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1992 Volume 7
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RESEARCH ARTICLE   Open Access    

Model-based reasoning in financial domains

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  • Abstract: Finance is a challenging yet appropriate domain for model-based reasoning, an area of research otherwise grounded in classical physics. Among the many features that suggest a model-based approach are that firms have formal internal structures, business entities have idealizable behaviours, and there is a history of formal analysis of business problems. This article discusses the motivations and foundations of the model-based approach, and surveys several existing artificial intelligence programs that exploit its advantages. The survey shows that there are ample opportunities for useful systems and significant research in this area. However, accomplishing either of these goals depends crucially upon moving beyond qualitative models based only on accounting information, which tend not to capture the actual complexities of the domain.
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  • Addanki S, Cremonini R and Penberthy JS, 1991. “Reasoning about assumptions in graphs of models” Artificial Intelligence51 (1–3) 145–177. (Also in: J de Kleer and B Williams (eds), Qualitative Reasoning about Physical Systems II North-Holland MIT Press.

    Google Scholar

    Bailey AD, Duke GL, Gerlach J, Ko C, Meservy RD and Whinston , 1985. TICOM and the analysis of internal controls “The Accounting Review”LX (2) 186–201.

    Google Scholar

    Bailey AD, Han KS, Stansifer RD and Whinston AB, 1989. “The advanced internal accounting control model using a logic programming approach” Working Paper.

    Google Scholar

    Bailey AD, Kiang Y, Kuipers B and Whinston AB, 1990. “Analytical review and qualitative and causal reasoning in auditing” Draft.

    Google Scholar

    Benaroch M and Dhar V, 1996. “An intelligent assistant for financial hedging”. In: Proc. 7th IEEE Conf. on AI Applications168–174, Miami, FL.

    Google Scholar

    Benaroch M and Dhar V, 1996. “A knowledge-based approach to solving hedge design problems”. In: 1st Int. Conf. on AI Applications on Wall Street140–145, New York.

    Google Scholar

    Bouwman MJ, 1983. “Human diagnostic reasoning by computer: An illustration from financial analysis” Management Science29 (6) 653–672, 06.

    Google Scholar

    Brealey RA and Myers SC, 1981. Principles of Corporate Finance. McGraw-Hill.

    Google Scholar

    Bridgeland DM, 1990. “Three qualitative simulation extensions for supporting economics models”. In: Proc 6th IEEE Conf. on AI Applications266–273, Santa Barbara, CA.

    Google Scholar

    Console L, Theseider Dupré D and Torasso P, 1991. “On the relationship between abduction and deduction”. J. Logic and Computation1 (5) 661–690.

    Google Scholar

    Daniels HAM and Feelders AJ, 1991. “Combining qualitative and quantitative methods for model-based diagnosis of firms” In: Singh M and Trave-Massuyes L (ed), Decision Support Systems and Qualitative Reasoning. North-Holland.

    Google Scholar

    Davis R and Hamscher WC, 1988. “Model based reasoning: Troubleshooting”. In: HE Shrobe (ed), Exploring Artificial Intelligence: Survey Talks from the National Conferences of Artificial Intelligence297–346. Morgan Kaufmann. (Also in: PH Winston and SA Shellard (eds), 1990. Artificial Intelligence at MIT: Expanding Frontiers MIT Press. And in WC Hamscher, J de Kleer and L Console (eds), 1992, Readings in Model-based Diagnosis Morgan Kaufmann.)

    Google Scholar

    de Kleer J and Williams BC, 1987. “Diagnosing multiple faults”, Artificial Intelligence, 32 (1) 97–130, April. (Also in: Ginsberg, ML (ed), 1987, Readings in Nonmonotonic Reasoning Morgan Kaufmann. And in: WC Hamscher, J de Kleer and L Console (eds), Readings in Model-based Diagnosis Morgan Kaufmann.)

    Google Scholar

    de Kleer J and Williams BC, 1989. “Diagnosis with behavioral modes”. In: Proc. llth Int. Joint Conf. on Artificial Intelligence 1324–1330,Detroit, MI. (Also in WC Hamscher, J de Kleer and L Console (eds), 1992, Model-based Diagnosis Morgan Kaufmann.

    Google Scholar

    de Kleer J and Williams BC, (eds), 1991. Qualitative Reasoning about Physical Systems IIEisevier.

    Google Scholar

    de Kleer J, 1986. “An assumption-based TMS” Artificial Intelligence28 (2) 127–162. (Also in: Ginsberg, ML (ed), 1987, Readings in Nonmonotonic Reasoning Morgan Kaufmann).

    Google Scholar

    Dhar V, Lewis B and Peters J, 1988. “A knowledge based model of audit risk” AI Magazine9 (3) 57–63, Fall.

    Google Scholar

    Elliott JW and Uphoff HL, 1972. “Predicting the near term profit and loss statement with an econometric model: A feasibility study” J. Accounting Research259–274, Autumn.

    Google Scholar

    Falkenhainer B and Forbus KD, 1991. “Compositional modeling: Finding the right model for the job” Artificial Intelligence51 (1–3) 95–143. (Also in J de Kleer and B Williams (eds), 1992, Qualitative Reasoning about Physical Systems II North Holland MIT Press.)

    Google Scholar

    Feigenbaum EA, McCorduck P and Nii HP, 1988. The Rise of the Expert Company. Times Books.

    Google Scholar

    Hamscher WC, de Kleer J and Console L, (ed), 1992. Readings in Model-based DiagnosisMorgan Kaufmann.

    Google Scholar

    Hamscher WC, 1990. “Explaining unexpected financial results” Technical Report 11, Price Waterhouse Technology Centre, Menlo Park, CA 94025. (Also in Working Notes of the Spring Symposium on Automated Abduction, 96–100, AAAI Press, 1990.)

    Google Scholar

    Hamscher WC, 1991a. “ACP: Reason maintenance and inference control for constraint propagation over intervals” In: Proc. 9th National Conf. on Artificial Intelligence506–511, Anaheim, CA,July. (Also in WC Hamscher, J de Kleer and L Console (eds), 1992, Readings in Model-based Diagnosis Morgan Kaufmann.

    Google Scholar

    Hamscher WC, 1991b. “Model-based financial data interpretation” In: 1st Int. Conf. on AI Applications on Wall Street IEEE Press. (Also in: Working Notes of the Model-based Reasoning Workshop AAAI Press, 1991. And in: Working Notes of the 2nd International Workshop on Principles of Diagnosis Technical Report RT/DI/91–10–7, Dipartimento di Informatica, Universita di Torino, 1991.)

    Google Scholar

    Hamscher WC, 1991c. “Modeling digital circuits for trouble shooting” Artificial Intelligence51 (1–3) 223/271, 10. (Also in: WC Hamscher, J de Kleer and L Console, (eds), 1992, Readings in Model-based Diagnosis Morgan Kaufmann.)

    Google Scholar

    Hamscher WC, 1992. “Modeling accounting processes to support multiple tasks: A progress report” In: Proc. 10th National Conf. on Artificial Intelligence,San Jose, CA,July.

    Google Scholar

    Hart PE, Barzilay A and Duda RO, 1986. “Qualitative reasoning for financial assessments: A prospectus” AI Magazine7 (1) 62–68, Winter.

    Google Scholar

    Helfert EA, 1986. Techniques of Financial Analysis. Homewood.

    Google Scholar

    Hillier FS and Lieberman GJ, 1980. Introduction to Operations ResearchHolden-Day.

    Google Scholar

    Hyvönen E, 1991. “Interval constraint spreadsheets for financial planning.” In: 1st Int. Conf. on AI Applications on Wall Street302–311, IEEE Press.

    Google Scholar

    Karp PD and Wilkins DC, 1989. “An analysis of the distinction between deep and shallow expert systems” Int. J. Expert Systems Research and Applications2 (1) 1–32.

    Google Scholar

    Kaufman S, 1989. “Report Finds Massive Fraud at Miniscribe” San Jose Mercury News, 4D, 09 12.

    Google Scholar

    Kosy DW and Wise BP, 1984. “Self explanatory financial models.” In: Proc. 4th National Conf. on Artificial Intelligence176–181, Austin, TX,August.

    Google Scholar

    Kosy DW, 1989. “Applications of explanation in financial modeling.” In: Widman LE, Loparo KA and Nielsen NR, (eds), Artificial Intelligence, Simulation, and Modeling487–509. Wiley-Interscience.

    Google Scholar

    Kuipers BJ, 1987. “Abstraction by time-scale in qualitative simulation.” In: Proc. 6th National Conf. on Artificial Intelligence621–625, Seattle, WA,August. (Also in DS Weld and J de Kleer (eds), 1990, Readings in Qualitative Reasoning about Physical Systems Morgan Kaufmann.)

    Google Scholar

    Maher ML, 1990. “Process models for design synthesis.” AI Magazine, 11 (4) 49–58, Winter.

    Google Scholar

    MiniScribe, 1989. Summary of Report of the Independent Evaluation Committee of the Board of Directors of MiniScribe Corporation. Exhibit provided in 8-K Disclosure, 09 12.

    Google Scholar

    Peters JM, 1990. “A cognitive computational model of risk hypothesis generation.” J Accounting Research28 (Supplement) 83–103.

    Google Scholar

    Poole D, 1991. “Representing diagnostic knowledge for probabilistic Horn abduction.” In: Proc. 12th Int. Joint Conf. on Artificial Intelligence1129–1135, Sydney, Australia,August. (Also in: WC Hamscher, J de Kleer and L Console (eds), 1992, Readings in Model-based Diagnosis Morgan Kaufmann.

    Google Scholar

    Saltzman S, 1967. “An econometric model of a firm.” The Review of Economics and Statistics, 49332–342, 08.

    Google Scholar

    Weld DS and Addanki S, 1990. “Query-directed approximation.” Technical Report 90–12–02, Department of Computer Science and Engineering, FR-35, University of Washington.

    Google Scholar

    Weld DS and de Kleer J, 1990. Readings in Qualitative Reasoning about Physical SystemsMorgan Kaufmann.

    Google Scholar

    Wild JJ, 1987. “The prediction performance of a structural model of accounting numbers” J. Accounting Research25 (1) 139–160, Spring.

    Google Scholar

    Williams BC, 1990. “Interaction-based invention: Designing novel devices from first principles” In: Proc. 8th National Conf. on Artificial Intelligence, 349–356, Boston, MA,August.

    Google Scholar

    Zipser A, 1989. “How pressure to Raise Sales Led MiniScribe to Falsify Numbers” Wall Street Journal, 109 11.

    Google Scholar

  • Cite this article

    Walter Hamscher. 1992. Model-based reasoning in financial domains. The Knowledge Engineering Review. 7:6457 doi: 10.1017/S0269888900006457
    Walter Hamscher. 1992. Model-based reasoning in financial domains. The Knowledge Engineering Review. 7:6457 doi: 10.1017/S0269888900006457
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RESEARCH ARTICLE   Open Access    

Model-based reasoning in financial domains

  • Published online: 07 July 2009
The Knowledge Engineering Review  7,  Article number: 10.1017/S0269888900006457  (1992)  |  Cite this article

Abstract: Abstract: Finance is a challenging yet appropriate domain for model-based reasoning, an area of research otherwise grounded in classical physics. Among the many features that suggest a model-based approach are that firms have formal internal structures, business entities have idealizable behaviours, and there is a history of formal analysis of business problems. This article discusses the motivations and foundations of the model-based approach, and surveys several existing artificial intelligence programs that exploit its advantages. The survey shows that there are ample opportunities for useful systems and significant research in this area. However, accomplishing either of these goals depends crucially upon moving beyond qualitative models based only on accounting information, which tend not to capture the actual complexities of the domain.

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    Walter Hamscher. 1992. Model-based reasoning in financial domains. The Knowledge Engineering Review. 7:6457 doi: 10.1017/S0269888900006457
    Walter Hamscher. 1992. Model-based reasoning in financial domains. The Knowledge Engineering Review. 7:6457 doi: 10.1017/S0269888900006457
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