This paper empirically assesses the relationship between Deposit Insurance Funds (DIF) and the quality of risk assets of listed Deposit Money Banks (DMBs) in Nigeria. The entire fifteen listed DMBs in the country as of 31st December, 2017 were focused on and the secondary data were subsequently sourced from the yearly financials of the Nigeria Deposit Insurance Corporation (NDIC) for a 29-year period covering from 1989 to 2017. The Auto-Regressive Distributed Lag (ARDL) and the Vector Error Correction (VEC) estimation techniques were the basis of estimating the relationship between the variables of interest in this study. Evidence from our analyses indicates that the volume of total deposits and total loans and advances of DMBs have long run negative and statistically significant relationship with DIF. Conversely, the quality of risk assets of DMBs exhibits a positive and insignificant relationship with the target reserve ratio of DMBs. The study thus recommends that regulatory agencies in the banking sector (CBN and NDIC), amongst others, collaborate with listed DMBs to diversify and manage their risk assets by strategically intensifying the implementation of existing measures aimed at minimising incidences of loan default and the alarming levels of non-performing loans in the portfolio of Nigerian DMBs.

For understanding the place of income in smartphone diffusion, this paper aims to find out the dependence of smartphone market indicators on income level worldwide and in the developing economies. The strength of the relationship between above mentioned variables identifies the speed of smartphone diffusion influenced by income. For current purposes, secondary data from 189 countries were analyzed by using Hierarchical Cluster Analysis and Chi-square analysis. The results confirmed that income level influences smartphone purchase and diffusion. However, the strength of the relationship between income and smartphone market indicators is diverse globally and in developing countries. In developing countries, the strength of the relationship is smaller in comparison with the overall results. It means that income level has weak moderating effect in smartphone diffusion, and it cannot be considered as a key indicator of smartphone diffusion in developing countries according to results of the analysis in 2016 and the arithmetic mean of 2013-2017 years.

This paper gives insight about the association between market orientation, entrepreneur orientation, learning orientation, technological orientation and access to finance, and SME’s performance in Indonesia. The study provides a clear understanding about the relationships among SME’s performance in Indonesia and market orientation, entrepreneur orientation, learning orientation, technological orientation, and what mediating role financial access plays in this relationship. The study broached that it is apparently essential to identify the strategic variables which may reflect the aforementioned management activities or processes, such as marketing, innovativeness, risk taking, technology and learning culture, which SMEs use and that probably influence their performance. The study is among the pioneering studies on the issues related to the market orientation, entrepreneur orientation, learning orientation, technological orientation, and access to finance in Indonesia. The study uses SEM-PLS as statistical tool to answer the research questions raised in this study and research objectives envisaged in the current study. The findings of the current study have provided support to with the hypothesized results. The study has argued that to deal with the current external opportunities and menaces, new knowledge and skills for improving their existing and future performances must be provided for the organizations. The study will be helpful for policymakers and researchers in examining the link between market orientation, entrepreneur orientation, learning orientation, technological orientation, and access to finance in Indonesia performance of SMEs in Indonesia.

In today's dynamic business landscape, the audit profession encounters numerous obstacles, particularly in adapting to the necessity of computer-assisted audits due to the immense volume of data requiring scrutiny. Despite the emergence of different digital auditing tools, there is a gap in research regarding the level of adoption, and its effects on the quality of audit services especially in the context of developing countries. This study seeks to investigate the impact of digitalization of audit tasks on the quality of audit services of accounting firms in Nigeria. The study, which has its foundation on the Technology Acceptance Model (TAM) integrated with the Technology, Organization, and Environment (TOE) framework, adopted the survey research design. The population of study was made up practitioners of accounting firms in Abuja and Lagos, Nigeria. A self-designed questionnaire was used as a tool for data collection for the study. Findings of the study indicate that automation of audit tasks enhances the quality of audit services suggesting that adopting IT infrastructures leads to more reliable audit procedures, improved efficiency and accuracy, as well as mitigating audit risks. Results also revealed that Big Four auditors are significantly ahead in the adoption of digital technologies compared to the non-Big Four auditors, confirming the dominance of larger accounting firms in application of emerging technologies in performing audit tasks.

Research on stock exchange markets is essential to stock market investors as it offers sensitivities to risk management. This research investigates the patterns of the volatility of stock market prices in ten African stock markets. We estimated the dynamic GARCH model of Engle using the method of maximum likelihood estimation. Daily time series from January 1, 2021 to December 30, 2022, were obtained from African Stock (Securities) Exchange database. The findings established the existence of a normally distributed Senegalese stock market as against time-varying volatility of stock prices in Nigeria, Ghana, Mali, Burkina Faso, Togo, Niger Republic, Benin Republic, Ivory Coast, and Gambian. Hence, the likelihood that an asset or stock is being overpriced (overvalued) or underpriced (undervalued) in the Senegal stock market is low. It is therefore easier for stock traders and investors in Senegal to pick entry and exit points. Unfortunately, this cannot be said of the investors in stock markets of other countries. In effect, the closing price of a stock is most often heavily deviated with significant outliers. This further infers that variations of stock prices in these markets are very wide, heavy, and unpredicted. Hence, it is a case of the volatility of volatilities.

This paper analyses the causal relationship between Foreign Portfolio Investment (FPI), Equities Market Volatility, Exchange Rate and Inflation in Zimbabwe using a monthly time series data between October 2018 and November 2021. The granger causality model was used to present the link between the variables, and EGARCH was used to account for volatility and asymmetric effects on the variables. To incorporate innovations and responses into the Granger model, impulse response functions were used. Links between exchange rate and foreign portfolio investments were found. This only suggests that exchange rate volatility will vary when overseas investors purchase and sell financial securities on the Zimbabwe Stock Exchange (ZSE). In contrast, foreign investors sell local financial securities when local stock market returns are negative, leading to a significant outflow of foreign portfolio investment thereby reducing demand for currency. A significant causal relationship was found between the volatility of the exchange rate and stock market returns. It is assumed that stock market returns, and foreign portfolio investments are caused by fluctuating currency rates. The relationship between exchange rate and ZSE returns, and inflation was found based on Granger causality. This implies that stocks are not suitable for long-term investments that compensate investors for their diminished purchasing power. Policy makers should advise the Zimbabwe Stock Exchange to recommend a reduction in capital gains tax and withholding tax and this encourages investors to hold local equities for a long time.

This research aims to enhance portfolio selection by integrating machine learning regression algorithms for predicting stock returns with various risk measures. These measures include mean-value-at-risk (VaR) variance (Var), semi-variance mean-absolute-deviation (MAD) and conditional value-at-risk (C-VaR). Addressing gaps in existing literature. Traditional methods lack adaptability to dynamic market conditions. We propose a hybrid approach optimized by genetic algorithms. The study employs multiple machine learning models. These include Random Forest, AdaBoost XGBoost, Support Vector Machine Regression (SVR) K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN). These models are used to forecast stock returns. Utilizing monthly data from the Tehran Stock Exchange, the results indicate that the genetic algorithm prediction model combined with mean-VaR, Var semi-variance and MAD, produces the most efficient portfolios. These portfolios offer superior returns with minimized risk compared to other models. This hybrid strategy provides a robust and efficient method for investors aiming to optimize returns while managing risk effectively. To implement this approach successfully it is crucial to balance investments. This involves both traditional and alternative asset classes, ensuring diversification. It also capitalizes on market opportunities. Regular review and adjustment of fund allocation are essential. Maintain an optimized strategy for maximum returns and minimal risk.

This article introduces a comprehensive analysis of 20 leading companies, scrutinized through their financial metrics across various sectors. By deploying multi-criteria decision-making (MCDM) techniques, we aim to offer investors a clear and objective perspective on which companies stand out as the best investment options. Among the MCDM techniques, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is utilized, renowned for its efficiency in handling complex decision-making scenarios which is conducted by two clauses. 1) Implementing TOPSIS with assigning equal weights and same share to every chosen metrics as criteria and 2) employ BWM (Best Worst Method) to calculate these weights base on their significance and relevancy to the prosses of ranking. According to the Result gained from the computation, ranks 1 to 5 belong to the similar companies with both assumptions which are Ford Motor Co, BP plc, Tesla Inc, General Motors Co and Exxon Mobil Corp. The consistency in rankings across two different weighting assumptions highlights the robustness of the criteria used, ensuring stable and reliable outcomes. This enhances the credibility of the findings, making them more trustworthy and citable for those who seek reliable and robust methodologies for informed investment decisions.

Solution for a normally loaded infinite isotropic plate containing five cracks with coalesced yield zones is obtained using a complex variable method. Influence of coalesced yield zones on the load bearing capability of the infinite plate is analyzed. Analytical expressions for stress intensity factors, displacement components and crack opening displacement (COD) are obtained. Numerical study is carried out to determine the yield zone length, applied load ratio and COD. The numerical results are reported graphically between some important parameters.

The present work aims to investigate the effect of an edge crack on the stress concentration around the circular hole surrounded by Functionally Graded Material (FGM) in an infinite plate subjected to uniaxial tensile load. The numerical investigation has been carried out using Extended Finite Element Method (XFEM). Two cases have been analysed in this work, i.e. the whole plate made up of radial FGM and homogeneous material plate having radial FGM layer around the hole. Young’s modulus of FGM varies according to exponential and power law function. The relations of stress intensity factor (SIF) and stress concentration factor (SCF) with normalised crack length, Young’s modulus ratio, FGM layer thickness and power law index have been presented. It has been observed that the FGM layer case has low SCF around hole than FGM plate case in presence of an edge crack.