Firm value shows the performance of a firm while reflecting the present value of the firm’s future cashflows, hence affecting investment decisions. Therefore, this paper explores the relationship between asset structure, leverage, and firm value of 51 listed companies between 2010 and 2019 using secondary data collected from audited financial statements. The study applies panel data regression models and the causal-comparative research design. The quantitative data are analyzed using multiple regression. The result shows that plant, equipment, property, current, and financial assets influence the firm value positively. Nonetheless, the quotient of current to total assets was reported to yield the highest beta coefficient, implying that significant firm value creation is realized for every additional current asset held, weighed against the quotient of additional equipment, property, and plant to the value of total assets. Leverage had an insignificant influence on the value of firms, implying that no maximization of value is attainable in manufacturing firms through the astute use of borrowed funds. The study recommends that finance pundits consider firms’ asset structure and the use of borrowed funds when formulating financial and investment policies. The study enriches the scholarly world by developing a model for establishing the value of listed firms.

Purpose: This study analyzes the effects of competition and risk-taking behavior on the stability of commercial banks in Kenya.Design/methodology/approach: An unbalanced panel dataset of 36 licensed commercial banks in Kenya for 2001–2020 was extracted from the published financial statements. A dynamic panel data analysis model, a two-step system generalized method of moments (GMM), was employed.Findings: The results indicate that competition reinforces bank stability, whereas banks’ risk-taking behavior has an inverse relationship with strength.Practical implications: The study confirms the competition-stability nexus, implying that measures may be implemented to foster competition among banks with reduced concentration. These measures may include, but are not limited to, reduced entry barriers and optimal capital requirements. Second, efforts should be made to ensure excessive risk-taking by banks. Employing an elaborate exposure monitoring system with clear warning signs is recommended.Originality/value: This study is unique in several ways. First, it employs structural and nonstructural measures of competition and ex post standards of banks’ risk-taking behavior. Second, contrary to past studies, this study uses various firm-level measures of bank stability. Lastly, it provides essential empirical evidence from the context of a developing economy, whose institutional and macroeconomic environments differ significantly from those of a developed economy.

Purpose: The paper investigates the effect of ownership structure on the financial distress of firms listed in sub-Saharan Africa.Design/methodology/approach: Using secondary data from 106 non-financial firms listed in 9 selected SSA countries from 2016 to 2021, the research using paired t-tests and conditional logistic regression model analysed a sample of 174 distressed observations matched with 174 non-distressed observations.Findings: T-tests determined significant differences between distressed and non-distressed groups concerning institutional, foreign, and local ownership. Conditional logistic results established that institutional, foreign, and state ownership significantly reduce distress. However, managerial ownership does not influence financial distress while a significant positive relationship is observed between local ownership and financial distress.Originality/value: This is the first study to investigate the influence of ownership structure, including local ownership, on financial distress in SSA, employing a unique methodology of matched design and conditional logistic regression analysis. Furthermore, the paper presents cross-country evidence from emerging frontier markets, highlighting the importance of governance frameworks in firms’ stability.

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Purpose: The aim of this paper was to evaluate which of the seven GARCH-type models, namely sGARCH, IGARCH, EGARCH, TGARCH, GJRGARCH, APARCH, and CGARCH, was suitable for predicting the Nairobi Securities Exchange-listed firms' volatility. Theoritical framework: The Efficient Market Hypothesis is crucial in predicting market value of stocks. Therefore, this study employed the efficient market hypothesis to the the predictability of the stocks returns volatility. Design/Methodology/Approach: In this study, we used census approach to collect data from 49 Nairobi Securities Exchange listed firms. The data was collected from 1st January 2011 to 31st December 2020. TO evaluate the volatility, we used the GARCH-type models. Findings: The study found that the APARCH model as the best suitable for forecasting the volatility of Nairobi Securities Exchange-listed firms. Research, Practical & Social implications: We propose the the APARCH model as the best suitable model for predicting volatility of stock returns. The findings can be used by investors in making judicious financial decisions. For acedmic purpose, the findings are essential in supporting new knowledge of which model is best fit in predicting the NSE stocks returns volatility. Original/ Value: The study contributes to the literature on the best suitable model in predicting the volatility of the stocks returns.

Purpose: The study evaluates the influence of human capital efficiency (HCE) and market power on bank performance.Design/methodology/approach: The study employs two measures of bank performance: profitability and stability. Unbalanced panel data of 35 banks operating in Kenya for 2005–2020 collected from published financial statements is utilized. The study employs the feasible generalized least squares (FGLS) method in the analysis and the two-step system generalized method of moments (GMM) for robustness check.Findings: The study affirms an inverted U-shaped relationship between market power and bank performance. The effect of market power on bank profitability is enhanced when a bank has highly efficient human capital. Further, HCE significantly impacts bank stability for banks with low HCE. Interestingly, a further increase in HCE narrows the net interest margins for banks with high HCE, conferring welfare benefits to customers as interest rate spreads shrink.Practical implications: This study provides important insights into the role of human capital in bank performance. First, banks ought to invest in promoting HCE through training and development. As regulators root for bank consolidation, attention to HCE is imperative for fostering profitability and stability.Originality/value: The study fills an essential gap in the literature by evaluating the effect of firm-level market power on bank performance in an emerging market. We adopt a novel stochastic frontier estimator to generate the Lerner index. Further, this is the first study known to the authors to evaluate the effect of market power on bank performance in the context of human capital efficiency variations.