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Neural network forecasting of quarterly accounting earnings

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  • Callen, Jeffrey L.
  • Kwan, Clarence C. Y.
  • Yip, Patrick C. Y.
  • Yuan, Yufei

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  • Callen, Jeffrey L. & Kwan, Clarence C. Y. & Yip, Patrick C. Y. & Yuan, Yufei, 1996. "Neural network forecasting of quarterly accounting earnings," International Journal of Forecasting, Elsevier, vol. 12(4), pages 475-482, December.
    • Handle: RePEc:eee:intfor:v:12:y:1996:i:4:p:475-482
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    References listed on IDEAS

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    1. Brown, Lawrence D., 1993. "Earnings forecasting research: its implications for capital markets research," International Journal of Forecasting, Elsevier, vol. 9(3), pages 295-320, November.
    2. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
    3. Donaldson, R.G. & Kim, K.H.Y., 1993. "Evaluating Alternative Models for Conditional Stock Volatility : Evidence from International Data," Discussion Papers dp93-06, Department of Economics, Simon Fraser University.
    4. Chatfield, Chris, 1995. "Positive or negative?," International Journal of Forecasting, Elsevier, vol. 11(4), pages 501-502, December.
    5. Lee, Chi-Wen Jevons & Chen, Chung, 1990. "Structural changes and the forecasting of quarterly accounting earnings in the utility industry," Journal of Accounting and Economics, Elsevier, vol. 13(2), pages 93-122, July.
    6. Masson, Egill & Wang, Yih-Jeou, 1990. "Introduction to computation and learning in artificial neural networks," European Journal of Operational Research, Elsevier, vol. 47(1), pages 1-28, July.
    7. Tam, KY, 1991. "Neural network models and the prediction of bank bankruptcy," Omega, Elsevier, vol. 19(5), pages 429-445.
    8. Brown, Lawrence D., 1993. "Reply to commentaries on "Earnings forecasting research: its implications for capital markets research"," International Journal of Forecasting, Elsevier, vol. 9(3), pages 343-344, November.
    9. W. S. Hopwood & P. Newbold, 1980. "Time Series Analysis In Accounting: A Survey And Analysis Of Recent Issues," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(2), pages 135-144, March.
    10. Griffin, Pa, 1977. "Time-Series Behavior Of Quarterly Earnings - Preliminary Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 15(1), pages 71-83.
    11. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    12. T. Subba Rao & M. M. Gabr, 1980. "A Test For Linearity Of Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(2), pages 145-158, March.
    13. Brown, Ld & Rozeff, Ms, 1979. "Univariate Time-Series Models Of Quarterly Accounting Earnings Per Share - Proposed Model," Journal of Accounting Research, Wiley Blackwell, vol. 17(1), pages 179-189.
    14. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    15. Brown, Philip, 1993. "Comments on 'Earnings forecasting research: its implications for capital markets research' by L. Brown," International Journal of Forecasting, Elsevier, vol. 9(3), pages 331-335, November.
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    Cited by:

    1. Olson, Dennis & Mossman, Charles, 2003. "Neural network forecasts of Canadian stock returns using accounting ratios," International Journal of Forecasting, Elsevier, vol. 19(3), pages 453-465.
    2. Fischer, Thomas & Krauss, Christopher & Treichel, Alex, 2018. "Machine learning for time series forecasting - a simulation study," FAU Discussion Papers in Economics 02/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    3. Laskai András, 2019. "AI foundations of the international business planning and the AI consciousness model," International Journal of Science and Business, IJSAB International, vol. 3(1), pages 17-28.
    4. Daniel Vela, 2013. "Forecasting Latin-American yield curves: An artificial neural network approach," Borradores de Economia 761, Banco de la Republica de Colombia.
    5. Amani, Farzaneh A. & Fadlalla, Adam M., 2017. "Data mining applications in accounting: A review of the literature and organizing framework," International Journal of Accounting Information Systems, Elsevier, vol. 24(C), pages 32-58.
    6. Qing Cao & Mark Parry & Karyl Leggio, 2011. "The three-factor model and artificial neural networks: predicting stock price movement in China," Annals of Operations Research, Springer, vol. 185(1), pages 25-44, May.
    7. Syouching Lai & Hungchih Li, 2006. "The predictive power of quarterly earnings per share based on time series and artificial intelligence model," Applied Financial Economics, Taylor & Francis Journals, vol. 16(18), pages 1375-1388.
    8. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    9. Yao, Jingtao & Li, Yili & Tan, Chew Lim, 2000. "Option price forecasting using neural networks," Omega, Elsevier, vol. 28(4), pages 455-466, August.
    10. Robert G. Biscontri, 2012. "A Radial Basis Function Approach To Earnings Forecast," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 1-18, January.
    11. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    12. Chu, Ching-Wu & Zhang, Guoqiang Peter, 2003. "A comparative study of linear and nonlinear models for aggregate retail sales forecasting," International Journal of Production Economics, Elsevier, vol. 86(3), pages 217-231, December.
    13. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 672-688, July.
    14. Hwarng, H. Brian & Ang, H. T., 2001. "A simple neural network for ARMA(p,q) time series," Omega, Elsevier, vol. 29(4), pages 319-333, August.
    15. Rä‚Zvan Popa, 2020. "Improving Earnings Predictions With Neural Network Models," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 26, pages 77-96, December.
    16. Daniel Vela, 2013. "Forecasting Latin-American yield curves: An artificial neural network approach," Borradores de Economia 10502, Banco de la Republica.
    17. Filip Staněk, 2023. "Optimal out‐of‐sample forecast evaluation under stationarity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2249-2279, December.
    18. Schnaubelt, Matthias, 2019. "A comparison of machine learning model validation schemes for non-stationary time series data," FAU Discussion Papers in Economics 11/2019, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    19. Gencay, Ramazan & Selcuk, Faruk, 2001. "Software reviews," International Journal of Forecasting, Elsevier, vol. 17(2), pages 305-317.
    20. Chi, Li-Chiu & Tang, Tseng-Chung, 2007. "Impact of reorganization announcements on distressed-stock returns," Economic Modelling, Elsevier, vol. 24(5), pages 749-767, September.
    21. Brad S. Trinkle, 2005. "Forecasting annual excess stock returns via an adaptive network‐based fuzzy inference system," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(3), pages 165-177, July.
    22. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.

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