• The Journal of Asian Finance, Economics and Business
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• v.3 no.4
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• pp.25-37
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• 2016

This study aims to investigate the determinants of dividend payout of Oil and Gas industry of Pakistan using secondary data from published annual reports from 2008 to 2014 listed on KSE (Karachi Stock Exchange). Dividend payout can be affected by profitability, firm size, financial leverage, sales growth, investment opportunities, liquidity, business risk, and ownership structure. Panel data technique used due to panel characteristics of available data with ordinary least square regression model to find out the impact of set of explanatory variables on the dividend payout using the Stata. Financial leverage, sales growth and business risks are the most significant variables of the study where financial leverage and business risk have significant negative effect on dividend payout while sales growth has favorable positive impact on dividend payout. Results revealed significant positive link of profitability and firm size with dividend payout whereas government ownership is negatively associated with dividend payout. Investment opportunities, liquidity and managerial ownership showed insignificant relationship with dividend payout. This Suggests that dividend payout policy is dependent on business strategies including both investment and financing decisions. Financial managers should consider these factors while formulating dividend policy of the firm.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.19-27
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• 2020

This paper aims to empirically study the determinants of liquidity of Indian listed firms. To account for profit persistence, we apply a (pooled, fixed and random) effect models to a panel of Indian listed firms that covers the time period from 2010 to 2016. This study consists of 2154 firms operating in Indian market. Liquidity (LQD) of Indian firms is measured by liquid assets to total assets, whereas bank size, capital adequacy, profitability, leverage, and firm age are used as internal determinants. Further, economic activity, inflation rate, exchange rate, and interest rate are the external factors considered. The findings reveal that leverage, return on assets, and firm age are the essential internal determinants that impact the liquidity of Indian listed firms. Furthermore, among the internal determinants, the results indicate that firm size, leverage ratio, return on assets ratio, and firm age are found to have a significant positive association with firms' LQD, except leverage ratio and firm age has a negative relationship with firms' LQD. From this result, this article has provides helpful ideas and empirical evidence on the inner and external determinants of the companies mentioned in India is very useful to bankers, analysts, regulators, investors and other stakeholders.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.5-18
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• 2017

Total debt in the People's Republic of China surged to nearly 290% as a ratio to GDP by the second quarter of 2016, mostly on account of non-financial corporate debt. The outpouring of credit to stem the impact of the global financial crisis accentuated industrial overcapacity in traditional sectors, such as steel, cement, and energy, while feeding asset bubbles in the property, equity and bond markets. At the Chinese corporate level, this has translated into weakened fundamentals and a fall in industrial profits, particularly of SOEs. As debtors struggle to service interest payments, non-performing loans (NPLs) have been on the rise. This paper assesses the financial fragility of the Chinese economy by looking at risk factors in the non-financial sector. We apply quantile regressions to a dataset containing all Chinese listed companies in Standard & Poor's IQ Capital database. We find higher sensitivity over time of corporate leverage to some of its key determinants, particularly for firms at the upper margin of the distribution. In particular, profitability increasingly acts as a curb on corporate leverage. At a time of falling profitability across the Chinese non-financial corporate sector, this eases the brake on leverage and may contribute to its continuing increase.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.423-431
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• 2021

This study aims to examine the effect of liquidity, activity, leverage, and profitability on firm value, as well as the effect of disclosure of corporate social responsibility (CSR), which in this study is a moderator and company size as a control variable. The sampling technique used in this study is a purposive sampling method with certain criteria, to obtain a sample of 22 LQ45 index companies listed on the Indonesia Stock Exchange in 2014-2019. The data analysis method in this study used was the Multiple Linear Regression Analysis with the SPSS 18 Program. The results show that the ratios of liquidity, activity, leverage, and profitability are significant to firm value in accordance with the initial hypothesis of the study. Corporate Social Responsibility (CSR) plays a role as a moderating variable and company size variable as a control variable on the effect of financial ratios (liquidity, activity, leverage, and profitability) on firm value. The implication of this research is that CSR has a very important role in increasing company value. To attract more investors, companies must pay attention not only to financial performance but also to social performance. Large-scale companies tend to do more CSR so that the company value will increase.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.501-508
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• 2021

The largest source of revenue in Indonesia comes from the taxation sector. Taxes increase the state revenue, which the government utilizes for building public facilities and infrastructures, providing subsidies to the public, financing public interests, and so on. In addition to producing revenue, taxes may be used to promote economic stability. Thus, this study aims to examine and analyze the financial aspects of tax aggressiveness. The financial aspects include leverage, capital intensity, inventory intensity, and earning management. The population used in this study was manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the 2016-2019 period. Data analysis was carried out based on Eviews, with a selected sample of 32 companies of four observation years. Therefore, the number of samples was 128. The results of this study revealed that the best estimation model to use is the Fixed Effect Model (FEM). This study proved that leverage and earning management had a positive and significant effect on tax aggressiveness. In contrast, capital intensity and inventory intensity did not affect tax aggressiveness. In addition, the result of this study is still far from perfect. It is, therefore, hoped that further research can add other variables to find better results.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.501-515
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• 2022

Despite the stylized statistical features of returns of financial returns such as fat-tailed distribution and leverage effect, no stochastic volatility models that can explicitly capture these features have been presented in the existing frequentist approach. we propose an approximate parameterization of stochastic volatility models that can explicitly capture the fat-tailed distribution and leverage effect of financial returns and a maximum likelihood estimation of the model using Langrock et al. (2012)'s hidden Markov model approximation in a frequentist approach. Through extensive simulation experiments and an empirical analysis, we present the statistical evidences validating the efficacy and accuracy of proposed parameterization.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.627-633
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• 2020

The study attempts to analyze the impact of firm's risk on capital structure in the context of seasonal and non-seasonal businesses. We use two independent variables namely credit risk and systematic risk and one dependent variable to explore this connection. Sugar sector is taken as seasonal while the textile sector as non-seasonal businesses. The panel data of twenty-five firms from each sector are taken ranging for the period of 2012 to 2019 which has been retrieved from their annual reports for empirical analysis of the study. The results reveal the negative impact of credit risk on capital structure in both types of businesses. Increasing (decreasing) one point of credit risk causes a decrease (increase) leverage ratio by 0.27 points for seasonal while increasing (decreasing) one point of credit risk causes to decrease (increase) leverage by 0.15 points for non-seasonal businesses. Furthermore, the study shows positive impact of systematic risk on leverage ratio in non-seasonal business and no impact in seasonal business. Any increase (decrease) in the systematic risk causes an incline (decline) leverage ratio by 2.68 units for non-seasonal businesses. The study provides a guideline to managers for risk management in businesses. The research focusses on theoretical as well as managerial and policy implications on risk management in businesses.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.541-550
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• 2010

The $L_1$-regression estimator is susceptible to the leverage points, even though it is highly robust to the vertical outliers. This article is concerned with the improvement of robustness of the $L_1$-estimator. To improve its robustness, in terms of the breakdown point, we attempt to dampen the influence of the leverage points by means of reducing the weights corresponding to the leverage points. In addition the algorithm employs the linear scaling transformation technique, for higher computational efficiency with the large data sets, to solve the linear programming problem of $L_1$-estimation. Monte Carlo simulation results indicate that the proposed algorithm yields $L_1$-estimates which are robust to the leverage points as well as the vertical outliers.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.4
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• pp.592-609
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• 2019

This study attempts to expand the leverage cycle theory using the subprime real estate investors. The leverage cycle theory has demonstrated asset price fluctuations irrelevant to changes in fundamentals through the restructuring of transaction composition centered on optimistic buyers. However, it needs to understand how this theory works in the depressed housing market with low-income residential regions to explain the geographic origins of the financial crisis. In the depressed housing market, the subprime real estate investors focused on low-income residential regions. Through this spatial focus, the low-income residential regions solely have real estate investor-oriented composition of new purchase transactions in the depressed housing market. The discovery of the subprime real estate investors as new actors lays the foundation for applying the leverage cycle theory to the depressed housing market which has been a underserved area for capital investment. This attempt illustrates how the geographical reinterpretation of an economic theory reestablishes spatio-temporal context of economic phenomena.

• The Journal of Fisheries Business Administration
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• v.42 no.2
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• pp.1-14
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• 2011

We try to find the determinants of fisheries firms' capital structure during the years from 1992 to 2007 in this paper. We also have a comparative analysis of capital raising behavior in pre and post-IMF financial crisis. Regression analysis is used for this empirical study. Dependent variable is leverage ratio and independent variables are firm size, operating risk, proportion of tangible asset, non-debt tax shield effect, sales growth ratio, profitability and dummy variable. We compared the characteristics of fisheries industry with that of manufacturing industy. The determinants of fisheries firms' capital structure and correlation between pre and post-IMF financial crisis are roughly same as the hypothses except a little difference. As a peculiar difference, corrlation between fisheries firms' operating risk and leverage ratio is (+) in the pre-IMF financial crisis, but (-) in the post-IMF financial crisis. Proportion of tangible asset has a (+) correlation with leverage ratio in pre and post-IMF financial crisis, but in case of manufacturing industy, (-) correlation shows in the pre-IMF financial crisis. Because, in the pre-IMF financial crisis, high proportion of tangible asset doesn't play a role of a collateral, but only increase the bankruptcy probability. Non-debt tax shield effect and leverage ratio have (-) correlation in all industry and all period, but only (+) correlation in case of fisheries industry in the pre-IMF financial crisis. Sales growth ratio has no significant relationship with leverage ratio in fisheries industry, and this is not coincide with our hypothsis. We have a limitation of the sample size of fisheries firms and sample period in this study. Further study is required to classify the fisheries industry with in-shore fisheries, deep sea fisheries and cold storage industry.