عباس علیمرادی

The main purpose of this research is to explain why and how the stock liquidity affects the default risk of petrochemical and petroleum products companies listed in Tehran Stock Exchange. The study used experimental data and parametric tests in order to estimate the relationship between stock liquidity and default risk through information efficiency and corporate governance roles of stock liquidity. The present research is applied in terms of purpose and is a descriptive-correlative study. All data required regarding the stock liquidity, price, trading volume and days, stockholder ownerships, etc., were extracted from Rahavard Novin database software. To investigate the relationship between variables, the multivariate regression analysis model using OLS method was applied in Eviews platform. The empirical findings showed that there is a significantly negative relationship between stock liquidity and default risk of petrochemical and petroleum product companies listed in TSE and also stock liquidity can affect the default risk through reducing the information asymmetry in the stock pricing process and strengthen the corporate governance. These results could provide visible signals based on the realities of the market in order to improve models to assess and predict the risk of default and lead managers and decision makers of suppliers, customers, partners and stakeholders, to conclude more flexible contracts with petrochemical and petroleum products companies and ultimately better mitigate business risks.

Recent theories of firm dynamics emphasize on the role of financial variables as determinants of firm growth. Most of the technical literature shows that there is a positive relationship between financial leverage and firm growth. The purpose of this paper is to examine whether such relationship exists among oil and gas companies within the Organization of the Petroleum Exporting Countries (OPEC). Data were collected from the selected members of the OPEC. The collected data was then analyzed using the Arellano and Bond (1991) GMM method and Sargan test. The results showed a significant and positive relationship between financial leverage and firm growth which is in line with the technical literature. This research contributes to the body of knowledge by examining a specific and important sector within several different countries. It shows the current theory is not affected by industry or country.

Though it is generally accepted that information asymmetry has an impact on capital structure policy, the nature of the information asymmetry is not well understood. Recent theoretical works and empirical evidences suggest that financing choice depends upon the information asymmetry about investment risk of the particular use of funds (Halov & Heider, 2012) (Rao, Mohanty, & Baxamusa, 2015). Consistent with this view, we analyzed the data gathered among 199 companies listed in Tehran Stock Exchange during 2009-2016 by The Multiple Linear Regressions in order to test research’s hypotheses have been applied. We also examined the influence of Petrochemical industry on that relationship. The findings show that equity is used to fund projects with greater information asymmetry about their risk such as intangible assets and capital expenditure, while debt is used to fund investments with lower information asymmetry about their risk such as liquidity enhancement. We also found that the membership in petrochemical industry has no effect on the intangible assets and cash holding’s financing method, but concerning with capital expenditure and working capital the impact is significantly negative.

The research on the Markowitz model and optimization of its portfolio using a variety of evaluation indicators and meta-beta-algorithms has always been the focus of attention of accounting and finance researchers. The results of studies carried out by various types of optimization methods are different in the Markowitz modified models. The purpose of this study is to measure the optimal portfolio and its corresponding return, with respect to the portfolio in the traditional Markowitz model, as well as to compare the position of the refining and petrochemical companies versus stock market outperformers, through integrating the operational criteria and the new indicators of liquidity using the genetic algorithm in the Markowitz model. Therefore, financial data related to the research variables for 35 cases of TSE-listed refinery and petrochemical companies from 2012 to 2016 fiscal years were extracted from Rahavard Novin database software and simulated by the genetic algorithm. The results show that returns on the stock portfolio optimized using the genetic algorithm and without considering the liquidity limitations and filters have a significant and positive difference with the return on the stock portfolios optimized with regard to the liquidity limitations and filters. Furthermore, the application of liquidity limitations and filters in the formation of optimal stock portfolios leads to a conservative increase in the choice of stocks (portfolio formation), which leads to a reduction in the risk and return of investment in such portfolios.