This paper examines the regulation of corporate governance on leverage structure decision-making in Bangladesh from 2003 to 2017. Appropriate panel methods are employed to control the problems of serial correlation, heteroskedasticity, and the cross-sectional nature of manufacturing companies. The study finds that corporate governance attributes such as board size, managerial ownership, and duality are the dominant factors for leverage decision-making. The results also indicate that control variables such as firm size and profitability have an influential role on leverage decision-making in Bangladesh. Our findings substantiate the idea that political and family connections to corporate governance structure greatly influence the leverage decision-making of corporate firms in Bangladesh. Int. J. Financial Stud. 2019, 7, 50 2 of 16 weak corporate governance, such as family issues, institutional issues, political affiliation, corruption, and the lack of a sense of responsibility and accountability. In this circumstance, financial managers cannot freely make optimal financial decisions in terms of firm value and sustainability. Weak financial decision-making incurs a great deal of loss, which threatens sustainability. The previous studies also consider only primary data, and, to the best of our knowledge, they did not consider the main corporate governance attributes of board size, board composition, board independence, managerial ownership, institutional shares, and CEO duality from secondary data. Hence, the relationship between corporate governance and leverage structure decision-making in Bangladesh has not been fully explored. In this respect, in Bangladesh, there is an urgent need to determine whether corporate governance has any impact on leverage structure decision-making or not.We have investigated the manufacturing sector for several reasons: First, past literature has been primarily dedicated to the analysis of developed countries and there are very few studies focused on developing countries such as Bangladesh. Second, Bangladesh has been experiencing embezzlement in capital markets resulting from political weaponry and government intervention. These consequences radically affect the financial decision-making of manufacturing companies in Bangladesh. Third, the manufacturing sector provides the basic needs of people and fuels economic growth in Bangladesh, and it is highly vulnerable due to a lack of high-quality corporate governance. Poor accounting and auditing standards, bad accountability, low transparency, managerial inefficiency, and political turmoil (Pontines and Siregar 2008) have led to the poor sustainable development of the sector.The major contributions of the paper are designed to add new insights to the current literature: (i) The previous literature on this subject in Bangladesh is few and partial. To the best of our knowledge, research in this area was initiated by Haque et al. 2011 on the qualitative factors of corporate governance in Bangladesh. The most influential variables for c...
The heart of this study is particularly on risk assessment of financial decision support systems (FDSSs), to advance the model performance and improve classification accuracy. To conquer the downsides of the classical models, statistical intelligence (SI) technologies, for example, multilayer perceptrons (MLPs) and support vector machines (SVMs), have been deliberated in FDSS applications. Recently, the prestigiousness of SI approaches has been confronted by the latest prediction learners. Therefore, to ensure the competitive performance of SI mechanisms, the current investigation scrutinizes the topological applications of MLPs and SVMs over eight different databases with equivalent combinations in credit scoring and bankruptcy predictions example sets. The experimental results reveal that MLP5‐5 and MLP4‐4, that is, the sigmoid activation function with five and four hidden layers, are the feasible topologies for the MLP algorithm, and on all databases in all performance criterions, SVM trained with the linear kernel function (SVM‐1) achieves better prediction results. From the “Baseline” family, random forest learner brings significant improvements in financial decisions. Lastly, FDSSs are found to be correlated with the nature of databases and the performance criterions of the trained algorithms. The results of this study, however, have practical and managerial implications to make a range of financial and nonfinancial strategies. With these contributions, therefore, our study not only supplements earlier evidence but also enhances the predictive performance of SI algorithms for financial decision support applications.
The paper aims to examine the impact of leverage structure dynamics on firm value in Bangladesh. To this end, the panel techniques (GMM and PCSE) were used to control for serial correlation, heteroskedasticity, and cross-sectional difficulties in the panel data set. The paper found that leverage structure influences firm value. The result also supports the trade-off theory, which asserts that tax savings on interest expenses result in a lower total cost of capital and ultimately upturn firm value. Lastly, the paper highlights the significance of endogenous variables such as liquidity, profitability, tangibility, and tax rate on firm value in Bangladesh.
More than two decades, capital structure decision marked as variation from optimal decisions as determinants are not properly considered due to the collapse of corporate governance. This study examines the impact of determinants on capital structure decisions in Bangladesh using Fixed-Effect Model (FEM) and Panel Corrected Standard Error (PCSE). The study revealed that debt structure is considerably influenced by liquidity, firm size, asset structure, non-debt tax shield, and operational age of companies. The study also indicates that the companies, which are not financially, sound, but used more debt because the owners of such companies are politically empowered in stock market. The firms that hold less fixed assets (as a percentage of total assets, particularly the family-run and politically affiliated firms used more debt regardless of their tax bracket, profitability and growth—showed a greater capacity for increased debt. This study primarily focused on financial framework to make capital structure decision based on related determinants.
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