INVESTIGATING THE EFFECT OF FINANCIAL LEVERAGE AND FIRM SIZE ON THE RANK OF SHARE LIQUIDITY FOR COMPANIES LISTED ON TEHRAN STOCK EXCHANGE HAMIDREZA VAKILIFARD, PHD. 1 GHOLAMREZA ASKARZADEH 2 Faculty member of Management Department, Science and Research University, Islamic Azad University, Tehran, Iran 1 Faculty member of Sama Technical and Vocational College, Islamic Azad University, Yazd, Iran 2 ABSTRACT One of the criteria taken into consideration by investors when making decisions about participation in an investment opportunity is the liquidity of asset. Liquidity refers is to the quick and ease of converting assets into cash. Liquidity of assets has two aspects: ease of exchange versus reduction of the value. An asset with high liquidity is the one that can be sold quickly without significant reduction in its value. An investor tries to consider liquidity risk of an asset and finally decides to buy it after comparing its risk with the risk of other available investment opportunities. Regarding this, some firms may use leverage to increase their debt ratios. This investigation aimed to determine the relationship between financial leverage and liquidity rank of industrial and manufacturing companies listed on Tehran Stock Exchange. Moreover, in order to get a deepened investigation, the firm size was also studied. To this aim, a population of 163 companies whose information was available for a five-year period (2009-2013) was selected. Regression analysis was used to test the hypothesis. The results indicated that firms with higher financial leverage enjoyed less liquidity. Furthermore, smaller companies had less liquidity comparing with medium-sized and large companies. Keywords: financial leverage, stock liquidity ratings, firm size, stock liquidity coefficient 1. INTRODUCTION Expansion of the scope of business units has created new financial needs that the internal and external sources are capable of meeting them. The internal resources include interest-bearing liabilities and shareholders' equity. Using external sources include interest-bearing liabilities to shareholders' rights. The use of external sources has its own advantages and disadvantages regarding the capital cost, interest rate and dividends. Consequently, this can affect the efficiency, stock price and accounting earnings. Funding received from interest-bearing loans has several strong points: first, loan interest has acceptable tax expense and this causes the reduction of effective cost of the loan. Especially, if the rate of return gained by the use of these resources is greater than the rate of cost of financing, the common stock holders find no reason to share the loaners in the residual income since the rate of interest and the long-term debt is fixed. The second reason is that loaners have no right to vote. Thus, with less money, shareholders can take more control over the actions of the larger companies. On the other hand, long-term debts suffer from the following weaknesses: first, long-term debts create financial obligations and relying too much on them leads to the increase in financial leverage and consequently increase in the probability of bankruptcy and failure to pay back the loan or the interest. Excessive use of long-term debts, especially for the firms that do not enjoy optimal financial condition, makes the obligations of the company heavier and increase the financial risk and bankruptcy of shareholders. Secondly, the higher the ratio of the loan in some countries, the higher the risk will be. Consequently, the expected rate of return of creditors and the expenses of loans will increase; this can influence the advantages of tax exemptions (Brigham, 2003). On the other hand, the quick exchange of shares into cash is of significant importance for many investors. However, the major question being raised here is that if a company 72
chooses a high financial leverage, how can this affect the liquidation of shares? In response, some argue that since firms with high financial leverage have higher financial risk and the probability of their bankruptcy is high, the ratio of their liquidity is low. Still some believe that firms with high financial leverage create significant growth opportunities in the future and therefore increase the demand for the purchase of their shares and consequently the coefficient of share liquidity is higher. The main purpose of this study was to investigate the relationship between financial leverage and stock liquidity rate of industrial and manufacturing companies listed on the stock exchange. Furthermore, to deepen the study, the firm size was added to the model. For this purpose, the literature regarding various related theories is reviewed and domestic and foreign investigations are discussed. Next, the research method including assumptions, population and statistical sample used to test the hypotheses is described. Then, the results of the analysis are presented and finally conclusions and recommendations are discussed. 2. REVIEW OF THE LITERATURE A) Bankruptcy costs and the theory of Modigliani and Miller Non-leveraged firms compared with leveraged firms are more likely to go bankrupt. When the ratio of debt to equity exceeds certain limits, the probability of bankruptcy increases and bankruptcy expected costs rises. This will negatively influence the company's value and its capital expenses. If the company is unable to pay its debts or compensate its bankruptcy, decisions to be made on financing will be highlighted. Therefore, companies are forced to waive many of the investment projects and try to maintain the company's liquidity. It can then be evident that no one is willing to invest in a company which is expected to go bankrupt. In order to attract business investment and reassure the investors by giving useful information, companies need to spend a lot. Unlike followers of Miller's and Modigliani's theory, the company's charges increase in this case. (Azizian, 2008). B) The theory of hierarchy of financing options resources. The formation of this hierarchy is the result or consequence of asymmetric information. According to this theory, in cases that there is information asymmetry between managers and outside investors, finance directors prefer the company's internal resources to its external resources. This means that they finance by retained earnings or savings and then if the internal resources were not adequate, they would fund by sources outside the company by releasing bonds with the lowest risk (i.e. borrowing); again, if borrowing could not resolve the problem and more financial resources were needed, they would release the stocks. Many reflected on the theory of hierarchy financing options. What follows is some of the most important ones. 1. There is no desirable or target debt ratio for companies. 2. Profitable companies lower their borrowing. 3. Companies tend to keep and save their cash (Frank et al., 2003) C) Liquidity Liquidity refers to the ease and quickness of converting an asset to cash. Liquidity has two aspects: ease of exchange versus reduction of the value. If the price of an asset is reduced sufficiently, it can be easily converted into cash. This kind of asset is called a high liquidity asset since it can be sold without a significant decrease in its value. Maintaining the assets in cash cannot be much profitable. For example, maintenance of the cash that is considered the most cash investments has sometimes no efficiency. (Ross and Vesterfield, 2003). However, one of the risks of the asset is the risk of its liquidity. Because of the nature of risk aversion, investors are looking for assets that can be readily converted into cash or the assets with risks that in exchange earns excess returns. Stock liquidity coefficient is a very important factor that should never be neglected. This factor is influenced by parameters such as the company's turnover, number of transactions, number of traded shares, number of buyers and number of the stock trading days. How this value is calculated is shown in the following. According to this theory, firms follow a certain hierarchy in order to provide their financial 73
After calculating the coefficient of liquidity, the gained numbers are arranged from large to small; this means that the first rank is the highest level of liquidity, and second, third, forut, etc., have less liquidity, respectively. 3. BACKGROUND OF THE STUDY Different studies have investigated the effect of several variables, such as firm size, tangible assets, profitability, growth, fluctuations in earnings and dividends, on companies' financial leverage. Several researchers stated that the more cash assets increase the borrowing capacity. In contrast, some support the negative effects of this relationship. Valier (1988) argued that assets which can be exchange to cash easier or have greater transmissivity are better guaranteed and should often be financed with debts, This is because banks and markets of public debt charge lower costs in financing these assets. For example, lower discount rate on the sale of cash assets can make it easier for the banks to convert them to cash if necessary. Likewise, cash assets are regarded better supports for bondholders. One of the reasons is that these assets are more convenient for bondholders in terms of monitoring and evaluation; in addition, they can be easily sold in cases of bankruptcy. Therefore, the liquidity of more assets can reduce financing costs through reduced external borrowing and increase the amount of capital of the firms that can borrow. When financing costs are reduced through debt, companies realize that it's better to borrow more and enhance optimal leverage as much as required. This way, higher liquidity increases financial leverage. Harris et al. (1990) predicted a positive relationship between final value (i.e. liquidation value) and the leverage. The expected liquidation values are higher for cash assets with easier liquidity. This indicates that the company's liabilities are directly associated with assets liquidity. In their model, they focus on debt advantages in providing information about company's profitability. Investors extract the debt information by viewing the company's ability to fulfill contractual payments at different levels of leverage. This information can be used for any required change in operating policies or the financial structure of an enterprise. Finally, their model predicted that firms with higher liquidation values have higher leverage for the assets and deal with fewer problems. On the other hand, Myers and Rajan (1998) emphasized the liquidity expenses to state that managers with more cash assets deal with the problem of assigning a specific sector of their activity. The analysis is based on the assumption that higher liquidity sometimes makes it difficult to predict the asset value. Uncertainty about the value of assets potentially increases the conflicts of gained interest, particularly in the case of representative institutions and financial intermediaries. Foreign creditors increase the borrowing costs or they decrease company's share of financing through debts. In other words, the borrowing capacity decreases. Agency liquidity costs increases by leverage and decreases by the expertise in the management of the company. Finally, Myers and Rajan (1998) concluded that the effect of liquidity on debt levels and optimized leverage can be negative in high levels of debt and leverage. In their study, Awan et al. (2010) investigated the effect of growth opportunities on corporates' leverage. Results indicated that a positive relationship exists between growth opportunities and debt level of the company. They also examined the size of the company and concluded that no relationship exists between leverage and growth opportunities in highgrowth companies and that these companies, in fact, have no growth opportunity. Izadinia and Rasaeian (2009) studied the relationship between financial leverage and asset liquidity of companies. They concluded that 65% of the changes in financial leverage are determined by variables such as return on assets, firm size, the ratio of book value to market value of equity and the net value of properties and equipment. Return on assets and the firm size have a significant negative effect on financial leverage while other variables have no significant effect on that. 4. METHODS A correlational design was used in this study; the analysis was also done by panel data. The information about liquidity rate, debt ratio (corresponding to financial leverage) and assets 74
(corresponding to firm size) of 163 firms listed on Tehran Stock Exchange were collected by Rahavard Novin software. This information was then analyzed by Stata software. To achieve the objectives of the current study, the following hypotheses were proposed. 4.1. Hypotheses The key question raised here is whether a significant relationship exists between the size and financial leverage of the company, and the liquidity rate for companies listed on Tehran Stock Exchange. Accordingly, the proposed hypotheses are as follows. Hypothesis 1: There is a significant relationship between financial leverage and stock liquidity rate. Hypothesis 2: There is a relationship between firm size and stock liquidity rate. B) To select the active companies, their transactions during the years 2009-2013 must no be interrupted or stopped. In other words, the shares of these companies must be active in the stock during the mentioned period. The interval length must not exceed three months. C) To be comparable with the other companies and to avoid inconsistencies, the fiscal year of the selected companies must be ending by March 29; also, their fiscal year must not be changed during the years 2009-2013. 4.4 The model used in the study According to the variables mentioned before, the research model is proposed as follows. Liquidity= 4.2. Studied variables The dependent variable was stock liquidity rate and the independent variable consisted of firm size and financial leverage. Financial leverage is the division of the company's total liabilities to its total assets. Where financial leverage (debt ratio), size is the size of the company (natural logarithm of assets), liquidity is the liquidity rate, β 0 is the fixed ratio, Firm size is the natural logarithm of total assets of the company. 4.3 Population and statistical sample The spatial domain of research was the industrial companies listed on Tehran Stock Exchange being investigated in the period between 2009 and 2013. Knock-out of systematic sampling was used to select the statistical sample. Companies with the following characteristics were excluded from the sample: A) Due to the different nature of their activities, investment, insurance, leasing and banking companies were excluded from the selected group. e is the error rate which is independent from regression factors. In case of the rejection of hypothesis H 0, H 1 will be accepted assumption that indicates a significant relationship between liquidity and independent variables. 5. ANALYSIS OF THE RESULTS To estimate the model used in this study, panel data techniques was used. The importance of using this technique, which combines cross-sectional and time series data, can mainly be explained by an increase in the number of observations, the raise of degree of freedom, reduction of variance inconsistency and collinearity between variables. Thus, the model estimation is done using panel data for all companies in the sample during the years 2009 to 2013. Then, based on estimates obtained as well as the application of F and T statistical tests, the calculated probability (p-value), coefficient of determination and evaluation 75
of each of the hypotheses of the study will be discussed. The question that is often raised in applied studies is whether there is evidence of the ability to integrate data or the model is different for all sectional units. Therefore, it should be checked to assure whether there is heterogeneity or individual differences between the units? If so, the panel data approach is used; otherwise, the panel data approach with ordinary least squares (OLS) is applied to estimate the model. To this aim, F Limer test is performed. In this test, H 0 which is the similarity of intercepts (combined data) is taken against H 1 which is the dissimilarity of intercepts (panel data). If it is found that the investigate units were heterogeneous and there are individual differences among them, they will be considered better panels. This way, Hausman test is used to choose between fixed and random effects. Hausman test statistic, which is used for the detection of fixed or random variation of the cross sections, has chi-square distribution with degrees of freedom equal to the number of variables. Before testing the model and conducting the corresponding tests, the features of statistical data for the presence of unit root and durability are examined. To this aim, IPS test is used, the results of which is presented in Table (1). Table (1) Results of testing the durability of model variables Variable (t) P-value Liquidity -7.11 0/00 Leverage -6.22 0/00 Size -18.31 0/00 Source: the researcher's calculation using Eviwes the variables in the model since the P-value is less than five percent. Therefore, it can be said that all variables in the model are durable. As previously stated, the hypotheses in the present study were tested using panel data and regression analysis obtained from companies in the sample. F Limer test and Hausman test were also used for the detection of panel data model. Since the results obtained from the F Limer test is F statistic with P-value equal to 0.000, H 0 regarding the application of combined data method cannot be accepted. Thus, using panel data is recommended here. Given the significance level, the obtained result of the study indicates that the investigated levels have individual differences and the use of panel data is more appropriate. Hausman test was performed after selecting a panel data analysis method through Limer test. Given the chi-square statistics for this test (66.3) and a significance level of 0.000, it can be concluded that H 0 is rejected and the opposite hypothesis at 95 percent confidence level is confirmed; this implies using fixed effects. One of the most important classical assumptions in the linear regression model is that disturbing components have the same variance. If the model has inconsistent variance, F and T statistics give wrong results. Examining the variance of the disturbance terms and considering the significance level of less than 5% (0.000) obtained in this test, H 0 claiming the inconsistent variance is rejected and the model should be estimated using generalized least square (GLS). The final results obtained from model estimation are presented below in Table (2). Table (2) Results of estimation of the model using generalized least squares (GLS) As shown in Table (1), the null hypothesis regarding the non-durability of the variables is rejected for all Dependent Independen Coefficie variable P-value Z Standard error t variable nt Leverage 0/000 5/28 0/14 0/76 Liquidity Size 0/000-14/39 0/01-0/ 26 Intercept 0/000 29/47 0/21 8/01 Source: researcher's calculations using Stata (Version 11) The first hypothesis expresses the relationship between financial leverage and liquidity rate. According to the results shown in the table above, a significant relationship exists between them. Based on this, the obtained ratio is 0.76. Therefore, given the first hypothesis, there is a positive relationship 76
between financial leverage and the rate of liquidity. This means that the greater the debt ratio of a company, the greater the rank number of that company will be. That is to say the firm enjoys lower liquidity coefficient. In other words, companies that have more debt enjoy lower liquidity. But according to the second hypothesis, the negative relationship between firm size and liquidity rate of a company was confirmed since the coefficient obtained from that was 0.26. The larger the size of a company, the smaller the number for rate of liquidity will be (i.e. the liquidity coefficient is higher). In other words, smaller companies enjoy lower liquidity coefficient and this coefficient is higher for medium-sized and large companies. 6. CONCLUSIONS Stock liquidity is one of the factors that investors take into consideration, along with other criteria such as profitability, growth opportunities and higher dividends. The purpose of this study was to identify the relationship between liquidity of shares, financial leverage and firm size. The proposed hypotheses claiming a relationship between rate of stock liquidity and financial leverage (H 1 ) and also the relationship between stock liquidity rate and firm size (H 2 ) were tested. The results suggested that a direct and significant relationship exists between the rate of stock liquidity and financial leverage (the rank number of companies with less debt is smaller and this means they enjoy higher liquidity coefficient). Also, the negative relationship between stock liquidity and firm size shows that the larger the company, the smaller the liquidity rank number will be. This means that these companies have a higher liquidity coefficient. It is, thus, recommended that when investing in stocks, shares of big and mediumsized companies as well as companies with less debt be selected. REFERENCES 1. Ahn, S., Denis, D., and Denis, K. (2006). "Leverage and investment in diversified firms". Financ. Econ. Vol 79, pp: 317-337. 2. Alderson, Michael J., and Brian L. Betker, (1995), "Liquidation Costs and Capital Structure", Journal of Financial Economics 39, 45-69. 3. Aoun, D., and Hwang, J,. ( 2008 )." The effects of cash flow and size on the investment decisions of ICT firms: A dynamic approach," Informamation economics andpolicy. Vol 20, PP: 120-134 4. Azizian, A. (2006). The effect of capital structure on the cost of capital, MS Thesis, Shahid Beheshti University. 5. Brigham, O. and Gapenski, L. ; translated by Parsaeean, A. (2003). Intermediate finance management. Tehran. Termeh Publication. 6. Corrado, J. and Bradford, J. D. (2000). "Fundamental of Investmenst," Journal of Financial Economics. Vol 54, PP: 25-39. 7. Frank, Marrayz,Goyal, (2003), "Capital Structure Decisions",social science research network, from: www.ssrn.com\abstract:273006 8. Harris, Milton, and Artur Raviv, (1990), "Capital Structure and the Informational Role of Debt", Journal of Finance 45, 321-349. 9. Hayat M. Awan, (2010), M. Ishaq Bhatti, Raza Ali (Pakistan), Azeem Qureshi. Investment Management and Financial Innovations, Volume 7, Issue 1 10. Hong, Z., and Jason X. (2006). "The Financing Behavior of Listed Chinese Firms".The British Accounting Review, Vol 38, pp: 239-258. 11. Izadinia, N & Rasaeeian, A (2009). Studying the relationship between financial leverage and liquidity of assets in Tehran Stock Exchange. Financial Accounting Quarterly, (2). 12. Karimi, F. & Akhlaghi, H. (2008). Studying the effect of financial leverage and growth opportunities on company's investment decisions in Tehran Stock Exchange, Financial Accounting Quarterly, (8). 13. Lang, L., Ofek, E., and Stulz, R. (1996). "Leverage, investment and firm growth". Financ. Econ. Vo140, pp: 3-29. 14. Myers,stewart. & Rajan, G. translated by Parsaeeina, A. (1994) Optimal capital structure, Journal of Financial Research. 15. Ross and westerfield,fundamental of corporate finance,(2003),macgrhill,pp22-16. Salavati, Sh. & Rasaeeian, A. (2007), Investigating the effect of capital structure on stock liquidity in Iran, a useful economic letter, 13 (63). 17. Shleifer, Andrei, and Robert W. Vishny, (1992), "Liquidation Values and Debt Capacity: A Market Equilibrium Approach", Journal of Finance, 47 77
18. Sung C., ( 2009). "On the interactions of financing and investment decisions." Managerial Finance. vo1 35, pp:691~- 699. 19. Taghavi, M. (2005),Firms' financing. Financial Accounting Quarterly, (3). 20. UmutLu, M,. (2010). "Firm Leverage and investment decisions in an emerging market". vvww.ssrn.com. 21. Vidhan, K., Goyal, A., and Lehn, B. (2002). "Growth opportunities and corporate debt policy": the case of the U.S. defense industry. Journal of Financial Economics. Vol 64, PP: 35-59. 78