Managements Expectations About Future Cash Flows Finance Essay
Financial analysts did not rely upon CF analysis; Analysts view it as an important supplementary tool useful in avoiding misleading inferences in the patterns of accrual based earnings numbers Dorfman (1987).
The magnitude of abnormal returns associated with good or bad news earnings signals is inversely related to firm size Freeman (1987) and speculated that findings might simply be due to differential time series properties of the earnings numbers of large and small firms an uncontrolled factor in research design and calls for future research to examine the possibility. The empirical evidence on the importance of the size effect in the above settings, led to consider whether controlling explicitly for firm-size leads to inter-firm differences in predictive ability.
Theoretical and empirical work in accounting and finance has documented the importance of firm size when testing the information in security prices with respect to future earnings (Collins, Kothari and Rayburn 1987) and interested in assessing the information in security prices with respect to the predictive ability of earnings and found that that price based earnings forecasts outperform time series forecasts by the greater margin for the larger firms than smaller firm is of direct interest here. The study result implies that firm-size may help to explain inter-firm differences in the predictive ability of quarterly earnings data and helps to motivate the consideration of firm-size as an independent variable in the current study.
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Freeman (1987) provided evidence that the magnitude of abnormal returns associated with good or bad news earnings signals is inversely related to firm-size. Freeman speculated that the findings might simply be due to differential time series properties of the earnings numbers of large and small firms an uncontrolled factor in research design and calls for future research to examine the possibility.
Brown, Griffin, Hagerman and Zmijewski (1987) compared the accuracy of analysts to time series models based on historical earnings data. The attribute analystsââ‚¬â„¢ superiority to a timing advantage (more information was publicly available if the forecasts were made after the public announcement dates) and an informational advantage (more information is used by the analysts than historical earnings data).
Barth, Cram & Nelson (1986) studied the role of accruals in predicting future cash flows. Findings proved that disaggregating earnings into cash flow and the major components of accruals significantly enhances earnings predictive ability, findings also showed relation between cash flow next year and current cash flow and each component of accruals is significant and has a sign consistent with prediction.
The relationship between the earnings forecast error and predictability earnings because one of the evidence suggested that earning forecast optimism was not an effective mechanism for the gaining access to manager information ( Eames, Glover and Stice. 2001; Matsumoto 2002), earnings level to be an important control variable in examination the association between forecast error and earnings predictability, a lot of studies report an inverse relation between forecast error and the level of reported earnings (Brown 2001, Eames, Glover and Stice 2001, Eames and Glover 2002, Hwang, Jan and Basu 1996). This relationship reflects the earnings shocks and that was due to unanticipated events and earnings management.
Olsen and Dietrich (1985) demonstrated that the monthly sales announcements of major department and discount stores provide information for investors not only for the retail giants but also for their suppliers. The sales volume announcements for the retailers furnish information on the future cash flow prospects for their suppliers and, thus incorporated into the suppliersââ‚¬â„¢ share prices. Dharan (1987) investigated the comparative abilities of accrual sales and cash collections of sales to predict future cash flows and showed that, when cash realization occurs in a period subsequent to sales realization, cash flow forecasts from earnings based on accrual sales are better than cash flow forecasts from earnings based on cash collections. This is because accrual sales ââ‚¬Å“provide information on managementââ‚¬â„¢s expectations about future cash flows.
Greenberg, Johnson, and Ramesh (1986) used 1963-82 compustate data to test the ability of earnings and CFFO to predict future CFFO, for each firm two separate ordinary least squares regression models were used. The first model test used previous earnings against current CFFO (earnings model) and the second model used CFFO for lags of 1 to5 years against current CFFO (cash flows model).R square for the earnings and cash flows model were compared and the model with the higher R square was determined to be the better predictor. The results showed that earnings outperformed CFFO in predicting future CFFO and concluded that the study provides evidence in support of the FASB's assertions that the current earning was a better predictor of the future cash flows than was the current cash flows.
Similarly a supporter of Greenberg, Johnson, and Ramesh's (1986) similar previous findings found by Murdoch and Krause (1990) as well, however, the Singaporean study by Austin and Andrew (1989), whose approach was similar to that of Greenber, Johnson and Ramesh (1986) found that neither earnings nor CFFO proved to be superior in predicting future CFFO.
Bowen, Burgstahler and Daley (1986) examined relationships between signals provided by accrual earnings and various measures of cash flow, Findings indicated that Correlations between traditional cash flow measures and alternative CF measures that incorporate more extensive adjustments are low, 2nd the correlations between alternative measures of CF and earnings are, while the correlations between traditional measures of CF and earnings are high. These first two results were consistent with earnings and alternative measures of CF that incorporate more extensive adjustments conveying different signals. Finally, for four out of five cash flow variables, the results were consistent with the hypothesis that random walk models predict CF as well as model based on the other flow variables. An exception to this general result was that net income plus depreciation and amortization and working capital from operations appear to be the best predictors of cash flow from operations. Overall there results were not consistent with the FASB's statements that earnings numbers provide better forecasts of future cash flows than do cash flow numbers.
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The firm size independently explained a substantial portion of the variation in post announcement drifts in security returns due to potentially misspecified quarterly earnings expectation models Foster, Olsen and Shevlin (1984). (Ball and Watts 1972, Albrecht, Lookabill and McKeown 1977, Watts and Leftwich 1977 and Lev 1983 studied the Earnings ability to predict future earnings studied first or second order autocorrelations and or forecasts over one or two-year horizons and provided evidence to support a random walk model that is uncorrelated earnings changes, However, random walk may not be descriptive of the earnings process whereas Ramesh and Thiagarajan (1989) rejected a random walk earnings model and Lipe and Kormendi (1993) showed that higher order, rather than random walk, models are descriptive of market-adjusted earnings' time-series process. The magnitude of abnormal returns associated with good or bad news earnings signals is inversely related to firm size (Freeman 1987), speculates that these findings might simply be due to differential time-series properties of the earnings numbers of large and small firms-an uncontrolled factor in his research design-and calls for future research to examine the possibility.
Earlier additional information content of cash flows relies primarily on cross sectional regression models relating both earnings and cash flows to security return metrics that assumes a uniform relation between earnings (cash flow from operations) and security returns across observations. Ali (1994) however, conditions the incremental information content of unexpected earnings and cash flows from operations on their magnitude with respect to price and Ali (1994) found that changes in earnings (cash flows from operations) are not expected to persist and thus have reduced implications for returns.
Dechow and Dichev (1986) found out the new method of measuring working capital accruals and the earnings and illustrated the usefulness of analysis in two ways. First, Dechow and Dichev (1986) examined the relation between measuring the accrual quality and its firm characteristics. The process of accrual suggested a magnitude that estimate errors systematically related to business fundamentals as variations in the operation cycle and its length and Dechow and Dichev (1986) concluded accrual quality was negatively related to accrual of absolute magnitude, operating life cycle, loss incidence, sales of standard deviation, cash Flow, accrual, earning had a positive relationship with firm and its size. Dichow and Dichev concluded that the firm characteristics could be use as the instrument of accrual and its quality, accrual and their qualities which were depended on regression demanded a long time series of the data, and the cash flows estimation of accrual that it is making costly and infeasible for its practical application. Secondly this study illustrated the usefulness of analysis by the surveying the relationship between measuring the accrual and its quality earnings persistence. Those firms which have low accrual and its quality with low accrual quality and more accruals those were unrelated to cash flow realizations so it produced further noise, less persistence in the findings. In fact Dechow and Dichev (1986) found strong and positive relationship between the accrual and its quality earnings persistence as well though the quality of accrual was hypothetically, and related to magnitude of absolute accruals.
Sloan (1996) recognized that accruals levels were less a persistent then the cash flows and found that the accrual and its quality level were incremental each other in describing earnings persistence, with the accrual and its quality had more powerful determinant.
There were two widely held views about the motivation of management to managing and the each had quite different implications regarding the predictive usefulness of the resultant numbers .There are different views one of them view was earning management was motivated by the managers that attempted to sustained the stock prices and enhanced by using their personal funds to boost the economic performance of the firm. Managers manage earnings to reveal relevant information about the future prospects of firms. They showed that the earnings firms were classified into managing earning for the positive reasons and not much predictive future cash flow related to numbers and found that the firms earnings has been classified as managing earning as the reasons exhibited greater predictive abilities of future cash flows that related to restated numbers. (Collins and Lys 2007).
Cheng and Dana (1996) studied persistence of cash flow components in the predicting future cash flows and the findings were components of cash flow from operating activities were persist differently. Findings were that the cash that was related to net sales, Cost of goods sold, operating expenses and interest has a grater impact on future cash flows, and about cash related to others has lower persistence and taxes had no persistence then they incorporated accrual components into regression model, found cash flow components were higher than accruals that however did not enhance performance of model as well, results were consist with ACCPA that cash flows should be distinguished.
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Bowen, Burgstahler and Daley (1986) predicted CF from operations one and two years into the future by employing a set of alternative predictor variables including current net income, net income plus depreciation, working capital from operations and past values of CF from operations. Bowen, Burgstahler and Daley confined data analyses to annual numbers and employed a limited set of simple linear forecasts and did not attempt to identify multivariate CF prediction models. The study found that the differences in relative forecast errors of the net income and CF from operations predictor variables were not significant none of this study results were consistent with the FASB's assertion of the superiority of earnings as predictors of future cash flows. However the use of relatively short, annual data bases in conjunction with naive expectation models limits the generalizability of this study.
Lev (1983) examined cross sectional relationship between the set of economic characteristics and the first and second order autocorrelation coefficients of earnings changes, return on equity changes, and sales changes. The main objective was to see if characteristics of the studied time series were related to the firm's economic environment. Lev finding that there was associations between characteristics of the firm's economic environment and the first two autocorrelation coefficients in earnings changes can be viewed as consistent with result that a persistence measure from a higher order (2,1,0) ARIMA model of earnings is associated with the characteristics of the firm's economic environment.
Brooks (1981) compared the predictive abilities of quarterly cash flows for a sample of 30 firms. The sample period was from 1964 to 1978. In this study univariate and transfer function Box- Function was used to procedure to develop forecasting models. In this study cash was defined for the quarter as earnings from operations fro the quarter plus depreciation and amortization in the quarter plus a quarter of the annual change in the deferred taxes. The input series in his multivariate model was earnings before extra-ordinary items; the Brooks found the addition of earnings series to cash flow series in a multivariate setting did not improve the prediction of cash flows that were obtained from past cash flows series alone in a univariate setting. Thus there was no statistically significant difference between the two Box- Jenkins forecasting models second examining the residuals from the earnings univariate model and cash flow univariate model, on a firm basis, the residual mean square error was smaller for the earnings model than cash flow model, thus indicating that earnings model
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