The global financial crisis has induced a series of failures of most conventional banks. This study investigates the main sources of banking fragility. We use a sample of 49 banks operating in the ...MENA region over the period 2006–2013 to analyze the relationship between credit risk and liquidity risk and its impact on bank stability. Our results show that credit risk and liquidity risk do not have an economically meaningful reciprocal contemporaneous or time-lagged relationship. However, both risks separately influence bank stability and their interaction contributes to bank instability. These findings provide bank managers with more understanding of bank risk and serve as an underpinning for recent regulatory efforts aimed at strengthening the joint risk management of liquidity and credit risks.
•Our study is the first that deeply compare bank credit system of France and Germany.•This paper presents a comparative study of all factors contributing to banking credit risk.•We propose a ...methodology combining bank-specific variables and macroeconomic variables.•The paper considers two different categories of determinants, explicitly macroeconomic (systematic) and microeconomic (no-systematic).
This paper applies a dynamic panel data approach to examine the determinants of non-performing loans (NPLs) of commercial banks in a market-based economy, represented by France, compared with a bank-based economy, represented by Germany, during 2005–2011. The paper is motivated by the hypothesis that macroeconomic and bank-specific variables have an effect on loan quality, and that these effects vary between different banking systems. The key question discussed is which credit risk determinants are important for both countries. The results indicate that except for the inflation rate, the set of macroeconomic variables used in the paper influence the NPLs of both economies. This result is explained by the fact that both economies belong to the same euro area. Additionally, our study finds that compared to Germany, the French economy is more susceptible to bank-specific determinants. This highlights the impact of the type of economy (bank-based or market-based) on credit risk.
This paper carried out a hybrid clustering model for foreign exchange market volatility clustering. The proposed model is built using a Gaussian Mixture Model and the inference is done using an ...Expectation Maximization algorithm. A mono-dimensional kernel density estimator is used in order to build a probability density based on all historical observations. That allows us to evaluate the behavior’s probability of each symbol of interest. The computation result shows that the approach is able to pinpoint risky and safe hours to trade a given currency pair.
Purpose This study aims to test the contagion effect of the Tunisian revolution on the Egyptian stock market. Thus, the purpose of this research is to distinguish the contagion effect from the simple ...interdependence between these markets. Design/methodology/approach This paper examines the contagion hypothesis between Tunisia and Egypt during the Arab Spring, using a DCC-MGARCH model to capture time-varying contagion effects and dynamic linkages in stock markets. Therefore, to identify the contagion effect from the simple interdependence, the authors apply the pure contagion test developed by Forbes and Rigobon (2002). Findings The findings indicate a contagion effect, as the EGX 30 index exhibited similar changes, positive or negative, as the Tunindex index during the period of the Tunisian revolution. Moreover, the analysis demonstrates the presence of an interdependence between the Tunisian revolution and the Egyptian market, emphasizing the interconnections between these two economies. Practical implications The findings provide investors with a better understanding of financial market dynamics in times of major political unrest, notably on the Tunisian and Egyptian markets. By understanding the contagion effect of the Tunisian revolution on the Egyptian stock market, investors can further explore the complexities of these markets in times of financial crises, which can help mitigate losses and identify strategic investment opportunities. Originality/value This study makes two significant contributions to the field. First, it addresses the scarcity of research specifically focused on the contagion effect during the Arab Spring, aiming to fill this gap by testing the contagion effect of the Tunisian revolution on a nearby market. Second, it extends the contagion test of Forbes and Rigobon (2002), which associates “pure” contagion with a significantly higher correlation between markets during a crisis.
The paper focuses on the degree to which the accounting treatment of R&D expenditure is stock price informative followingthe adoption ofIAS. Therefore, using recent data of French listed companies, ...starting from the year in which IFRS were applied, 2005-2015, the present study examines the value relevance of the different R&D accounting treatments. Unlike evidence regarding the pre-IFRS period in France, we find that the capitalized portion of R&D is not correlated with market values, suggesting that under IFRS mandatory implementation, R&D assets are not value relevant. The expensed portion of R&D is positively related to market values only for manufacturing companies. Accordingly, we conclude that IFRS implementation has implications on the valuation of R&D expenditure by investors in French firms.
Aims and background
Pests and diseases of plants often threaten the availability and safety of plants for human consumption. To face these challenges, a new agricultural revolution is underway ...(agriculture 4.0). This agrarian revolution dramatically benefits from new digital technologies and artificial intelligence (AI).
Methods
The farmers need a reliable tool for an early disease diagnosis. Imaging is a promising technique for diagnosing and quantifying the disease plot. Easily automated and non-intrusive, imaging allows, with low costs in instrumentation and human resources, to account for much agricultural priority’s local mics on large production areas. The main purpose paper is to develop a hybrid model for tomato disease detection based on image data collection. We apply transfer learning and fine-tuning strategies to improve the performance of different pre-trained models. Two models have been selected to develop our hybrid model for plant disease identification among these CNN models. We used the plant village dataset, which contains nine classes of tomato diseases.
Results
First, we evaluate the performance of seven different architectures including VGG16, ResNet50, EfficientNetB0, EfficientNetB1, EfficientNetB2, EfficientNetB3 and EfficientNetB4. We applied the transfer learning technique. Then, the best two pre-trained models were selected and used to implement a weighted average ensemble. The proposed model achieves an accuracy of 0.981.
Conclusion
Many diseases can affect tomato plants and cause yield losses. Therefore, plant pathogens should be given more importance. Furthermore, this study can be adapted to cover other types of crops in future research.
Although the fifth‐generation (5G) is not yet officially launched, researchers worldwide have turned to the sixth‐generation (6G) communications system. The 3G has opened the gap to fourth‐generation ...(4G). It will be the same for 5G, which will facilitate the path to 6G. The technology 5G provides a high‐level infrastructure enabling various technologies such as autonomous cars, artificial intelligence, drone networking, mobile broadband communication, and, most importantly, the Internet of Things (IoT) and the concept of smart cities. We are, therefore, in the middle of the fourth industrial revolution (Industry 4.0). However, as new technologies gain traction, networks become increasingly complex and difficult to pin down to keep networks operating at the level prescribed by evolving services. The ultimate goal of 6G is to move from the concept of the Internet of intelligent things to the new idea of the intelligent Internet of intelligent things. This article shows the features and tools of 6G technology that will help meet these traffic needs. Besides, we highlight the main feature of the 6G, in terms of architecture and services, scheduled as recommended by the International Telecommunications Union (ITU) in its current technical specifications and discussions on the latest research in this area.
Compared with 5G technology, the future 6G technology is expected to allow even higher throughputs, even shorter latency times, greater component density, and the mass integration of artificial intelligence in all segments constituting the network. As we move toward the next‐generation 6G mobile radio, many challenges will need to be fully mastered concerning the individual components and their interactions. For example, the future 6G wireless network will consist of a large number of small mobile radio cells within which large amounts of data can be transmitted quickly and in an energy‐efficient manner.
The main objective of this article is to analyze and compare the impact of political uncertainty and financial crises on stock market volatility in 10 MENA countries over the period 2005–2018. To ...test our hypothesis, a variety of GARCH models are used. The results indicate that political events have more significant effect than financial crises on stock market volatility, as we detect an increase in market volatility during political elections and terrorist attacks. The comparative tests employed to identify the best GARCH model in capturing stock markets volatilities reveal that GARCH/EGARCH models perform the best in our study. EGARCH model is more suitable during unpredictable events while GARCH model work well during predictable events. Additionally, we found that the reaction of investors is not similar during the three events studied. In fact, terrorist attacks admit a more significant effect than political election periods. We observed that the reaction of the stock market during expected events is not instantaneous, whereas it is instantaneous during unexpected events. Overall, our findings are of great significance for investors and market regulators in understanding the role of major events on stock market stability, particularly in MENA region.
Purpose
The aim of this study is to conduct a comparative analysis between Islamic and conventional banks in terms of whether Islamic banks was more or less resilient/risky than conventional ...counterparts to the pandemic shock. It also examines the role of capital in improving the performance and stability within the two banking systems.
Design/methodology/approach
This study uses 82 banks from MENA (Middle East and North Africa) region for periods across 2011–2020, and employs a dynamic panel data approach to examine the resilience within both banking systems during the Covid-19 pandemic.
Findings
The results show that the Covid-19 pandemic has a negative impact on conventional banks' stability. However, Islamic banks performed better and were less risky than conventional ones. Banks with high-quality capital are more effective at controlling their risks and improving their performance during the pandemic.
Practical implications
The results offer important financial observations and policy implications to many stakeholders engaging with banks. Actually, the findings of this study facilitate to the stakeholders and bankers to have an alluded picture about determinants of risk and performance. The results can be used by bankers’ policy decision-makers to improve and enhance their consideration for risk management, taking into consideration the type of banking systems.
Originality/value
Compared to the various studies on the stability of Islamic and conventional banks, researchers have not sufficiently addressed the effect of the Covid-19 pandemic on risk and performance. Moreover, none of these studies has examined if Islamic banks was more or less resilient/risky than conventional counterparts to the pandemic shock. This leads the authors to identify the similarities and differences between two types of banks in the MENA region in a pandemic shock context.
The growing literature on credit risk determinants provides results that are based on the set of bad loans present in the bank's assets especially non-performing loans. Besides this classic proxy, ...the present paper examines the determinants of loan quality deterioration by using a qualitative measure. Actually, we take advantage of a detailed dataset containing information on the quality of loans contracted by banks to different Tunisian firms. The study aims to detect if credit risk determinants are different through quantitative and qualitative proxies. We take into account bank-specific indicators that are likely to affect banking credit risk. Overall, the results show that cost inefficiency, bank profitability is common determinants of the credit risk level and the loan quality deterioration, that are differently influenced by bank size and capitalization.
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