Studying the Relationship between Financial Variables and Securities Risk

Transcription

1 Studying the Relationship between Financial Variables and Securies Risk Behnam Gilaninia 1, Shahram Gilaninia 2, & *Asghar Asadi 3 1 Department of accounting, Science and Research Branch, Islamic Azad Universy, Ghazvin, Iran, 2 Department of Industrial Management, Islamic Azad Universy, Rasht Branch, Rasht, Iran, 3 Department of Business Management, Science and Research Branch, Islamic Azad Universy, Guilan, Iran *Corresponding Author Abstract The studies also suggest that calculated risk based on accounting data are appropriate substute for calculated risk based on market data. Currently one of the problems for investors and other active groups in the Iranian capal market is calculating risk of out of stock companies. Since no market for these companies are structured and organized, as a result Calculating risk of these securies is not possible due to lack of access to market data. Even many listed companies have no active market, as a result there is no possibily to calculate risk. For some of the listed companies due to inadequate market data currently calculating risk is not possible. While financial accounting data are important to measuring risk, accounting data can be used to provided a model to measuring risk and mentioned model can be appropriate substute for measuring risk by using the market data. Problem of calculating risk for out-of-stock companies and even many of listed companies & objective expressed by accounting standards commtee is of main motivation for researchers to examine the usefulness of financial accounting data of securies in risk assessment. 1. Introduction About the relationship between accounting and financial variables wh risk much research has been conducted by researchers. One of the first empirical research in this field that can be ced is studied by Beaver, et al They studied relationship between financial accounting data and the systematic risk Which was calculated according to market data,. Beaver and colleagues in their study used of accounting and Financial Information of 307 companies in the New York Stock Exchange between 1947 and Accounting and financial data that were analyzed by them were including dividing the prof policy, asset growth, financial leverage, liquidy and firm size, earnings variabily and accounting beta. Result of their study showed that there is a posive relationship between asset growth, degree of leverage, earnings variabily and the company's beta (systematic risk) and there is a negative relationship between prof Sharing policy (The ratio of cash earnings paid), liquidy, firm size, wh the company's beta. Findings of Beaver and colleagues is suggests that by using accounting and financial data a model for measure risk can be presented. Beaver and colleagues also concluded that in measuring the market risk model that is based on accounting data can measure risk more accurate than model that is only based on past market data examined the abily of predict the systematic risk using accounting data between 1963 and 1975.He investigated eight creria that accounting risk, according to previous experimental and theoretical studies were important in measure systematic risk. His study was in fact a re-test to predict the market risk by using a model that was based on accounting data. Eskew Study results showed that models based on accounting data predict next level of market risk better than models 22

2 based on past market data alone. Farrelly, Ferris and Reichenstei 1985 by gathering accounting information of 25 companies during a 5-year period examine the relationship between accounting data and systemic risk. Accounting and financial variables in their study of prof sharing policy were, the company's growth, financial leverage, liquidy, firm size and earnings variabily. Results of their study showed that 79% of changes in systemic risk are related to mentioned accounting variables. Namazi and Khajavi (1383) in a research were examined usefulness of accounting variables in prediction of systematic risk in the companies listed in Tehran Stock Exchange. To do their research they selected 40 companies listed in a period of 11 years (80-70). Their results showed that there are significant negative relationship between the liquidy ratios and profabily ratios wh systematic risk index and by increasing liquidy ratios, profabily systematic risk decreases and vice versa. Their research also showed There is a significant posive relationship between leverage ratios, financial leverage and operating leverage wh systematic risk index, wh increasing this variables systematic risk also increases. 2.The variables of study: A - independent variables Independent variables in this study are including accounting and financial variables and beta description of each of them will be discussed below. Company growth: Company growth is one of factors and variables to determine the price of securies and therefore their risk. Researchers to measure the growth use of various creria such as growth in total assets, fixed assets growth, sales growth and gross prof growth. In this study, fixed assets of the company as an indicator of firm growth has been considered. Increase in fixed assets is introducing the new investment by the business un.as a result is appropriate creria that can measure growth. Method of calculating the company's growth is as follows: ( Growth) ( FixedAssets ) ( FixedAssets ) ( FixedAssets ) 1 (Growth) = growth of company i in year t, (Fixed Assets) = fixed assets of company i in year t 1 Firm size: It is often argued that whatever companies be larger in terms of funds owners and capal market has more credibily, therefore, will have more and better access to external funds, even wh the lower interest or will have saving resulting from the scale. Whereas whatever company possess smaller size, capal markets and cred Loan organizations give lower cred to them and therefore business un have lower and more limed access than the previous mode to external funds and capal markets even financial instutions set higher interest for them. Also the study conducted by Fama and French, 1995 showed there are a relationship between firm size and efficiency of securies. Keim, 1983 and Ringanum, 1983 reached to similar findings. To calculate the size variable of different creria such as logarhm is used of market value, rights of shareholders of company, logarhm of total assets of the company, logarhm of total sales. 23

3 In this study according to the condions of capal market and the effect of inflation on firms is used of logarhm of sales as an indicator. Prof dividing policy: A company's earnings policy affect on company's risk and return and subsequently the company's stock price. Many research have been done on prof dividing policy Ferris and Reichenstein1993 in their article pointed to several examples of this kind. Among these researches studies of Lzenberger, 1970 can be mentioned. Results of this study suggest that there is a relationship between the returns and earnings policy and whatever paid interest rate be more returns of company will increase and therefore risk will increase. Another research on prof dividing policy is research of Ahmadpur and Namazy (1383) this has been done in a period of 11 years (80-70) and one of the factors examined in this study was distribution of profs and s correlation wh systematic risk. The results of this study indicate that there is an inverse relationship between the distribution of prof and risk indicators. Means whatever percentage of prof distribution increased systematic risk is decreased. The present study is sought to find the relationship between risk and prof distribution policy.the following ratios have been used to assess the earnings policy: DPS EPS. (Pay out) = ( Pay out) = the percentage prof distribution of company i in year t, DPS = Dividends paid per share in year t and firm i EPS = = earnings per share in the company i in year t, Earnings variabily: No doubt that corporate profs will change wh changes in overall economic activy. Of course for predicting better profs analyst must analyze several factors such as economic condions - the country's polical status, the relevant industry, company's development plans and management capabilies. In this study, for measuring rate of earnings variabily per year prof from the beginning of each year is calculated and the company's total assets are homogeneous and then homogenized earnings variance for a three-year period. Var E= Var[( Where: Earning )و )-2 Earning )-1,( Earning Var E = earnings variabily of company i in year t Earning = homogeneous profs of company i in year t Corporate liquidy: liquidy is the relationship between cash that is provided for company in the short term and the cash that a company will need. The main objective of company is desirable liquidy management. Some researchers, such as Beaver, Kettler and Scholes (1970) showed that the amount and composion of company liquidy will cause changing the risk and return )] 24

4 of company. So managers should take the policy that according to company suation from different dimensions like company growth and development, mode of company activies and... determine the amount of working capal (liquidy) to be desirable. Researchers have proposed various indexes to measure corporate liquidy. Sample of these indexes that can be ced are current ratio and quick ratio index,. In this research the company current liquidy measure is used. (Current Assets) (Liq) = (Current liabilies) (Liq) = liquidy ratio of company i in year t, (Current Assets) = current assets of company i in year t, (Current liabilies) = current liabilies of company i in year t, Financial leverage: Financial leverage indicates that what percent of total assets are financed through liabilies. Credors prefer low liabilies ratio, because if this ratio be high usually company will be at high risk too Thus, It can be said this ratio measures the power of fulfillment of obligations (Debt) from company and what goes up will increase the company's bankruptcy risk. there are several indexes to measure financial leverage. The ratio of debt to total assets, debt to equy ratio and the company's debt ratio to market value can be mentioned. In this paper ratio of debt to total assets is used to measure financial leverage which is as follows: (Total Debts) Lev = (Total Assets) Lev = Financial leverage of company i in year t, (Total Debts) = Total debt of company i in year t, (Total Assets) =total assets of company i in year t Beta: one of the most important models used to calculate the systematic risk is a single-index model. In this research single-index model is used to calculate beta R R e i i mt In the above formula real return on company i in period t, is systematic risk of company i, returns of market in periods t abnormal return of company i in period t. It should be noted that to calculate beta that is introducing systematic risk of company has been used of previous 36 months returns of company and market. How to calculate corporate returns And the market return are also explained. The following formula was used to calculate the monthly returns of companies: ( 1 )* P P 1D M R P 1 25

5 Where: R = Stock return of company i in month t, P = Price of share in company i in month t, = Ratio of capal increase the company i during month t, D = Dividends Cash of the company at the end of month i = t, and M =. Earnings pash per share to shareholders To calculate the monthly return of market inially cash return index at market prices (TDP) Tadbirpardaz software extracted then following formula based on market returns were obtained R mt TDP TDP TDP 1 1 R mt = Monthly return of market in the end of month t TDP = Cash returns index and price at the end of month t, After obtaining the monthly returns of market and company, by using EXEL software beta of company, has been calculated. Thus, according to the method described in each year And for each company is calculated separately 3- The dependent variable and way of calculate dependent variable risk premium (based on accounting data is examined hypotheses according to the relationship between accounting data wh the beta risk, as a result risk premium is the dependent variable for Hypothesis 7, since investors use of the company's accounting data for predicting the future risk in this study is used of Gordon model to calculate the the risk.expected return based on Gordon model is as follows: ER D P 1 t g ER = Expected return on firm i In year t, D 1 = Cash dividend, P t = Share price at time t, g = Rate of company growth. Growth rates of company is calculated by multiply return of equy in percentage of the profs that is not distributed among shareholders RP ER RF t Where: RP = The risk premium of company i in year t, ER = Expected return of company i in year t, RF t = Risk-free rate of return in year t. 26

6 4-Coclusion Accounting standards commtee (1994) states that one of the objectives of financial reporting is enable investors, credors and other users of financial statements for reliabily assessment,or risk associated wh the future cash flows of a sheet of exchange. The same Beaver Kettler and scholes, 2007 argue that we can't Hopes to make an accounting system whout understanding the interrelationships between accounting data and market variables or evaluation of existing systems based on a decision crerion. So the stated purpose by standard makers the information provided should be useful in assessing risk and return of securies by users outside the organization. Whether this goal is considered now, is the focus of this study. So far, many attempts have been made to provide a model to measure risk. Such models can be noted is capal pricing asset model (CPAM). Capal asset pricing model measures according to an agent means market efficiency risk. Farrelly,Ferris and Reichenstein 2005 and Cooley 1997, Farrelly and Reichenstein,1984 have said that using a measure of risk measurement is not suable, several factors are involved in risk securies. Therefore, several studies have been done to provide multi-factor model in order to predict risk. Researchers that can be mentioned are Fama and Fren and Beaver,et al 2007,some of researchers, such as Fama and Frnch, used of accounting and market data to measure the risk and researchers such as Ferris and Reichenstein1998 only used of accounting data to measure risk. Studies in western countries indicate that accounting data, such as growth, firm size, financial leverage, earnings volatily, cash earnings policies in the risk assessment of securies are important. By using the above variables risks can be measured. References 1 - Ahmed Ali, Ahmad and Mohammad Namazi (2001), Journal of Madras, the effect of operating and financial leverage on systematic risk and firm size (firms listed on the Stock Exchange), Spring 77, No. 6, pp Namazi, Mohammad and Shokrollah Khajavi (2005) accounting investigations, the usefulness of accounting variables in predicting systematic risk firms listed in Tehran Stock Exchange, the eleventh year, No. 38, pp Sinai, and Ismail Hasan Ali Khorram, (2006), financial research, financial leverage associated wh the systematic risk of common stock () public companies in Iran, Year VI, No. 18, pp Beaver, W,. Kettler, P., and Scholes, M. (2007). "The Association Between Market Determined and Accounting Determined Risk Measures." Accounting Review (October), Cooley, PL (2007). "A Multidimensional Analysis of Investor Perception of Risk". Journal of Finance (March), Elgers, PT (2008). "Accounting-Based Risk Predictions: Are examination." Accounting Review (July), Eskew, R. K (2009). "The Forecasting Abily of Accounting Risk Measures: Some Addional Evidence." Accounting Review (January), Farrelly, G. E., Ferris, KR, and Reichenstein, w. (2005), "Perceived Risk, Market Risk, and Accounting Determined Risk Measures." Accounting Review, (April), Kenneth R. Ferris and William Reichenstein (2009), "An Investigation Of The Usefulness Of Accounting 27

7 And Financial Data In The Assessment Of Secury Risk." Advances In Quantative Analysis Of Financial And Accounting, Volume2, part a, Pages