DETERMINING THE OPTIMAL MODEL FOR THE PREDICTION OF OPERATING CASH FLOW OF COMPANIES LISTED IN TEHRAN STOCK EXCHANGE

Abstract

Journal of Accounting Advances (J.A.A) Vol. 2, No. 1, Summer 2010, Ser. 58/3 Extended Abstract Determining the Optimal Model for the Prediction of Operating Cash Flow of Companies Listed in Tehran Stock Exchange Dr. G. Mahdavi M. Saberi Shiraz University FiroozAbad Islamic Azad University Introduction The main purpose of this study is to determine the optimal model for the prediction of operating cash flows of companies listed in Tehran Stock Exchange. Investors, creditors and other users of accounting information need the cash flow information for decision making. A firm’s ability to generate cash flows affects the values of its securities. Operating cash flow is the principal and perpetual part of company’s cash flows. In the prior studies, different models have been tested to predict future cash flow from operation. The differences between these models are related to the use of different independent variables. Previous research on earnings and cash flows ability to predict future cash flows in Iran has examined only two or three models and some of them have examined those models at firm-level. This study examines six models to predict future cash flows. Firstly, research hypotheses have been tested for the all firms as a whole and secondly they have been tested for various industries. The results suggest that disaggregating earnings into cash and accrual components increases predictive ability of future cash flow. Also, the results imply that the cash flow prediction model that is based on disaggregating earnings into six cash and major accruals components, can predict operating cash flow better than other models. Research Hypothesis Given the purpose of this study, in this research, six following hypotheses are developed and tested by using data gathered from 73 Iranian companies listed in Tehran Stock Exchange (TSE) for the period 1997 to 2006: A significant relationship exists between “the historical operational earnings” and “future operational cash flows”. A significant relationship exists between “the historical disaggregated operational earnings into cash and accruals components” and “future operational cash flows”. A significant relationship exists between “the historical disaggregated operational earnings into cash and major accruals components (including operational cash flows, change in accounts receivable, change in inventories, change in accounts payable, depreciation and other accruals)” and “future operational cash flows”. A significant relationship exists between “the historical operational cash flows and Nondiscretionary accruals and “future operational cash flows”. A significant relationship exists between “the historical operational cash flows and discretionary accruals” and “future operational cash flows”. A significant relationship exists between “the historical operational cash flows and discretionary accruals and Nondiscretionary accruals” and “future operational cash flows”. Methods Post event inquiry researches have been used in this study (using historical information). For statistical analysis and to test hypothesis, descriptive statistics (mean and standard deviation) and inferential statistics (correlation-test, single and multiple linear regression and analysis of variance) are used. The six following models are used to test six hypotheses: = α + EARN + (1) = α + OCF + ACCR + (2) =α + OCF + ΔAR + ΔINV + ΔAP + DEP + OTHERS + (3) (4) (5) (6) Where: OCF = Operating Cash Flows EARN = Operating Earnings ACCR = Accruals ΔAR = Change in accounts receivable ΔINV = Change in inventories ΔAP = Change in accounts payable DEP = Depreciation OTHERS = Accruals – (ΔAR+ ΔINV+ ΔAP+DEP) Results The results of statistical tests for the period 1997 to 2006 show that there is a meaningful relationship between independent variables and dependent variable in all hypotheses and all six models are able to predict future operational cash flows. Discussion and Conclusion According to the results, we find disaggregating earnings into cash and accrual components increases predictive ability of future cash flow. Also, the results imply that the cash flow prediction model that is based on disaggregating earnings into six cash and major accruals components (model No. 3), can predict operating cash flow better than other models. By testing the hypotheses in the industries-level, we find that ability of models in various industries is different. Our research provides evidence to confirm FASB’s stated objectives that information about earnings and its components is useful to predict future cash flows.