Accounting: The Use of Gathered Earnings - Essay Example

Q.3> Discuss the contribution made by empirical market-based research to your understanding of how and to what extent earnings are used by investors. Evaluating the use of earnings to investors had been a major area of research. The studies conducted on the subject by Ball and Brown (1968) and Beaver (1968) are examples. During the 70’s it was more transparent that the use of earnings by investors does not fall under a straightforward empirical assessment. Findings suggest that the content of information related to earnings includes only some financial content which reflects stock prices, which are not of any particular help to the investors or policy makers. Also, the questions relating to the usefulness of earnings are of significant information to the researchers, practitioners and regulators. It is believed that the main essence that could be derived or analysed from the financial statements are earnings. Economic theory too supports corporate earnings with the crucial role of setting its direction for resource allocation in capital markets. Several valuation methods also depict the expected earnings as a explanatory variable. Management decisions and formulation of compensation policies are always stated in terms of the earnings objectives. However, the disparity between the economic and accounting earnings (Fisher and McGowan (1983) and Fisher (1987), the manipulation and fraud in reported earnings (National Commission of Fraudulent Financial Reporting (1987) etc could be seen as the limitations of studies in earnings. Hence it could be observed that the evaluation as to the usefulness of earnings to investors is a very relevant subject in the current scenario. The empirical researches conducted in the field come up with major conclusions as discussed below. (i) The research evidently stated that there is very little or negligible correlation between earnings and stock returns. The nature of earnings also exhibits instability. Thus the extent of usefulness of quarterly and annual earnings to investors remains very limited. (ii) All the theories and methodologies till date focused on improving the relation between the earnings and stock returns have obtained to arrive at the extent of its use by the investors. (iii) The incorrect specifications of the earnings-return relation or the irrationality between the investors have in turn weakened the relation between earnings and stock returns. The reason for this could be poor quality of the information relating to the reported earnings. (iv) Thus, the need for investigating the process of financial information or understanding the actual use of earnings to investors came up. It could be inferred that if a revision in the stock prices can provide the usefulness of earnings, then larger revisions would satisfy greater usefulness. As per this the derivations about the relation between stock returns and earnings could be brought to light. In other words if the information of earnings to investors is significant then the earnings will be able to explain evidently the earnings reported with respect to price changes. Also if the price changes are not related significantly to the earnings, the information contribution or the usefulness for the investors will not be large. This evidently states the usefulness of the correlation between returns and earnings or the R2 of the regression of the returns on earnings to find out the information contribution or the use of earnings to investors. What evidence of bias is there in analysts’ forecasts? What are the determinants of the biases? Does the market recognize the apparent biases in pricing securities? All the interested parties on investments and stocks like Brokerage firms; Investment houses etc., spend much of their funds for analyzing their stocks and seeks the advice of analysts’ recommendations. Analysts give recommendation on stocks, to buy, sell or hold them and forecasts earnings estimates. Analysts’ forecasts used as estimates for market earnings expectation often suffers from certain errors or bias. This is mainly because the accuracy of analysts’ forecasts and their association with security returns contradict with forecasts with time–series and forecasts of earnings. Thus the bias or Earnings forecast error = Difference between actual earnings per share and a measure based on analysts’ forecasts. The empirical evidence states that during the 1980s and most of the 1990s, analysts were optimistic in forecasting information on earnings. [Barefield and Comiskey, 1975; Brown et al., 1985; O’Brien, 1988; Lim, 1998; Easterwood and Nutt, 1999] It was seen that analysts under reacted to negative information, but overreacted to optimistic information. There was an average optimistic bias of 0.94% of price, 2.5% for small firms, 0.53% for large firms. (Lim, 1998) The earnings forecasted by the analysts’ and actual earnings do not always seem to be the same. However in recent years, the optimism seems to be declining. The results reveal that issues with earnings forecasting are concentrated in negative earnings change firms, and the empirical result elements of whether analysts are superior to time series models and whether there is negative or positive bias and over- or under-reaction, depends on the number of negative vs. positive earnings change firms in the research period. The determinants of biases leading to the inefficiency of the analysts’ forecasts are due to many reasons. Historical evidence fails to find differential forecast accuracy among analysts. (Brown and Rozeff, 1980; O’Brien, 1990). Using larger data sets and better controls for forecast horizon, analysts’ accuracy is biased [Sinha, 1997] The determinants of bias thus include, experience (or learning), size of the brokerage firm, complexity of the analyst’s task including the number of firms and industries followed. [Mikhail et al., 1997; Jacob et al., 1999; Clement, 1999] As a solution the Inefficient analysts’ forecasts could be revised and the analysts should be given incentives to provide accurate forecasts by possible restructuring the Cost and reward structure of a financial analyst [Lys and Sohn, 1990; Abarbanell, 1991] Other macroeconomic determinants include trade intensity of growth differential or policy events such as trade and financial liberalization. Another important point in measuring bias is to considering its time-varying feature. It is accepted that for a given pair of countries, interdependence obviously varies over time. These macroeconomic determinants are assumed to influence the evolution of stock prices. The stock market is rather focused analysts’ biased forecasts. The market’s failure to recognize the optimistic bias (naïve reliance) requires a theory of market inefficiency However reasons for mis-pricing securities involve the presence of disparities and transaction costs of trading, Limitations of the ability enjoyed by the participants, behavioral biases among the market participants, and, anticipation of investors References seeked with respect to guidelines 1. Journal of Accounting Research, Vol. 27 Supplement 1989, Printed in U.S.A, On the Usefulness of Earnings and Earnings Research: Lessons and Directions from Two Decades of Empirical Research, http://accounting.wharton.upenn.edu/Spring2006/acct920/lev%201989.pdf 2. http://lipas.uwasa.fi/ktt/lasktoim/research/doc/Timo_Rothovius.htm 3. http://www.essex.ac.uk/afm/financecentre/Beine%20Candelon%20040206.pdf 4. http://www.economiamc.org/repo/83/LECTURE+3-Mc.pdf Read More