The Effect of SFAS No. 141 and SFAS No. 142 on the Accuracy of Financial Analysts' Earnings Forecasts after Mergers

The Effect of SFAS No. 141 and SFAS No. 142 on the Accuracy of Financial Analysts' Earnings Forecasts after Mergers

Date: May 2005
Creator: Mintchik, Natalia Maksimovna
Description: This study examines the impact of Statements of Financial Accounting Standards No. 141 and No. 142 (hereafter SFAS 141, 142) on the characteristics of financial analysts' earnings forecasts after mergers. Specifically, I predict lower forecast errors for firms that experienced mergers after the enactment of SFAS 141, 142 than for firms that went through business combinations before those accounting changes. Study results present strong evidence that earnings forecast errors for companies involved in merging and acquisition activity decreased after the adoption of SFAS 141, 142. Test results also suggest that lower earnings forecast errors are attributable to factors specific to merging companies such as SFAS 141, 142 but not common to merging and non-merging companies. In addition, evidence implies that information in corporate annual reports of merging companies plays the critical role in this decrease of earnings forecast error. Summarily, I report that SFAS 141, 142 were effective in achieving greater transparency of financial reporting after mergers. In my complementary analysis, I also document the structure of corporate analysts' coverage in "leaders/followers" terms and conduct tests for differences in this structure: (1) across post-SFAS 141,142/pre-SFAS 141, 142 environments, and (2) between merging and non-merging firms. Although I do not identify ...
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Budget-Related Prediction Models in the Business Environment with Special Reference to Spot Price Predictions

Budget-Related Prediction Models in the Business Environment with Special Reference to Spot Price Predictions

Date: August 1986
Creator: Kumar, Akhil
Description: The purpose of this research is to study and improve decision accuracy in the real world. Spot price prediction of petroleum products, in a budgeting context, is the task chosen to study prediction accuracy. Prediction accuracy of executives in a multinational oil company is examined. The Brunswik Lens Model framework is used to evaluate prediction accuracy. Predictions of the individuals, the composite group (mathematical average of the individuals), the interacting group, and the environmental model were compared. Predictions of the individuals were obtained through a laboratory experiment in which experts were used as subjects. The subjects were required to make spot price predictions for two petroleum products. Eight predictor variables that were actually used by the subjects in real-world predictions were elicited through an interview process. Data for a 15 month period were used to construct 31 cases for each of the two products. Prediction accuracy was evaluated by comparing predictions with the actual spot prices. Predictions of the composite group were obtained by averaging the predictions of the individuals. Interacting group predictions were obtained ex post from the company's records. The study found the interacting group to be the least accurate. The implication of this finding is that even ...
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Prediction of Business Failure as a Criterion for Evaluating the Usefulness of Alternative Accounting Measures

Prediction of Business Failure as a Criterion for Evaluating the Usefulness of Alternative Accounting Measures

Date: August 1986
Creator: Aly, Ibrahim M. Mohamed
Description: This study examines the usefulness of general price level information (GPL) and current cost information (CC) originally provided by SFAS No. 33 as compared to historical cost information (HC) in predicting bankruptcy. The study also examines the usefulness of GPL data versus CC data when each supplements HC data. In addition, this study tests the usefulness of the three types of information systems combined in one model (HC, GPL, and CC) versus HC data in predicting bankruptcy. The study focuses on the predictability of business failure using financial ratios as predictors. A comparison of these predictors is made in order to identify the accounting system that yields a better prediction of bankruptcy. Two multivariate statistical techniques, multiple discriminant analysis (MDA) and logistic regression analysis (LRA), are used to derive the ex—post classification and the ex-ante prediction results. Six functions are developed, based on ratios computed with HC, CC, GPL, the combined HC and GPL, the combined HC and CC, and the combined HC, GPL, and CC. The resulting functions are used to classify 40 firms as failed or nonfailed. The analysis is repeated for three time bases—one, two, and three years before bankruptcy. The main results of the various analyses ...
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Forecasting Quarterly Sales Tax Revenues: A Comparative Study

Forecasting Quarterly Sales Tax Revenues: A Comparative Study

Date: August 1986
Creator: Renner, Nancy A. (Nancy Ann)
Description: The purpose of this study is to determine which of three forecasting methods provides the most accurate short-term forecasts, in terms of absolute and mean absolute percentage error, for a unique set of data. The study applies three forecasting techniques--the Box-Jenkins or ARIMA method, cycle regression analysis, and multiple regression analysis--to quarterly sales tax revenue data. The final results show that, with varying success, each model identifies the direction of change in the future, but does not closely identify the period to period fluctuations. Indeed, each model overestimated revenues for every period forecasted. Cycle regression analysis, with a mean absolute percentage error of 7.21, is the most accurate model. Multiple regression analysis has the smallest absolute percentage error of 3.13.
Contributing Partner: UNT Libraries