DOL And DFL On Systematic Risk Finance Essay
Asset structure and financial structure of the firm play an important role in the systematic risk of its common stock. This study is an attempt to use the operating leverage (associated with the asset structure of the firm) and financial leverage (associated with the capital structure of the firm) as the determinant of systematic risk of the common stock in relation with the previous studies done by the researchers. The regression analysis is used to find the relationship between DOL, DFL and the systematic risk by analyzing the data for the period from 2000 to 2008.
The empirical results indicate that DOL can determine the systematic risk but DFL fails to do so. It is also revealed that the degree of two types of leverages are independent of each other and do not vary in relation with each other.
CHAPTER 1: INTRODUCTION
The capital asset pricing model estimate the return of a security with the help of risk free rate of return, market premium and the systematic risk of that security. The beta incorporated in the CAPM only considers the security specific parameters that affect the return on the risky security. Many tests of the CAPM indicated that the beta coefficients for individual securities were not stable, but the portfolio betas generally were stable assuming long enough sample period and adequate trading volume (Robert A. Levy, 1971). There was a mix support for a positive linear relationship between rate of return and systematic risk. Thompson, 1976 and Barr Rosenberg, 1973 indicated the need to consider additional risk variables. Risk of a firm consists of many risk factors such as business risk, operating risk, liquidity risk and financial risk.
Firm’s business risk is associated with the asset structure of the firm (the higher the firms fixed cost, higher the firm’s operating leverage). Higher fixed cost is generally associated with the use of highly automated, capital intensive firms. Firms having higher DOL will also have higher level of business risk.
Financial risk is the additional risk placed on the common stockholder as a result of the decision to finance with debt. With the use of debt the equity holders will have to bear virtually all of the business risk. Therefore the use of debt enhances the risk on the stockholders, this occurs because debt holders receive fixed interest payment but bear none of the business risk.
Modiglini and Miller’s (1958) results (i.e firm’s value is not affected by its capital structure and hence it’s cost of capital) when there are no bankruptcy costs. Conversely in real it can be quite costly moreover financial distress can be caused by key employees jump ship(employees turnover), supplier’s refusals to grant credit etc. bankruptcy related problems arise when firm accommodate large amount of debt in its financial structure. Therefore these costs discourage firms from pushing their use of debt to excessive levels. Firms with volatile earnings face great chance of bankruptcy therefore should use less debt than stable firms i.e. the firms with higher operating leverage (greater business risk) should limit their use of financial leverage. Similarly a firm that would face high cost in the financial distress should rely less heavily on debt. These issues lead the firm to trade-off the benefit of debt financing against the higher interest rates and bankruptcy costs. Therefore there must be a balance between the business and the financial risk or degree of both kind of leverages to arrive at the optimal capital and asset structure.
The determinants of systematic risk have been an important issue for many years. Many studies have investigated the association between market determined and accounting determined risk determinants (chei-Chang Chiou 2007, William Beaver 1970 and 1975). These studies enhanced the knowledge about the correlation between the betas of the common stock and the various accounting variables.
It is known that the firm’s capital structure and financial structure have influence upon the business risk and the financial risk, different studies have separately analyzed the impact of operating and financial leverage on the systematic risk. Hamada (1972) reports that firm’s capital structure contribute approximately 25% of the systematic risk. Lev B (1974) provide empirical evidence that operating leverage (as measure of variable cost) is one of the real determinant of systematic risk. Hill and Stone (1980) have provided knowledge about accounting analogue to study the joint impact of operating risk and financial structure on the systematic risk. Gahlon and Gentry (1984) determined beta on the basis of four variables namely DFL, DOL, the coefficient of variation of the total revenue and the coefficient of correlation between EAT and return on the market portfolio.
As the degree of two types of leverages are recognized as the real determinant in the Gahlon and Gentry’s (1984) model. The study found the joint impact of two types of leverages on the common stock beta. The study also has addressed the issue of trade-off between the financial and operating leverage.
The study provided the evidence that the firm’s asset structure and the financial structure play important role in the degree of risk involved in the firm’s business. Based on the results a firm can decides its asset and financial structure i.e the types of equipment used and the employment of debt that will lead the firm to the desired level of the risk. Also investors can evaluate the riskiness of the firm’s business by reviewing its capital and asset structure.
1.2 Problem Statement
The study discovered the effect of DOL and DFL on the systematic risk and discussed the trade off effect between the two types of leverages. The companies listed on the Karachi Stock exchange that are continuously in the KSE-100 index for the whole study period i.e. from 2000 to 2008 are considered for the study. The study is beneficial for Pakistani firms to understand the effect of the use of operating leverage and the use of financial debts on the risk involve in their common stocks.
In this study following hypotheses are tested
H1: There is an effect of DOL on the systematic risk (Beta).
H2: There is an effect of DFL on the systematic risk (Beta).
H3: There is trade off (negative correlation) between the degree of operating and financial leverage
1.4 Outline of the study
The study involved three variables. The dependent variable is the risk of the common stocks measured by beta coefficient of regression between monthly return of an individual firm and a market portfolio; the independent variables are the DOL and the DFL.
1.4.1 The systematic risk (beta)
Co-movement of an individual asset relative to market portfolio is referred as systematic risk. This co-movement is measured by security’s covariance with the market portfolio i.e. the portion of the security’s variance attributable to the variability of the market portfolio. This variable is calculated by regressing the monthly stock returns of the company with the monthly return of any market portfolio, in this study KSE 100 index is taken as the reference market portfolio.
(Ret) i =a+β (Ret) KSE100 i=1,2,3...........
In the above equation (Ret)KSE100 represents the monthly return of the KSE 100 index, (Ret)i monthly return of company i, a is the intercept of the line and β is the systematic risk of company i.
The Degree of operating leverage (DOL)
If a high percentage of firm’s costs are fixed, hence do not decline when demand falls, then the firm is exposed to relatively high degree of business risk, this is called DOL. A high DOL implies that a relatively small change in the sales results in a large change in the EBIT. It is defined as follows
DOL= ΔEBIT% ÷ ΔSales%
It is calculated with the help of regression between the sales and EBIT by the following equation
(EBIT)i = αi + bi (Sales)i i=1, 2, 3……….
In the above equation EBIT is the earning before interest and taxes, αi intercept of the line, bi the DOL and (Sales)i sales of company i.
In addition DOL is calculated with the proxy Fixed Asset to Total Asset suggested by Gershon N. Mandelker and S. Ghon Rhee (1984), Anthony Saunders, Elizabeth Strock, Nickolaos G. Travlos (1990) and Thomas J. O'Brien and Paul A. Vanderheiden (1987)
The degree of financial leverage (DFL)
Financial leverage refers to the use of financing other than equity (debt or preferred stock) to magnify the operating results. It is defined as the percentage change in the EAT that results from the percentage change in the EBIT.
DFL= ΔEAT% ÷ ΔEBIT%
It is calculated with the help of regression between the EAT and EBIT by the following equation
(EAT)j = αj + bj (EBIT)j j=1, 2, 3……….
In the above equation EAT is the earning after interest and taxes, αj intercept of the line, bj the DFL and (EBIT)j is the earning before interest and taxes for company j.
In addition DFL is calculated with the proxy Long term Debt to Total Asset suggested by Gershon N. Mandelker and S. Ghon Rhee (1984), Mark Brimble and Allan Hodgson (2007), Douglas V. DeJong and Daniel W. Collins (1985), and Dennis E. Logue and Larry J. Merville (1972).
CHAPTER 2: LITERATURE REVIEW
Numbers of studies have been done by researchers to investigate about the real determinants of the systematic risk of the common stock. Researchers have attempted to explain the extent to which risk depends on a particular risk factor.
Menachem Brenner and Seymour Smidt (1977) provide theoretical evidence that beta for a security does not remain stationary over the time, it hide an important fact that firms make decisions about how to operate in the factor and product markets of the real economic sector. Stewart C. Myers and Stuart M. Turnbull (1977) pointed out, the actions taken as a result of these decisions generate a real return composed of an immediate cash flow plus any change in the present value of future investment opportunities. They have examined the good and bad aspects of the capital asset pricing model as it is simple to evaluate corporate assets the only thing required to know is the correct beta for the firm. But the bad news is that the beta does not remains constant it vary with project’s expected life, the growth trend of the expected cash flows and the other variables that are not usually considered significant in assessing business risk. . To estimate systematic risk the regression procedure uses the realized financial returns generated in the real financial market of the economy. It therefore provides no knowledge of the real determinants of beta from the underlying characteristics of the real assets. Moreover, financial managers cannot look to the CAPM for estimating beta on the basis of firm related variables. Mayer (1977) used financial leverage and the volatility of operating earnings as the determinants of beta. James M. Gahlon and James A. Gentry (1982) identified the DOL, DFL, coefficient of variation of revenue and cash flow correlation coefficient as determinants of beta. An example was taken to study the effect of different cash flow characteristics to the DOL, DFL and variability of revenue and ultimately the change in the systematic risk of the common stock.
Uri Ben-Zion and Sol S. Shalit (1975) were examined three different means of risk namely leverage, size and the dividend. Their findings suggested that the firm’s leverage, size and the dividend record are the important determinant of risk. All of the three variables were found statistically significant with the systematic risk of the common stock, but because of the low value of R square Uri & Shalit Suggested that there must be some other variables as well that might affect the risk of the common stock.
Baruch Lev (1974) discussed the relationship that exists between operating leverage and the risk. Lev (1974) raised the point that risk is a crucial factor for both investors and the firm which depends on the managerial decision of the firm regarding their fixed and variable costs sources. The relationship has been empirically examined for homogeneous industries of electric utility, steel and oil and it was found that the firms with higher variable costs (lower DOL) are negatively associated with the systematic risk. Lev(1974) found that the coefficient of determination was not good enough and he concludes that the operating leverage is not the only source of systematic risk. It was suggested that the large expenditure by the firm will increase the riskiness of the stock and hence will change the stock prices and market value of the firm.
A simple model was developed by Menachem Brenner and Seymour Smidt (1978) to explore the relationship between the systematic risk of a security and the characteristics of the underlying real assets. They have explained that if there has been a large change in the market value of a firm's equity that can be explained in terms of known changes in the fundamental characteristics of the firm's assets, then a corporate manager can use their model to estimate whether the beta coefficient of the firm's equity has changed, and, if so, by how much. They also suggest the changes required by a firm when it decides to change its operating or financial policies. They said that if life of an asset is perpetual (produces cash flows in the future) and the covariance between the expected cash flow and the rate of return on market portfolio is constant then the firm will have constant absolute amount of risk. The market value may vary because of changes in the expected cash flows.
Donald J. Thompson II (1976) has identified some variables in the light of prior research whose variability with the macroeconomic fluctuations contributes to the beta of a common stock, for example dividends, earnings, earnings yield, operating income, sales, total debt to total assets, cash flow to total debt, current ratio etc. To investigate the relationships between systematic risk and the proposed explanatory variables correlation and regression analysis was used, Donald (1976) found that the variables affecting operating variability, financial leverage and common stock marketability are significantly related with the risk of the common stock.
Ronald W. Melicher (1974) has examined the link between the market risk and that calculated with financial factors or data. He included 28 variables for electric utility companies.He factorially analyzed the data and found 7 significant factors which explain the 85% variation in the data. These factors were financial leverage, size (total assets), earning trend and stability (dividend payout ratio), operating efficiency, financial policies (net plant to total capital), return on investment and market activities (stock traded to stock outstanding). He empirically found a positive relationship between beta and size of the firm, net plant to total capital, return on investment and market activity. A nonlinear relationship exists between size of the estimated beta and the DFL. Further he tested a nonlinear relationship between beta and the financial leverage and found that in both cases either linear or nonlinear financial leverage is not affecting the size of the systematic risk. Estimated beta was significantly related with to the level of equity return and market activity of common stock. He also found a negative relationship between beta and the dividend payout policy which reflects earning trend and stability of the firm in the industry.
Gershon N. Mandelker and S. Ghon Rhee (1984) examined the association between DOL and DFL by extending the model suggested by Hamada and Rubinstein (1972) and incorporate the degree of both types of operating and financial leverages. The study showed that DFL and the DOL can explain a significant amount of systematic risk. They found that both types of leverages are positively related with the systematic risk i.e. increase in any kind of leverage will cause an increase in the systematic risk. They further explain that there is a trade-off between the DFL and DOL i.e. the firms with higher DOL will try to have lower DFL and vise versa.
Chei-Chang Chiou and Robert K. Su (2007) explored way to minimize risk faced by an organization. They have provided accounting determinants that affects the systematic risk such as earnings, sales growth, book value, dividend, DOL, DFL and degree of total leverage (the product of two types of leverages).The have suggested that depending on the prior year earnings, current year sales growth and the combined effect of earnings, dividends and book value on the stock price the DOL, DFL and DTL will effect systematic risk differently (either positively or negatively).
Ned C. Hill and Bernell K. Stone (1980) explained empirically the relation between the accounting based and market based measures of systematic beta and the effect of financial structure on the risk. A risk composition model was developed which defined accounting equity beta in terms of accounting measures of operating risk and financial leverage. The study concluded that changes in the financial structure or changes in the business operating risk can significantly explain the variation in the common stock beta.
The association between accounting determined beta (NI/TA, NI/NW and NI/MV) and market determined beta (covariance of security return with market portfolio) has been investigated by William Beaver and James Manegold (1975) and found that for a single security accounting beta explains 20% variation in the market beta hence accounting beta is one of the possible factors that explains systematic of the common stocks.
Thomas J. O'Brien and Paul A. Vanderheiden (1987) found a better way to know the firm’s DOL. They incorporate growth for sales and earnings in their model. They have found that growth opportunities and the firm’s implication of fixed and variable costs can affect the corporate risk.
Khaled Elmoatasem Abdelghany (2005) studied the accounting measures of equity beta i.e. systematic risk. The importance of accounting measures increases when there is unavailability of market historical data for the stock/share prices to estimate systematic risk. He divided risk into three categories namely financial risk, business risk and systematic risk in which financial risk is associated with the firm’s financial structure, business risk with asset structure and systematic risk with changes in the economic conditions. He analyzed many measures to explain systematic risk such as financial leverage, asset size, current ratio, earning variability and growth, dividend payout ratio and co-variability earning and found most of the variables statistically significant except earning to price ratio, covariance of earning and the financial leverage. He found statistically insignificant and negative relation of financial leverage with the systematic risk.
Dennis E. Logue and Larry J. Merville (1972) have suggested that the true beta of any firm is a function of financial policies, production policies, marketing policies and corporate policies. Because the financial policies reflect the impact of above mentioned therefore they limit their study to the financial policies. They have considered liquidity, leverage, investment and profitability to explain the systematic risk. They calculated financial leverage by Short term liability to total assets and by Long term debt to total assets and found it statistically significant in both measurements. The effect of financial leverage was found positive on the systematic risk beta. They also used the industry model i.e. they analyzed the results for homogeneous industries and found that in different industries different variables were significant which means that each industry is having different financial and operating characteristics.
Mark Brimble and Allan Hodgson (2007) assessed the risk relevance of the accounting variables, considered many variables such as dividend payout ratio, cash flow, interest coverage ratio, size, market to book value and operating and financial leverage etc. They used different procedures for beta estimation; operating leverage was statistically significant in all models whereas liquidity and dividend payout was insignificant in all of the models. In the financial measures financial leverage was insignificant in all of the models and hence failed to explain the systematic risk variation.
The studies cited suggest that the firm’s asset and financial structure, dividend policies and the firm’s size can affect the size of the risk which stockholders have to bear. The two types of leverages are considered as important risk determinants for the systematic risk in many researches done by the researchers. The choice of the asset mix and the financing mix can affect the systematic risk of the firm. The study is based on the determination of risk by the degree of operating and financial leverages as it is being suggested significant by the researchers, and to study the effect of corporate policies regarding financial and asset structure on the mix of two types of leverages and hence on the firm’s systematic risk.
CHAPTER 3: RESEARCH METHODS
3.1 Method of Data Collection
The secondary data is used in the study. The data for the share prices to calculate monthly return of the companies and KSE 100 index are gathered from the official website of the Karachi stock exchange. The annual data for the independent variables is collected through the annual reports and the State bank’s library.
3.2 Sampling Technique
The companies selected for the study are the non-financial companies in the KSE 100 index. The financial companies are dropped because their operations are influenced by many economic factors or their operations are more sensitive to the economic factors and the federal policies. The companies included in the sample are selected based on the following criteria
The financial statement data (annual reports) is available for the study period i.e. from 2000 to 2008.
The company must continuously being part of the KSE 100 index for the study period.
The stock prices are available on monthly basis for the study period.
The systematic risk (beta) is statistically significant.
There are currently 64 non-financial companies in the KSE 100 index. Seven companies had started their operations in mid of the study period therefore these companies are not taken into the analysis, for six companies data for the stock prices was not available and the systematic risk for five of the remaining companies was statistically insignificant. The rest of the 46 companies those fulfill all the above sampling conditions are taken under analysis.
3.3 Sample size
The study covered a period of 9 years starting from January 2000 till December 2008. The relationship between the systematic risk (beta) and DOL and DFL has been analyzed for 46 companies included in the KSE 100 index and validate the sampling conditions.
3.4 Research Model Developed
The dependent variable systematic risk (beta) is analyzed by multiple linear regression using degree of operating and financial leverage as independent variables. The model suggested by Gershon N. Mandelker and S. Ghon Rhee (1984) is used
Βi = γ0 + γ1DOLi + γ2DFLi + εi (i=1-46)
3.5 Statistical Technique
The effect of DOL and the DFL on the systematic risk was examined by multiple linear regression. Further to test the trade off effect between two types of leverage correlation was used. When all of the variables are scale and the objective is to predict the dependent variable by the independent variables then multiple regression is considered as an appropriate technique. Many of the previous studies also used the regression technique to predict the systematic risk like Mandelker and Rhee (1984), Mark Brimble and Allan Hodgson (2007), Uri Ben-Zion and Sol S. Shalit (1975) and William Beaver and James Manegold (1975).
If you are the original writer of this essay and no longer wish to have the essay published on the UK Essays website then please click on the link below to request removal:
More from UK Essays
- Free Essays Index - Return to the FREE Essays Index
- More Finance Essays - More Free Finance Essays (submitted by students)
- Example Finance Essays - See examples of Finance Essays (written by our in-house experts)
Need help with your essay?
We offer a bespoke essay writing service and can produce an essay to your exact requirements, written by one of our expert academic writing team. Simply click on the button below to order your essay, you will see an instant price based on your specific needs before the order is processed: