by this research. In comparison with other traditional asset classes, these results give appropriate data on the behavior, allowing them to adopt the suitable investment decision. The study conclusions are based on a comparison between the dynamic features of cryptocurrencies and FOREX Currency’s traditional mass financial asset. Thus, the result illustrates how well the probability clusters show the impact on cryptocurrency and currencies. This research covers the sample period between August 2017 and August 2020, as cryptocurrency became popular around that period. The following methodology was implemented and simulated using Eviews and SPSS software. The performance evaluation of the cryptocurrencies is compared with FOREX currencies for better comparative study respectively. Full article