IDEAS home Printed from https://ideas.repec.org/a/wly/isacfm/v3y1994i1p1-19.html
   My bibliography  Save this article

Explaining Financial Results

Author

Listed:
  • Walter Hamscher

Abstract

CROSBY III automatically constructs explanations for financial results. The key elements of the program are (1) a body of raw financial data to be explained, (2) an extensible knowledge base of financial relations expressed as algebraic constraints, (3) a selection of possible explanatory variables and information about the relative likelihoods of individual hypotheses, (4) an algorithm for generating consistent, adequate, plausible and parsimonious interpretations of the data, (5) a facility for explaining how a particular interpretation supports the data and (6) a facility for explaining why one interpretation is preferred over another. This paper focuses on facilites (5) and (6). CROSBY III is an implemented but undeployed prototype that has been tested on historical data and financial models of a small high‐technology company along with its closest competitors, on more than ten divisions of a large company and on a collection of large banks.

Suggested Citation

  • Walter Hamscher, 1994. "Explaining Financial Results," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 3(1), pages 1-19, January.
    • Handle: RePEc:wly:isacfm:v:3:y:1994:i:1:p:1-19
    DOI: 10.1002/j.1099-1174.1994.tb00051.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/j.1099-1174.1994.tb00051.x
    Download Restriction: no
    File URL: https://libkey.io/10.1002/j.1099-1174.1994.tb00051.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Feelders, A J, 1992. "A Model of Explanation for Financial Knowledge-Based Systems," Computer Science in Economics & Management, Kluwer;Society for Computational Economics, vol. 5(2), pages 119-132, May.
    2. Abramson, Bruce & Finizza, Anthony, 1991. "Using belief networks to forecast oil prices," International Journal of Forecasting, Elsevier, vol. 7(3), pages 299-315, November.
    3. Marinus J. Bouwman, 1983. "Human Diagnostic Reasoning by Computer: An Illustration from Financial Analysis," Management Science, INFORMS, vol. 29(6), pages 653-672, June.
    Full references (including those not matched with items on IDEAS)

    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. Feelders, A. J. & Daniels, H. A. M., 2001. "A general model for automated business diagnosis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 623-637, May.
    2. Mingming, Tang & Jinliang, Zhang, 2012. "A multiple adaptive wavelet recurrent neural network model to analyze crude oil prices," Journal of Economics and Business, Elsevier, vol. 64(4), pages 275-286.
    3. Sanders, Nada R. & Manrodt, Karl B., 2003. "The efficacy of using judgmental versus quantitative forecasting methods in practice," Omega, Elsevier, vol. 31(6), pages 511-522, December.
    4. Movagharnejad, Kamyar & Mehdizadeh, Bahman & Banihashemi, Morteza & Kordkheili, Masoud Sheikhi, 2011. "Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network," Energy, Elsevier, vol. 36(7), pages 3979-3984.
    5. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    6. Kida, Thomas & Smith, James F., 1995. "The encoding and retrieval of numerical data for decision making in accounting contexts: Model development," Accounting, Organizations and Society, Elsevier, vol. 20(7-8), pages 585-610.
    7. Julia Bräker & Anna Osterbrink & Martin Semmann & Manuel Wiesche, 2023. "User-Centered Requirements for Augmented Reality as a Cognitive Assistant for Safety-Critical Services," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(2), pages 161-178, April.
    8. Siskos, Y. & Spyridakos, A., 1999. "Intelligent multicriteria decision support: Overview and perspectives," European Journal of Operational Research, Elsevier, vol. 113(2), pages 236-246, March.
    9. Marcus Vinicius Santos & Fernando Morgado-Dias & Thiago C. Silva, 2023. "Oil Sector and Sentiment Analysis—A Review," Energies, MDPI, vol. 16(12), pages 1-29, June.
    10. Mei-Teing Chong & Chin-Hong Puah & Shazali Abu Mansor, 2018. "Constructing a Composite Leading Indicator for the Global Crude Oil Price," International Business Research, Canadian Center of Science and Education, vol. 11(5), pages 129-134, May.
    11. Vetschera, Rudolf, 1993. "Zur Konsistenz von Abweichungsanalysen in hierarchischen Kennzahlensystemen," Discussion Papers, Series I 269, University of Konstanz, Department of Economics.
    12. Prat, Georges & Uctum, Remzi, 2011. "Modelling oil price expectations: Evidence from survey data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
    13. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    14. Michael F. Wolf, 1995. "New Technologies for Customer Rating: Integration of Knowledge‐Based Systems and Human Judgement," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(4), pages 289-301, December.
    15. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    16. Fan, Ying & Liang, Qiang & Wei, Yi-Ming, 2008. "A generalized pattern matching approach for multi-step prediction of crude oil price," Energy Economics, Elsevier, vol. 30(3), pages 889-904, May.
    17. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    18. Turgut Yokuş, 2024. "Early Warning Systems for World Energy Crises," Sustainability, MDPI, vol. 16(6), pages 1-18, March.
    19. Kwok, Helen, 2002. "The effect of cash flow statement format on lenders' decisions," The International Journal of Accounting, Elsevier, vol. 37(3), pages 347-362.
    20. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.

    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:wly:isacfm:v:3:y:1994:i:1:p:1-19. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1099-1174/ .

    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.