EARNINGS PERFORMANCE IN PREDICTING FUTURE EARNINGS AND STOCK PRICE PATTERN

Abstract

So far, business forecasting has been considered important in almost all economic entitiesand it is often used in areas such as in security analysts, institutional lending, and manage-ment. This research aims at examining empirically the predictability of time series of earn-ings for future earnings and stock price patterns by means of Autoregressive Integrated Mov-ing Average (ARIMA). It is expected to provide contribution in the form of empirical evi-dence, in which earnings are considered useful for predicting earnings and stock price pat-tern. The forecasting is by using some techniques among others, the naïve model, regression,ARIMA (Box-Jenkins) and so on. The data were taken from stock market data center at UGMand UTY’s IDX corner during 1996-2007. Based on the sampling criteria, 22 companieswere used as the sample. The results showed that there were no statistically significant dif-ferences among actual earnings for the earnings forecast. The first hypothesis which statesthat there is ability in predicting earnings income is statistically supported. The second hy-pothesis which states that there is the ability of earnings in predicting stock price pattern isalso statistically supported