International Journal of Advanced Biotechnology and Research (IJBR) ISSN 0976-2612, Online ISSN 2278–599X, Vol-7, Special Issue-Number4-July, 2016, pp784-790 http://www.bipublication.com

Case Report

Investigating the influence of risk management on earnings volatility of the listed companies in Tehran stock exchange

Jafar Akbari1*, Fatemeh Samadi2 and Masoumeh Jafari3 1Department of Financial Management, Tehran East Branch, Email : [email protected] 2Department of FinancialManagement, Tehran East Branch Email : [email protected] 3Department of Governmental Management, Tehran East Branch, Islamic Azad University, Tehran, Iran Email : [email protected] Corresponding author is Jafar Akbari

ABSTRACT This invetigation aims to examine the impact of risk management practices on earnings volatility of the listed companies in Tehran stock exchange. All listed companies in Tehran stock exchange were selected as the statistical population of the research during 2005 to 2015. Risk management, liquidity risk management and operational risk management, and earnings volatility were selected as the independent and dependent variables of the study, respectively. Dechow & Tang (2008) model is used for measuring earnings volatility in this research. 130 firms were selected as the statistical population based on the systematic elimination method. The obtained results show that risk management doesn’t impact on earnings volatility. As well, liquidity risk management significantly and negatively impact on earnings volatility, and operational risk management positively and significantly influence on earnings volatility.

Keywords: Risk management; Liquidity risk management; Operational risk management; earnings volatility.

1. INTRODUCTION Risk management is an evaluating risk process Risk management enables manager to and designing strategies for identifying risk. effectively run a business unit, despite of risk Researchers believe that risk management of a and its dependent opportunities in order to business unit is essential for reducing general increase the capacity of creating firm value. In risk of a firm's bankruptcy, for improving recent years, risk management has been performance, and finally for increasing firm increasingly developed, especially due to the value. Agency risk management is a dynamic current regulations persuade banks to enhance approach of measuring integrated risk by which and control their risk managements (Alzula, organizations decrease their risk level (Bushman 2003). Managers deal with risks in almost all & Zuiden). Having established agency risk organizations. They adjust organizational management, a firm is enabled to regularly investment risk versus its potential return, and measure risks and identify the required manage risks in an organization's portfolio resources and stages to overcome or reduce risks practices and investments, regarding strategic (Funstan, 2003). The main defualt of risk considerations. However, staffs and management is that each business unit is management in an operationallevels of an established to create value for its stakeholders. organization focus usually on a kind of a risk Investigating the influence of risk management on earnings volatility of the listed companies in Tehran stock exchange

management titled with "operational risk". As management results in earnings management staffs and management implement business accuracy and decreased forecast error, and processes, operational risks start to emerge. The controls earnings volatilities. Therefore, available defect in processes' esence may result liquidity risk management results in decrased in inefficieny and problems during the earnings volatility. Berry & Xu (2013) examined operation, and possible undesirable effects may how risk management and earnings volatility also seen in the organization success (Chelik et have correlated and concluded that there was a al, 2012). Generally, risk management looks for negative and significant relationship between the recognizing the risk possibilitis and risk two factor. tolerance. It can be seen in risk litrature that risk Jumnez & Delkato Garcia (2012) examined the management results in decreased earnings relation between risk management and firm volatility (Beasley et al, 2008; Gordon et al, performance of Spanish firms during 2000 to 2009). This is one of the major advantages of 2005. They concluded that there was a risk management, because risk management significant relation among risk management and ables to decrease the related to firms' firm performance of Spanish cases. financial distress. The cost of firms' financial Li et al, (2010) investigated the relation between distress is a potential value in improving risk earnings manipulation and systematis risk in management implementation characteristics. Banking industry. According to the their The current investigation followed by Edmonds research, there is a significant relation between et al, (2015) examined how risk management earnings manipulation and banks' systematic affect earnings volatility. The results suggested risk. The results also suggested that risk that increased quality of risk management management results in decreased earnings practices result in decrased earnings volatility. volatility. Hutton et al, (2009) investigated the Edmonds et al, (2015) found that the economic relation between earnings management and impact of risk management is highlighted more managrial risk-taking and concluded that than for loss-making and financially-distressed managerial risk-taking in banks has significant firms. Therefore, the main issue in current relation with manipulation, as a result, research is how risk management affect earnings there is a significant relation between volatility of the listed companies in Tehran stock managerial risk-taking and earings management. exchange. 3. Research methodology

2. Research background 3-1- The research hypotheses Edmonds et al, (2015) examined the relation 3-3-1- The primary hypothesis between risk management behavior and earnings  Risk management significantly impact on volatility of firms. Their results suggested that earnings volatility of the listed companies in high quality implementation of risk management Tehran stock exchange. system results in decreased earnings volatility. 3-1-2- The secondary hypotheses Kelab & Wou (2014) investigated the relation  Liquidity risk management significantly between earnings volatility and earnings forecast impact on earnings volatility of the listed capability in English and American firms. They companies in Tehran stock exchange. examined 341 cases during 1991 to 2010 and  Operational risk management significantly concluded that there is a negative and significant impact on earnings volatility of the listed relation between earnings forecast capability and companies in Tehran stock exchange. earnings volatility in English and American 3-2- Research method firms. Ittner & Michels (2014) examined the The current study is a kind of practical research relation between liquidity risk management of a in terms of a goal. If we consider researches business unit and earnings management forecast based on nature and method, the current study is of the listed companies in U.S stock exchange. a kind of descriptive and non-experimental The results shown that liquidity risk (field and survey research). Meanwhile, library

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and field method are used as a inseparable part  5Levit  6Sizeit   itit of scientific researches in this study. 3-3- The statistical population and sample 3-4-2- The regression model of the second The population of the research includes all listed secondary hypothesi companies in Tehran stock exchange during EarningsVolatility  2005 to 2015, followed the below conditions: it    OR   Cf   GI   Na 1. The firm should be listed before 2005. 0 1 it 2 it 3 it 4 it

2. Its should end in 19/3 on each  5Levit  6Sizeit   it year. 3-5- Data analysis method 3. The firm should not change its fiscal year To estimate the efficiency of a regression model, during the study. inn this research, one the common effects, fixed 4. Banks, insurance and investment companies effects and random effects model is selected are not considered. using panel data by suitable test. F-Limer test is 5. The firms' data should be available. used for selecting between common effects and 130 firms were selected as the statistical fixed effects methods. population of the research based on systematic If fixed effects model is selected, Hausman test elimination mehod. would be used to select among fixed effects and 3-4- The regression model random effects models. Also, model’s error term 3-4-1- The regression model of the primery autocorrelation, heteroskedasticity and data hypothesis normality would have been examined.

EarningsVolatilityit  To illustrate the description power of descriptive variables, to examine the significance of 0  1RiskManagementit  2Cfit  3GIit variables and to investigate the adequacy of   Na   Lev   Size   4 it 5 it 6 it it whole model, adjusted coefficient of 3-4-2- The regression model of the first determination, T-statistics and F-Fisher test are secondary hypothesis used, respectively.

EarningsVolatilityit  As well, statistical analyses are done through EVIEWS 7 and EXCEL software.  0  1LRit  2Cfit  3GIit  4 Nait 4- RESULTS 4-1- Multicolinearity Table 1-1- Pearson correlation test Operational risk Risk Liquidity risk Variables management management management Operational risk management 1.000000 Risk management -0.012778 1.000000 Liquidity risk management 0.067299 -0.016356 1.000000

According to the table 1-1, there is no high or low (close to +1 and -1) correlation coefficient influencing the results of the regreson aalysis. As a result, there is no multicolinearity between the variables of the research. 4-2- Significance test of fixed affects method Table 1-2: F-Limer test Description Statistics amount Freedom degree Probability Cross-section F 2.278308 129 *0.000 Cross-section Chi-square 292.685670 129 *0.000 * 5% error level Table 1-3- Hausman test Description Statistics amount Freedom degree Probability Cross-section F 12.730918 6 *0.0475 * 5% error level

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Regarding the results of both table (F and Hausman), the obtained probability were less than 5% in each tests, so fixed effects method should be used in the related regression model. 4-3- Dickey-Fuller test Table 1-4- Test of cumulative unit root test on variables by Dickey-Fuller Variables Statistics Probability Earnings volatility -11.403 *0.0000 Risk management -14.357 *0.0000 Liquidity risk management -31.08 *0.0000 Operational risk management -15.601 *0.0000 flow -10.816 *0.0000 -33.755 *0.0000 Fixed assets -14.63 *0.0000 Financial leverage -15.242 *0.0000 Firm size -17.487 *0.0000 * 5% error level According to the table 1-4, the examination of calculated statistics and their acceptance probability indicates that H0 is rejected and all variables of the study are durable. 4-6- The primary hypothesis test Table 1-5- The regression test of the primary hypothesis Estimated Estimation of Significance Variable t-statistics coefficients deviation level Fixed 3.376474 0.563119 5.996018 0.0000 Risk management 0.000877 0.000904 0.970935 0.3318 0.615313 0.265736 2.315505 0.0207 Dividend 0.00446 0.277517 0.008815 0.9930 Fixed assets 0.130293 0.295948 0.440257 0.6598 Financial leverage -0.036433 0.221714 3.807712 0.0001 Firm size -0.036433 0.034688 -1.050323 0.2938 * 5% error level Table 1-6: Description and significance ability of whole model R2 ANOVA Adjusted Coefficient of Sig F DW coefficient of determination determination **0.000 25.69610 1.73 0.828 0.859 ** 1% error level Regarding the table 1-5, since Durbin-Watson statistic test value is determined among 1.5 to 2.5, there is no correlation between errors and regression can be used. The adjusted coefficient of determination is 0.828; indicating 82.8% of all earnings volatilities depend on the independent and control variable. On the other hand, due to significance level of F-test in error level less than 0.01, it can be concluded that the regression model is a suitable model and the independent variable are able to firms' earnings volatility changes. Estimated impact factor of risk management on firms' earnings volatility is -0.001, suggesting risk managementnegatively and adversly impacts on earnings volatility. Also, according to significance level of t-statistics, and due to the amount of risk management on (0.3318) is more than 5% error level, , H0 is confirmed with 95% confidence level. It can be stated that, risk management doesn’t significantly impact on earnings volatility of the listed companies in Tehran stock exchange.

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4-7- The first secondary hypothesis test Table 1-7- The regression test of the first secondary hypothesis Estimation of Significance Variable Estimated coefficients t-statistics deviation level Fixed 3.317797 0.568415 5.836926 0.0000 Liquidity risk management -0.133338 0.020207 -6.598675 0.0000 Cash flow 0.615091 0.255929 2.403370 0.0164 Dividend 0.014258 0.284932 0.050041 0.9601 Fixed assets 0.142202 0.286865 0.495710 0.6262 Financial leverage 0.756830 0.239004 3.166599 0.0016 Firm size -0.02069 0.034888 -0.593268 0.5531 *5% error level Table 1-8: Description and significance ability of whole model R2 ANOVA Sig F DW Adjusted coefficient of Coefficient of determination determination **0.000 28.88545 1.7 0.75 0.82 ** 1% error level Regarding the table 1-7, since Durbin-Watson statistic test value is determined among 1.5 to 2.5, there is no correlation between errors and regression can be used. The adjusted coefficient of determination is 0.75; indicating 75% of all earnings volatilities depend on the independent and control variable. On the other hand, due to significance level of F-test in error level less than 0.01, it can be concluded that the regression model is a suitable model and the independent variable are able to firms' earnings volatility changes. Estimated impact factor of liquidity risk management on firms' earnings volatility is -0.133, suggesting liquidity risk management negatively and adversly impacts on earnings volatility. Also, according to significance level of t-statistics, and due to the amount of liquidity risk management on earnings quality (0.000) is more than 5% error level, , H0 is rejected with 95% confidence level. It can be stated that, liquidity risk management significantly and negatively impact on earnings volatility of the listed companies in Tehran stock exchange.

4-8- The second secondary hypothesis test Table 1-8- The regression test of the second secondary hypothesis Estimated Estimation of Significance Variable t-statistics coefficients deviation level Fixed 2.484692 0.744735 3.336345 0.0009 Operational risk management 3.782492 1.623217 2.330245 0.0199 Cash flow 0.597255 0.266014 2.245199 0.0249 Dividend -0.026045 0.279512 -0.093181 0.9258 Fixed assets 0.072332 0.297654 0.243006 0.8080 Financial leverage 0.782185 0.221978 3.523704 0.0004 Firm size -0.030247 0.032845 -0.920898 0.3573 * 5% error level Table 1-9: Description and significance ability of whole model R2 ANOVA Sig F DW Adjusted Coefficient of coefficient of determination determination **0.000 26.63553 1.7 0.83 0.86 ** 1% error level Regarding the table 1-8, since Durbin-Watson of determination is 0.83; indicating 83% of all statistic test value is determined among 1.5 to earnings volatilities depend on the independent 2.5, there is no correlation between errors and and control variable. On the other hand, due to regression can be used. The adjusted coefficient significance level of F-test in error level less

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