This paper investigates the effect of economic policy uncertainty (EPU) on the systemic risk of the fintech industry. To achieve this goal, we first estimate the evolution of system-wide systemic risk using the CatFin method. We further examine whether EPU significantly affects systemic risk. Our findings demonstrate that the systemic risk of the fintech industry is time-variant and sensitive to major crisis events. Systemic risk tends to increase after major crises, especially the outbreak of the COVID-19 pandemic. EPU has a considerable impact on systemic risk, notably during periods of turmoil.

This paper studies non-compliant firms with gender legislation and why some businesses are taking the risk of not binding the gender quotas. It is conducted on firms listed on the SBF120 index, after the introduction of the gender law of Copé and Zimmermann, in 2011.

Our findings show that gender diversity on advisory committees, unlike monitoring committees, is likely to decrease the non-compliance likelihood. Non-compliant firms have busy members, specifically among men and long-tenured CEOs who are serving in non-dual structures. Regarding women's profiles, non-compliant boards are prone to hire short-tenured and local female candidates. Finally, their financial and social performances are not damaged while their corporate risks are decreased. When penalties are not required against non-compliant firms, refractory businesses do not bear “real” costs.

Background: Bladder cancer (BLCA), particularly invasive BLCA, has become a medical burden worldwide as it is associated with recurrence and easy metastasis. There are specific differences in the expression of various miRNAs in tumor and normal tissues. Hence, miRNAs can be used as biomarkers for tumor diagnosis and prognostic evaluation. The current study aimed to predict the downstream target genes of BLCA-related miRNAs and explore their association with immune infiltration. Method: Data on BLCA-related mRNA and miRNA expression levels were downloaded from The Cancer Genome Atlas. Correlation analysis and Cox regression analysis were performed to validate the miRNA risk model. The infiltration of various immune cells should be compared to determine the distinct differences between the immunological microenvironment of the two risk groups. Results: A predictive framework of BLCA was established using the expression levels of two miRNAs. Cox regression analysis showed that the low-risk group had a better prognosis. Then, the target genes of miRNA were predicted, and the target genes were analyzed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Moreover, variations in immune cells and functions between the high- and low-risk groups were assessed. Conclusion: The prognostic features composed of two associated miRNAs (MIR-25, MIR-548AN) may help predict the overall survival of BLCA.

The aim of this article is to model a negotiation between shareholders in high-technology-risk industries and local residents on the safety investments to be implemented. The methodology used is a Nash bargaining model, with a DE curve representing shareholders' dividend demands and an NS curve representing the safety demands of local residents' associations. The model is used to determine the level of safety investment required. One of the main results is that the estimation of a higher accident risk is accompanied by both a higher safety investment and a higher dividend payout. The most obvious implication of this result is that it is undoubtedly necessary to give greater weight to local residents in investment decision-making, in order to improve the well-being of all stakeholders.

Background: Hepatocellular carcinoma (HCC) stands out as one of the most lethal cancers globally, given its complexity, recurrence following surgical resection, metastatic potential, and inherent heterogeneity. In recent years, researchers have systematically elucidated the significance of long non-coding RNA (lncRNA) in the initiation and progression of HCC. The introduction of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases has significantly enhanced the prognostic assessment of HCC. However, the association between HCC and cell senescence has been infrequently explored in the literature. Method: We downloaded liver hepatocellular carcinoma (LIHC)-related messenger RNA and lncRNA expression levels from TCGA. Correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to validate the lncRNA risk model associated with cellular aging. Comparing the infiltration of diverse immune cells enabled the identification of distinct differences in the immunological microenvironments of the two risk groups. Subsequently, we conducted a real-time polymerase chain reaction (qPCR) experiment to confirm the accuracy of the selected lncRNAs. Results: A predictive framework for HCC was constructed based on the expression levels of five lncRNAs. Multivariate and univariate Cox regression analyses revealed that lncRNA signatures associated with senescence were independently correlated with an increased risk of HCC. Additionally, the nomogram also provides a more refined and sensitive model. Further investigation into the variations in immune cells and functions between the high-risk and low-risk groups was conducted. Subsequently, a qPCR experiment results revealed underexpression of AC068756.1, AC090578.1, AC145343.1, and LINC0022 in Huh7 and LM3 cells. In contrast, AP003392.4 did not exhibit a significant difference between Huh7 and control cells. Conclusion: The prognostic features and nomogram, consisting of five aging-related lncRNAs (AC068756.1, AC090578.1, AC145343.1, AP003392.4, and LINC00221), may be useful in predicting the overall survival of HCC.

Cloud computing is one of the fastest growing domains of the IT industry, however, the growth rates for each of the models on a global and local (Russian) scale have not been generalized, despite the obvious value of such analysis. Modern business and industry in Russia is going through another period of instability and at the same time is forced to follow the trend of digitalization. That is why a balanced scientific analysis and forecast of the development of cloud technologies is needed, as the main factor in improving business efficiency. The purpose of the study: is to review the main models of cloud services for modern business and industry, describing their capabilities separately and the prospects for the market as a whole. The materials for the study were analytical reports of leading consulting companies and materials from specialized web-sites. Result: The article considers cloud technologies as the main global technological trend, describes popular models of cloud services, their opportunities for business and industry. Russian and global leaders in the provision of cloud services are also described, the growth rates of these markets for each of the models are indicated. The most popular and promising cloud service models in 2022 are: UCaaS, CaaS, SaaS, IaaS, RPAaaS, PaaS. The cloud technology market will show strong growth until 2030, generating both hybrid and absolutely new service models. The private business, industrial and public sectors will increasingly move to cloud services. The main trends in the development of cloud technologies until 2030 are: hybrid cloud, artificial intelligence (AI) and cloud computing, deployment of cloud services in the planetary orbit. The results obtained are very valuable for analysts and industry experts. The above trend analysis provides valuable predictive data to research economists, investors, business and industry leaders and other stakeholders on how the cloud services market will grow in the next 5-7 years. The results of the study also have a general theoretical nature, substantiating the importance of further forecasting the development of this market (especially using mathematical methods).

This study empirically examines the influence of corporate financialization on trade credit financing, focusing on non-financial companies listed in China's A-share market from 2010 to 2022. The results indicate that as corporate financialization increases, companies will obtain less trade credit financing. Further incorporating moderating factors like market position and financing constraints, we find that a higher market position effectively mitigates the negative impact of corporate financialization on trade credit financing, whereas higher financing constraints exacerbate the adverse effects of corporate financialization on trade credit financing. Additional analysis shows that corporate financialization negatively affects trade credit financing by crowding out main business performance and increasing operational risks. Moreover, corporate financialization more strongly inhibits trade credit financing in state-owned companies.

Financial literacy seems to be more important and focused than ever. Several recent studies have found that Portugal is at bottom of the table compared to the Eurozone countries regarding financial literacy. As it’s a key factor in the development of a country, it appears to be crucial to understand what people know about financial matters when they complete compulsory schooling. With a sample of 296 Portuguese students who enrolled in the polytechnic higher education system for the first time, we studied if they understand simple concepts related to financial issues (such as loans), as well as whether they are aware of the risk of not recovering the money invested that is embedded in some of the most talked-about and common financial products that are available in the market. This last objective seems to be relevant since a lot of fraudulent schemes involving teenagers, young adults, and financial markets have emerged in recent years. From the results, some disturbing conclusions can be drawn. For instance, more than two-thirds of the sample do not know what Euribor is (similar result regarding Spread). About a third of the simple do not understand inflation’s consequences. 16,9% do not know what term deposits are, and derivative products and saving certificates are seen as very alike regarding the risk they represent. Students who chose a business-related course as their first choice when applying showed a higher level of financial literacy, although it is still low compared to what one would expect.

Since 2011, the conflict in Syria left the country with a devastating energy sector and fragile economy. The residents struggle daily to live with only two hours a day of electricity. The crisis encouraged some Syrians to assemble photovoltaic (PV) panels to generate energy. Unfortunately, the geopolitical risks, the inflation, and displacement are making the situation worse. The geopolitical risks are complex and multifaceted due to the ongoing war and the involvement of various regional and international actors. In this letter, we focus on the situation in war-torn Syria, its economy, and the opportunities for renewable energy development in the country. We also give some recommendations for academics and policy makers.

This paper examines the impact of COVID-19 on Small and medium-sized enterprises (SMEs) deposits across 13 African nations from 2016 to 2022, using a seven-year dataset and Ordinary Least Squares estimator. Notably, it uncovers a significant positive link between the pandemic and SMEs deposits, indicating heightened reserves amidst economic uncertainty, potentially driven by risk mitigation or government support. Associations between gross domestic product (GDP), inflation, unemployment, foreign direct investment (FDI), exchange rates, and SMEs deposits were evident, showcasing higher GDP aligning with increased deposits, while inflation and unemployment linked to reduced ones. FDI showed a positive influence, and exchange rate fluctuations notably affected SMEs deposits, especially for those in international trade. These findings emphasize policy reconsideration for crisis strategies supporting SMEs reserves during uncertainty and interventions addressing inflation, unemployment, and exchange rate risks. Future research exploring regional nuances and global comparisons could further enrich policymaking for resilient SMEs amid evolving economic landscapes.

The precise prediction of carbon emissions trading prices is the foundation for the stable and sustainable development of the carbon financial market. In recent years, influenced by a combination of factors such as the pandemic, trading regulations, and policies, carbon prices have exhibited strong random volatility and clear non-stationary characteristics. Traditional single-perspective prediction methods based on conventional statistical models are increasingly inadequate due to the homogenization of features and are struggling to adapt to China's regional carbon emissions trading market. Therefore, this paper proposes a multi-perspective fusion-based prediction method tailored to the Chinese market. It leverages carbon emissions trading information from key cities as relevant features to predict the price changes in individual cities. Inspired by the development of artificial intelligence, this paper implements various time series models based on deep neural networks. The effectiveness of the multi-perspective approach is validated through multiple metrics. It provides scientific decision-making tools for domestic carbon emissions trading investors, making a significant contribution to strengthening carbon market risk management and promoting the establishment and rational development of a unified carbon market in China.

The diplomatic relations between Azerbaijan and Pakistan have undergone significant development since the late 1990s. Despite some studies focusing on diplomatic and political relations, the economic dimension of this partnership has not been systematically covered. In this paper, a robust least squares (RLS) approach is used to model bilateral trade between the two countries and identify statistically significant determinants, including economic, institutional, and cultural factors, after analyzing the main economic and subsectoral trade dynamics of both countries. The results reveal that Azerbaijan's imports from Pakistan are significantly associated with the country's higher income and market size, while Pakistan's elevated exchange rate and trade costs hinder bilateral trade. In addition, Pakistan's rising manufacturing output increases exports to Azerbaijan but decreases imports from Azerbaijan. Among institutional determinants, government effectiveness, the trade freedom index (TFI), and political stability play significant roles in bilateral trade. Lastly, it was found that cultural proximity increases Pakistani exports to Azerbaijan but not imports from Azerbaijan. The analysis also indicates that domestic savings stimulate Pakistani exports. These findings underscore the complex nature of bilateral trade between Azerbaijan and Pakistan and highlight the need for institutional arrangements to harmonize trade flows and boost welfare gains from trade. The results may be of great importance to intergovernmental working groups, domestic policymakers, and businesses.

This paper explores the transformative journey from traditional e-commerce to the emerging realm of virtual commerce (v-commerce) within the metaverse, a collective virtual shared space created by the convergence of virtually enhanced physical reality and physically persistent virtual reality. The metaverse, with its immersive and interactive capabilities, is reshaping the landscape of economic activities, creating a paradigm shift in the way consumers shop, sell, and buy goods and services. The study delves into the impact of virtual reality (VR) technologies on consumer behavior, business models, and the overall economy. It investigates how VR is revolutionizing the shopping experience by offering immersive, personalized, and interactive platforms, thereby influencing con-sumer decision-making processes. The paper further examines the implications of these changes for businesses, particularly in terms of strategy, operations, and customer engagement. Moreover, the paper discusses the challenges and opportunities presented by the metaverse economy, including issues related to privacy, security, digital divide, and regulatory frameworks. It also highlights the potential of v-commerce to drive economic growth, innovation, and sustainability in the digital age. The paper concludes with a discussion on the future directions of v-commerce and the potential strategies for businesses to thrive in this new economic landscape.

Environmental concerns are increasing and business firms are inclined towards adoption of eco-friendly products and services. They are hiring employees via set of green HRM practices and struggling to become an environmentally sustainable firm. Pakistani food industry is booming day by day. However, less is known about the green HRM practices executed in the fast food industry of Pakistan. Therefore, this research is interested in examining the impact of Green recruitment and selection, green training and development and green performance and compensation management on the P-O fit, affective commitment and green recovery performance in Pakistan’s fast food industry. The moderating effects of transformational leadership will be examined between Green HRM practices and green recovery performance. A sample of 408 employees who are working at different designations were selected to accomplish the purpose of the research. These managers will be selected through convenient sampling technique. There were 21 fast food restaurants (Burger Joints) selected from all over Karachi, few of them includes; KFC, Burger Lab, Burger O Clock, Vintage, Plan B and more. The collected primary data will be tested through the application of structural equation modeling technique. Smart PLS software is used to assess the objectives. The results of the study revealed significant association between Green R&S, Green T&D and P-O fit. A non-significant association is found between Green P& C and P-O Fit. The study affirmed that Affective commitment posit a direct influence on GRP. The Green R&S and Green P&C revealed insignificant impacts on the green recovery performance within the fast food industry. The indirect association was analyzed between P&C, P-O fit, AF and GRP and revealed an insignificant result. Likewise, an indirect association is found between R/S, P-O Fit, AF and GRP. The future researchers are recommended to analysis the remaining elements of GHRM and investigate their impacts on the fast food industry of Pakistan. There is a need to create awareness regarding green HRM practices and their influence on the Green recovery performance in Pakistan. Policy makers are recommended to develop such policies that promotes GHRM in Pakistan.

This study analyzed whether the level of corporate governance of companies listed on the Brazilian capital market is related to the investment decisions of Brazilian pension funds. We start from the assumption that the corporate governance system mitigates the moral risk, that may arise in the relationship between corporate managers and investors and respective shareholders, Brazilian pension funds. Shareholding dispersion would enable opportunism for corporate managers, making decisions focused on their interests to the detriment of shareholders or investors. The governance system would signal that this behavior would be controlled, signaling safer behavior for investors. Thus, the hypothesis is that the level of corporate governance would attract pension funds that would understand this system as reducing investment risk. To test this, we used panel data, with a sample of 1,582 observations of companies listed on the Brazilian Stock Exchange (B3) from 2010 to 2017. The statistical results show that corporate governance positively correlates with investment in pension funds. This leads to the conclusion that, for Brazilian pension funds, companies' signaling about their corporate governance practices is a risk-mitigating factor. Furthermore, these results allow us to infer that the company's governance level associated with leverage is a differentiating signaling element as the evidence points to a positive relationship.

In this study, the time-varying pattern of returns with the trading cost is assessed in light of sanctions on the Russia’s economy. The analysis is performed on the Moscow Exchange Index (MOEX) using the ordinary least squares (OLS) method, Bayes’ Theorem technique, and vector error correction model (VECM). Firstly, the transparency of asset’s value in the same trading period was noted to execute the trade with a limited price impact. Thus, the liquidity seems not priced in returns. In addition, the posterior probability of the transparent asset’s value stabilized the market at a limited transaction cost. In this case, there is less likelihood of liquidity acting as a risk element in returns during the same trading session. These results correspond to the era without sanctions, as well as economic restrictions period. Before the economic restrictions, the execution of investment occurred on its real or close value due to the market transparency in the following trading period. This implies, that the past trading cost series is not priced in yields on investment. During the Russia-related sanctions, a higher price impact of transaction was noted due to the ambiguity in the future asset’s value. Therefore, the past liquidity series is a pricing element in the short run and long run. The analysis suggests a potential inference of trading cost to determine the yield on investment.

Liquidity and its associated issues are one of dominant strands in the market microstructure. In this study, microblogging-based behavioral perspective on economic unrest is linked to the market liquidity. The concept of liquidity is examined in terms of price dispersion relative to the quantity traded. The analysis contains the quantification of multiple linear regression, Gaussian distribution technique, and vector error correction methodology. In the economic stability period, the investor’s mood, either in positive manner or pessimistic context, had an influential role on the price impact volume-based liquidity. Meantime, the probability was higher for occurrence of price impact volume-based liquidity in response to the sentiment indicators. In the economic unrest environments, the positive bias investor’s mood was not vigorous enough to influence the dispersion of asset’s prices and trading quantity. Most importantly, the negative bias investor’s emotion was linked to increase the dispersion of asset’s prices relative to the quantity traded. Investors with a lower amount of trading quantity had declined the liquidity in the market. Additionally, there was a higher probability for occurrence of illiquidity in the pessimistic market periods. However, changes in past sentiment series were not associated with changes in pervious liquidity series, either in short run or long run. The findings may be potentially applicable to manage the behavioral perspective of liquidity risk.

Gold has been traditionally well recognized as a safe heaven for financial markets. Lately, Bitcoin has been gradually considered as a popular alternative. Since the outbreak of COVID-19 in early 2020, it has become even more necessary and critical to examine the diversification capability of them to hedge financial risks associated with an unexpected crisis comparable to the pandemic. This paper hence employs the wavelet analysis, complemented by the multivariate DCC-GARCH approach, to measure the coherence of the gold and Bitcoin prices with six representative stock market indices, three for developed economies and three for emerging economies, all of which are heavily affected by the pandemic. To have a more balanced and comprehensive analysis, two-year data are used, spanning from 12th April 2019 to 15th April 2021, which covers approximately one year before and one year after the announcement of the COVID-19 pandemic. The results suggest that the returns of both gold and Bitcoin are generally not strongly correlated with the market returns of all six indices, particularly for short-term investment horizons. That is, investors in all six indices can benefit through gold, as well as Bitcoin, in terms of hedging. Meanwhile, compared with Bitcoin, gold shows to be less correlated with the indices, particularly for long-term investment horizons. The findings hence suggest that gold and Bitcoin offer diversification benefits to investors in the market indices during a crisis such as the COVID-19 pandemic, especially for short-term investment horizons. The study also reminds policymakers thinking beyond the pandemic about the future of the earth, including air pollution and health, for sustainable development of the whole world.

We analyze the annual microdata of China's 100 commercial banks from 2007 to 2018 using the mediating effect analysis method, analyze the negative impact of economic policy uncertainty on the credit scale of commercial banks, and then verify the intermediary effects of the operational risks and short-term capital liquidity of commercial banks in the impact of economic policy uncertainty on the scale of commercial bank credit, separately. Moreover, we find that non-state-owned commercial banks, large-scale commercial banks, low-leverage commercial banks, and commercial banks with low profitability are more susceptible to economic policy uncertainty affecting commercial bank credit growth through short-term capital liquidity, and vice versa.

Many startups look for venture capital (VC) funding to grow their business. Anecdotally, in the Southeast Asia context, startup founders who attended an elite institute of higher learning have greater access to this kind of capital, but this has not been demonstrated quantitatively. We look at a dataset of nearly 800 startups in Southeast Asia who have received VC funding in the last 5 years and look for any correlation between the founder's educational background and the amount of VC funding received. We find that founders who have obtained a postgraduate degree from an elite university receive significantly more VC funding than those who graduated from other universities. Furthermore, this effect is only seen at later stages of funding, not at the seed stage. Potential reasons for this effect could be from stronger signaling of business acumen or technical skill; or better access to funding networks.