IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v12y1996i4p475-482.html
   My bibliography  Save this article

Neural network forecasting of quarterly accounting earnings

Author

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

Abstract

No abstract is available for this item.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(96)00706-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Mario Zupan, 2024. "Accounting journal entries as a long‐term multivariate time series: Forecasting wholesale warehouse output," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(1), March.
    18. 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.
    19. 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.
    20. Gencay, Ramazan & Selcuk, Faruk, 2001. "Software reviews," International Journal of Forecasting, Elsevier, vol. 17(2), pages 305-317.
    21. 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.
    22. 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.
    23. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Jumming Hsu & Xu-Ming Wang & Chunchi Wu, 1998. "The Role of Earnings Information in Corporate Dividend Decisions," Management Science, INFORMS, vol. 44(12-Part-2), pages 173-191, December.
    4. Sean Shun Cao & Ganapathi S. Narayanamoorthy, 2012. "Earnings Volatility, Post–Earnings Announcement Drift, and Trading Frictions," Journal of Accounting Research, Wiley Blackwell, vol. 50(1), pages 41-74, March.
    5. Lorek, Kenneth S., 2014. "A critical assessment of the time-series literature in accounting pertaining to quarterly accounting numbers," Advances in accounting, Elsevier, vol. 30(2), pages 315-321.
    6. Richard M. Morton, 1998. "The Incremental Informativeness of Stock Prices for Future Accounting Earnings," Contemporary Accounting Research, John Wiley & Sons, vol. 15(1), pages 57-81, March.
    7. He, Shuoyuan & Narayanamoorthy, Ganapathi (Gans), 2020. "Earnings acceleration and stock returns," Journal of Accounting and Economics, Elsevier, vol. 69(1).
    8. Carnes, Thomas A. & Jones, Jefferson P. & Biggart, Timothy B. & Barker, Katherine J., 2003. "Just-in-time inventory systems innovation and the predictability of earnings," International Journal of Forecasting, Elsevier, vol. 19(4), pages 743-749.
    9. Rountree, Brian & Weston, James P. & Allayannis, George, 2008. "Do investors value smooth performance?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 237-251, December.
    10. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    11. Pagach, Donald P. & Warr, Richard S., 2020. "Analysts versus time-series forecasts of quarterly earnings: A maintained hypothesis revisited," Advances in accounting, Elsevier, vol. 51(C).
    12. Michael Calegari & Neil L. Fargher, 1997. "Evidence that Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings: An Experimental Markets Approach," Contemporary Accounting Research, John Wiley & Sons, vol. 14(3), pages 397-433, September.
    13. Barniv, Ran, 2009. "Does foreign investor demand for information affect forecast accuracy? Evidence from the Chinese stock markets," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 18(2), pages 101-118.
    14. Lin, Hai & Tao, Xinyuan & Wu, Chunchi, 2022. "Forecasting earnings with combination of analyst forecasts," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 133-159.
    15. Renê Coppe Pimentel & Andson Braga de Aguiar, 2012. "Persistence of quarterly earnings: an empirical investigation in Brazil," Brazilian Business Review, Fucape Business School, vol. 9(Special I), pages 38-54, March.
    16. Martin, Anna D. & Mauer, Laurence J., 2003. "Exchange rate exposures of US banks: A cash flow-based methodology," Journal of Banking & Finance, Elsevier, vol. 27(5), pages 851-865, May.
    17. Bert De Bruijn & Philip Hans Franses, 2018. "How Informative Are Earnings Forecasts? †," JRFM, MDPI, vol. 11(3), pages 1-20, July.
    18. Bert de Bruijn & Philip Hans Franses, 2015. "How Informative are the Unpredictable Components of Earnings Forecasts?," Tinbergen Institute Discussion Papers 15-032/III, Tinbergen Institute.
    19. Mest, David P. & Plummer, Elizabeth, 1999. "Transitory and persistent earnings components as reflected in analysts' short-term and long-term earnings forecasts: evidence from a nonlinear model," International Journal of Forecasting, Elsevier, vol. 15(3), pages 291-308, July.
    20. John Garcia, 2021. "Analyst herding and firm-level investor sentiment," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 461-494, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfor:v:12:y:1996:i:4:p:475-482. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.