Different Types Of Risks Research Articles

Portfolio replication: Islamic vs conventional

PurposeThis conceptual paper aims to explore portfolio replication to resolve post-COVID pandemic private and public debt. This paper stresses the need to be less dependent on a debt-based system and the emergence Islamic equity market.Design/methodology/approachThis study analyses different types of risks involved in Islamic and conventional portfolios by using risk measures such as relative beta and comparatively examining the systematic and downside risk exposure of Islamic and conventional portfolios. Data was collected monthly from 2016 to 2022.FindingsThe findings indicate that the replications of a conventional portfolio into an Islamic portfolio are compatible with the regulatory standard, sharia boundaries and professional practices developed from investment theory. The result shows that Islamic portfolios have lower risk exposure compared with their conventional counterparts in most of the sample years, therefore, become further attractive for debt–equity portfolio swaps and Sharia-compliant investors preferring low-risk preferences. The result confirmed that the Islamic portfolios have a higher return and less risk than conventional portfolios.Research limitations/implicationsThe implications of this research are to provide a road map to the regulators, policymakers, governments and the financial industry on how to rearrange some of the public and private debt. A likely remedy is incorporating Islamic financial instrument principles through the equitisation of public and private debt.Practical implicationsThis research contributes to investors (particularly those who want to avoid riba [usury] based investment) to make more diversified portfolios by considering Islamic portfolios to reduce risk exposure.Originality/valueTo the best of the authors’ knowledge, this is the first paper to create bivariate debt–equity portfolios swaps composed of Islamic and conventional assets.

Reflection of the Impact of Risks in Financial and Non-financial Reporting

The economic activity of an organization is always associated with different types of risks. Financial statements serve as an information base for their identification, assessment, and control over their level. Almost all known risks affect the reliability of financial and completeness of non-financial reporting. Today the issues concerning approaches to assessing risk situations, ways of reflecting information about them in the reporting of companies remain topical. The emergence of new types of risks poses new challenges for business entities. It includes reducing or avoiding negative consequences from the onset of risks; unification of information about them in financial and non-financial reporting; search for methods of evaluation, control, and management of their new types. During the study, the author conducted a bibliographic study of the economic literature in the field of disclosure of information about risks in reporting, using methods of generalization, systematization, grouping, analysis, and synthesis.

Corporate Sustainability and Risk Management—The U-Shaped Relationships of Disaggregated ESG Rating Scores and Risk in the German Capital Market

This study addresses the relationship between the (dis)aggregated ESG rating and different types of risk (i.e., market risk, idiosyncratic risk, total risk) in the German stock market. We investigate not only the overall ESG rating and the E, S, and G pillar scores but also all the underlying category scores. Thereby, we provide in-depth insight into diverse CS operations. We cover 454 firm years (2012–2019) using ordinary least squares regression with firm and year fixed effects. Our main insights are the U-shaped relationships between CS and risk: Ecological investments first decrease systematic risk (beta), while overinvestment increases systematic risk again. Likewise, social investments initially decrease idiosyncratic risk, while overinvestment increases idiosyncratic risk again. Further findings suggest only one linkage between systematic risk and the social pillar score. In the category scores, a few more relevant linkages were identified, which indicates that disaggregation of the ESG ratings increases the explanatory power of models. In respect to findings from other capital markets, it appears that the effects of the ESG ratings on risk may depend on the existing level of sustainability in the capital market. Last, our study provides insights into the nonlinearity of the CS–risk relationships.

Demonetization risk in banks and share markets

Demonetization refers to the removal of a certain type of currency from circulation as legal tender (for example, 500 and 1000 currency notes). Risk management entails recognizing and analyzing different types of risk exposure, as well as adopting preventative measures to mitigate the risk. This research focuses on the different types of contracts and risks that investors face in the stock market, as well as risk in the banking sector.

The sector‐level safety net provided by the current mix of farm programs

AbstractCurrent farm policy includes a diverse set of programs intended to provide a financial safety net for producers of grains, oilseeds, and cotton. These programs make payments contingent on national market prices and yields at the farm or county level. A review of data for the 2014–2020 period demonstrates the successes and limitations of crop insurance, agriculture risk coverage and price loss coverage at offsetting reductions in national net market revenues for particular crops. Forward‐looking stochastic analysis confirms these programs protect against different types of risks but provide support levels that can vary greatly across commodities and time.

Developing next generation marine risk analysis for ships: Bio-inspiration for building immunity

Research on autonomous ships has led to several ideas about how they could be operated in terms of level of automation and human presence. However, all seem to point towards systems that will be more complex due to issues such as the tighter integration with software and the interactions with humans-in-the-loop. These ships will likely be completely different compared to conventional ones, which puts into question the usefulness of our current understanding of risk and how it is managed for ensuring safe operation. By a critical review of the literature, this paper highlights the need for advanced methods that will combine machine learning and simulation for dynamically assessing risk in a life cycle context and effectively transferring acquired operational knowledge back to the design phase. The main objective of this paper is to describe a novel life cycle risk framework for developing algorithms inspired by the biological immune system, which provides lifetime protection from harmful pathogens. This framework can be used to construct machine learning algorithms for dynamic risk monitoring and adaptive risk control that address different types of risk, while enabling faster future response to previously unencountered risks and operational feedback to design through learning. We demonstrate the feasibility of our approach in a specific maritime context with a case study on collision risk identification. Considering the lack of experience for autonomous ships, the benefit of our immune-inspired approach is that it departs from the classic risk scenario concept and that it does not rely on safety performance data for identifying risk factors and training the algorithms. We suggest this framework is particularly suitable for autonomous ships with high levels of autonomy, although applicable to conventional ships as well, as it can contribute to empowering them with risk awareness and the capability to deal with any risk environment.

China Transport Supply Chain Risk Management Challenges Face to COVID-19 Analysis

The international COVID-19 outbreak at the beginning of 2019 has had a huge influencing factor on lot of global and local manufacturing transportation chains, and triggered a continuous risks of logistics chains breakage by the way the COVID-18 pandemic has revealed the weakness of intercontinental supply chains arising from initial raw material scarcity, mass production and transportation disruption, and human being isolation. Among them, the short-term and medium-term and long-term impacts include encouraging companies to improve the flexibility of supply chains by constructing supply chains digital platforms, supply chains diversification systems and supply chains early warning system in the short, medium and long term, the global supply chains layout will change from internationalization to regionalization, and some high-end manufacturing industries will have a backflow trends. The risks associated with global supply chains management have created a discourse among practitioners and academics. Supply chains risk management is an integral function of the supply chains networks. Supply chains risks management have increasingly becoming a more popular research area recently, when COVID-18 appeared regionally, internationally and globally. In the article there are presented different calculation equations beginning from risk assessment during transportation and finishing by risk modeling, there are important factors influencing logistics and mainly supply chains when different types of risks appeared during COVID-22 transportation time.

Mitigating Risk in Financial Industry by Analyzing Social-Media with Machine Learning Technology

A large amount of data is available on Twitter that can be used to manage different types of risks in financial institutions. This paper shows how machine learning algorithms can be applied to analyze large unstructured data and train a model to make a future prediction on tweets to categorize them by risk type and use sentiment analysis to understand the risk type. This model reads each tweet and categorizes them by risk using a specified dictionary and adds sentiment analysis to show the risk type seen in each tweet. Logistic regression used in this research helped to formulate the prediction model. Twitter data from 2019 was used to train and test a supervised machine learning algorithm and once the model started predicting tweets efficiently, it was used to predict twitter data from 2022 in our experimental research. Our experiment confirmed that Twitter data can be used to manage risk with the right type of modeling using machine learning techniques.

İSLAMİ BANKALARDA RİSK YÖNETİMİ: TÜRKİYE'DEKİ KATILIM BANKALARI ÜZERİNDE BİR ARAŞTIRMA

Risk management is of strategic importance for banks whose operations are largely based on risky transactions. Islamic banks face almost all risks exposed in conventional banks. Risks are further diversified and complicated in Islamic banks. In this respect, risk management in these banks requires some unique risk measurement, risk mitigation and risk management systems. Also, Islamic banks cannot use some of the methods used by conventional banks in risk management. Therefore, there is a need for unique methods compliant with Shariah principles. In this paper, a detailed literature review has been conducted on studies investigating risk management in Islamic banks and the theoretical framework of the subject was established. Then, a qualitative research was conducted in order to identify the main risks encountered in Islamic (Participation) banks operating in Turkey. The risk management techniques of these banks were examined and compared with conventional banks. Also, main problems in risk management were determined and possible solutions were recommended in this context. Within the scope of the research, the data obtained by the interview method was interpreted by descriptive analysis method. According to results, risk management in Islamic banks is largely similar to conventional banks. On the other hand, different types of risks encountered in these banks and the obligation to comply with Islamic principles differentiate Islamic banks in the risk management process.

Revisiting the optimal insurance design under adverse selection: Distortion risk measures and tail-risk overestimation

This paper studies the design of optimal insurance from an insurer's perspective when it is subject to adverse selection issue. Different from the literature, the insureds who are exposed to different types of risks are allowed to apply different preference measures. By assuming that the insureds' preferences are dictated by some distortion risk measures that always over-estimate the tail risk, we figure out the optimal policy menu without assuming the parametric form of indemnity functions. We also find that the insureds who deem their losses riskier than those of others will always purchase full insurance, which is consistent with the results in past studies. Furthermore, we show that in the presence of adverse selection the optimal policy menu always outperforms the optimal single policy in the sense that the former can yield a larger expected profit for the insurer. This outcome also echoes some existing results in the literature.

China Transport Supply Chain Risk Management Challenges Face to Covid-19 Analysis

The international COVID-19 outbreak at the beginning of 2019 has had a huge influencing factor on lot of global and local manufacturing transportation chains, and triggered a continuous risks of logistics chains breakage by the way the COVID-18 pandemic has revealed the weakness of intercontinental supply chains arising from initial raw material scarcity, mass production and transportation disruption, and human being isolation. Among them, the short-term and medium-term and long-term impacts include encouraging companies to improve the flexibility of supply chains by constructing supply chains digital platforms, supply chains diversification systems and supply chains early warning system in the short, medium and long term, the global supply chains layout will change from internationalization to regionalization, and some high-end manufacturing industries will have a backflow trends. The risks associated with global supply chains management have created a discourse among practitioners and academics. Supply chains risk management is an integral function of the supply chains networks. Supply chains risks management have increasingly becoming a more popular research area recently, when COVID-18 appeared regionally, internationally and globally. In the article there are presented different calculation equations beginning from risk assessment during transportation and finishing by risk modeling, there are important factors influencing logistics and mainly supply chains when different types of risks appeared during COVID-22 transportation time.

Measuring the financial and social performance of French mutual funds: A data envelopment analysis approach

AbstractSocially responsible investors pursue both financial and non‐financial goals. In this paper, we attempt to assess the performance of French socially responsible mutual funds (SRMFs). We consider the data envelopment analysis (DEA) approach, which allows us to assign a unique efficiency score while combining financial and social characteristics, using various combinations within different types of risk (total risk, market risk, and downside risk). We report the list of funds found to be DEA efficient using various output‐oriented models. We also compare our obtained results with the traditional and modern measures used in the literature (Sharpe, Treynor, and the information ratio). We contribute to the literature by testing the validity of the DEA methodology in the financial context. The findings have important implications for fund selection processes and would be mainly of interest to investors and fund managers who integrate environmental, social, and governance criteria into their investment choices.

Risk perception, affect, and information avoidance during the 2016 U.S. Presidential election

During a presidential election cycle, voters consume information to alleviate uncertainty about the candidates and the process. As a result, elections offer an interesting (and somewhat novel) context for studying risk-related information behaviors. Here we argue that individuals avoid certain information, depending on the amount of risk they perceive and to what extent they experience risk-related affect. Based on national survey data collected one month prior to the 2016 U.S. presidential election (N = 512), we found that risk perception influenced information avoidance through affective responses to the different types of risks. Specifically, financial and political risk influenced avoidance through negative affective response to risk, while policy risk influenced avoidance through both positive and negative affective response. Thus, the mediation of affective responses varies by the type of perceived risks.

Welfare effects of business cycles and monetary policies in a small open emerging economy

This paper evaluates the welfare cost of business cycles and the effects of monetary policies in a DSGE model tailored to a small open emerging economy. The model generates rich business cycle fluctuations, features labor market idiosyncratic risks and accounts for imperfect financial and capital markets inclusion. In this context, households excluded from financial and capital markets experience larger costs of business cycle fluctuations due to their inability to hedge against labor market idiosyncratic risks. Different degrees of exposure to different types of risks generate divergent preferences regarding the conduct of monetary policy. While a strong response to inflation deviation from target maximizes welfare for included households, excluded households benefit the most from unemployment and wage stabilization policies.

A review of blockchain technology application on supply chain risk management

The purpose of this review is to investigate the landscape of scientific literature in analyzing the blockchain technology capabilities for enhancing supply chain resilience in times of increased risk and uncertainty. This article adopts a systematic literature analysis to extract and analyze the related papers. It is found that the blockchain technology can be considered as enabling technology for supply chain risk management. It helps to manage different types of risks in different industries, leading to resilience and robustness of a supply chain. This review also suggested that new research methodology, wider industrial adoption and combined implementation of blockchain and other advanced technologies can be investigated in the future to reduce supply chain risk more efficiently and effectively.

Ogledi strategije lobiranja kao mogućeg odgovora na amortizovanje aktivnog političkog rizika u poslovanju kompanije

The starting point of this paper is given through the issues observed in the part of economic-political business of a company. Every company faces different types of risks during its economic activities. One such risk is political risk, which can affect the company and its business in the country, but also globally.The concept of the paper is a presentation of a thematic study of the concept of political risk limited in the context of the economic-political dimension to the business environment in which the business of a company takes place. In this field, the pressure in the form of specific political risks on the company's operations is multiple, and risk management involves various measures and activities that can potentially reduce their impact. In this context, we believe that lobbying, as a realistic strategic model, can potentially respond to political risks in business. The basis of lobbying arises from the influence on political decision-makers in the process of making various regulations in the field of economic business which in perspective shows a certain degree of company satisfaction, but also the potential to reduce the intensity of political risk. The author tries to use a theoretical approach to explain the strategic approach of lobbying as one of the answers to the disenfranchisement of the political risk of the company's business before any economic investment.

The impact of continuous and discontinuous host country risk on the location choice of Chinese enterprises' OFDI

Research on outwards foreign direct Investment (OFDI) has presented consistent evidence that Country risk has a significant impact on the choice of location for OFDI by firms. Using the overseas wholly-owned subsidiaries of Chinese listed enterprises between 2002 and 2020 as a sample, this study investigates the impact of different types of risk on the location choice of Chinese enterprises' OFDI, and the moderating effect of the state-owned status of enterprises on this impact. The empirical results show that both continuous and discontinuous risks in the host country have a suppression effect on Chinese enterprises' OFDI. This study also explores the moderating effect of internationalization experience and statehood on the suppression effect.

Bank Risk Capital and Its Effectiveness in Selected Euro Area Banking Sectors

Risk capital or capital at risk (CaR) refers to the amount of capital set aside and maintained by banks to cover different types of risk. For banks, it is used as a buffer against claims or expenses in the event that ordinary capital is not enough to cover them. Thereby, risk capital can also be recognized as risk-bearing capital or surplus funds. Risk capital may generate very high costs, but on the other hand it protects against insolvency. That’s why a bank needs to find the ‘Gold mean’—the optimal value of risk capital that will not lower its efficiency, but still ensure financial security. The main objective of the study is identification of interdependencies between bank risk capital and effectiveness of the aggregated Eurozone banking sector and selected national banking sectors of the euro area. The paper tries to answer the research question whether the risk capital supports or lowers banks’ operational effectiveness. The adopted research hypothesis stated that there is a positive correlation between profitability and size of bank risk capital. To verify the hypothesis regression models were used. The results indicate that the size and structure of bank capital impact on the credit institutions’ effectiveness in the analyzed banking sectors, however with different intensity. Thereby, the article fulfils a research gap in the field of research studies that take into account how capital at risk and specific capital adequacy regulations may impact on a bank’s efficiency.

Exposure risk analysis of COVID-19 for a ride-sharing motorbike taxi.

A dominant mode of transmission for the respiratory disease COVID-19 is via airborne virus-carrying aerosols. As national lockdowns are lifted and people begin to travel once again, an assessment of the risk associated with different forms of public transportation is required. This paper assesses the risk of transmission in the context of a ride-sharing motorbike taxi—a popular choice of paratransit in South and South-East Asia and Sub-Saharan Africa. Fluid dynamics plays a significant role in understanding the fate of droplets ejected from a susceptible individual during a respiratory event, such as coughing. Numerical simulations are employed here using an Eulerian–Lagrangian approach for particles and the Reynolds-averaged Navier–Stokes method for the background air flow. The driver is assumed to be exhaling virus laden droplets, which are transported toward the passenger by the background flow. A single cough is simulated for particle sizes 1, 10, , with motorbike speeds . It has been shown that small and large particles pose different types of risk. Depending on the motorbike speed, large particles may deposit onto the passenger, while smaller particles travel between the riders and may be inhaled by the passenger. To reduce risk of transmission to the passenger, a shield is placed between the riders. The shield not only acts as a barrier to block particles, but also alters the flow field around the riders, pushing particles away from the passenger. The findings of this paper therefore support the addition of a shield potentially making the journey safer.

Impact of Environmental and Health Risks on Rural Households' Sustainable Livelihoods: Evidence from China.

China has entered a “post-poverty alleviation” era, where the achievement of sustainable livelihoods by farmers has become a focus. This study used the China Family Panel Studies (CFPS) database, which was constructed based on an analysis of the DFID sustainable livelihood framework, and built a sustainable livelihood index system for farmers using the entropy weight method to measure the weights of sustainable livelihood indexes and calculate a sustainable livelihood index. This study used the Tobit model to discuss the impacts of different types of risk on the achievement of a sustainable livelihood by farmers. The results showed that environmental risk, chronic disease risk, and major disease risk all had significant negative impacts on the ability of farmers to achieve a sustainable livelihood. The impacts of major disease and chronic disease risks on the achievement of a sustainable livelihood by farmers living in plain areas were stronger than those associated with environmental risk. In China, the environmental risks were complex and diverse and were the most important factors that affect the achievement of a sustainable livelihood by rural households in mountainous areas. Chronic disease risk was also an important adverse factor that affected the achievement of a sustainable livelihood by rural households in mountainous areas.