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並列摘要


The main purpose of this paper is to develop a stock price prediction model based on quarterly earnings forecasts. The prediction model is based on the residual income model by Ohlson (1995), and adjustment for autocorrelation by Higgins (2009). Prior research has not used quarterly data out of concern for seasonality. However, seasonality can be removed by including four consecutive quarterly terms of abnormal earnings in each price equation. The prediction results suggest that quarterly earnings forecasts can be useful inputs to models of price forecasts.

參考文獻


Higgins, H.,Lu, Q. F.(2009).Predicting stock price by applying the residual income model and bayesian statistics.Advances in Quantitative Analysis of Finance and Accounting.7,71-94.
Cochrane, D., & Orcutt, G. H. (1949). Application of least squares regression to relationships containing auto-correlated error terms. Journal of the American Statistical Association, 44, 32-61.
Higgins, H. (2009). Forecasting stock price with the residual income model. Working paper, Worcester Polytechnic Institute
Bagnoli, M.,Beneish, M. D.,Watts, S. G.(1999).Whisper forecasts of quarterly earnings per share.Journal of Accounting and Economics.28,27-50.
Barth, M.,Kallapur, S.(1996).The effects of cross-sectional scale differences on regression results in empirical accounting research.Contemporary Accounting Research.13,527-567.

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