Predicting corporate acquisitions: An application of uncertain reasoning using rule induction

Information Systems Frontiers

Volumn 5, Issue 4, 2003, Pages 401-412

  Ragothaman, Srinivasan ^a   Naik, Bijayananda ^a   Ramakrishnan, Kumoli ^a  

^a UNIVERSITY OF SOUTH DAKOTA   (United States)

Author keywords

Expert systems; Machine learning; Mergers and acquisitions; Rule induction; Uncertain reasoning

Indexed keywords

ARTIFICIAL INTELLIGENCE; CORRELATION METHODS; DECISION MAKING; EXPERT SYSTEMS; FINANCIAL DATA PROCESSING; LEARNING SYSTEMS; MANAGEMENT INFORMATION SYSTEMS; MARKETING; MATHEMATICAL MODELS; REGRESSION ANALYSIS; RISK MANAGEMENT; SOFTWARE PROTOTYPING; UNCERTAIN SYSTEMS;

RULE INDUCTION; SHAREHOLDERS; TRANSACTIONS; UNCERTAIN REASONING;

MERGERS AND ACQUISITIONS;

EID: 0344583815     PISSN: 13873326     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:ISFI.0000005653.53641.b3     Document Type: Article

References (43)

1. Akhigbe A, Madura J. The industry effects regarding the probability of takeovers. The Financial Review 1999:34.
2. Biggs S, Messier Jr. WF, Hansen JV. A descriptive analysis of computer audit specialists' decision-making behavior in advanced computer environments. Auditing: A Journal of Practice and Theory (Spring 1987):1-21.
3. Chan KCC, Wong AKC. A statistical technique for extracting classificatory knowledge from databases. In: Piatetsky-Shapiro G, Frawley WJ, eds. Knowledge Discovery in Databases, Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, 1991:107-123.
4. Comment R, Schwert GW. Poison or placebo: Evidence on the deterrence and wealth effects of modern anti-takeover measures. Journal of Financial Economics 1995;39:3-43.
5. Copeland TE, Weston JF. Financial Theory and Corporate Policy, 3rd Edition, Addison-Wesley Publishing Company, Inc., 1998.
6. Cudd M, Duggal R. Industry distributional characteristics of financial ratios: An acquisition theory application. The Financial Review 2000;35:105-116.
7. DePamphilis D. Mergers, Acquisitions, and other Restructuring Activities. Academic Press, 2001:27-33.
8. Frawley WJ, Piatetsky-Shapiro G, Matheus CJ. Knowledge discovery in databases: An overview. In: Piatetsky-Shapiro G, Frawley WJ, eds. Knowledge Discovery in Databases, Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, 1991:1-27.
9. Galai D, Masulis RW. The option pricing model and the risk factor of stock. Journal of Financial Economics 1976:53-82.
10. Gray GL. Software review - VP-expert. Expert Systems Review. March 1988:19-21.
11. IntelligenceWare. User's Manual: IDIS. Los Angeles, CA, 1994.
12. IntelligenceWare. IXL: The Machine Learning System. Los Angeles, CA: IntelligenceWare, Inc., 1991.
13. IntelligenceWare. A Dozen Success Stories. Brochure published by IntelligenceWare, Inc., Los Angeles, CA, 1992.
14. Jensen MC. Agency costs of free cash flow, corporate finance and takeovers. American Economic Review 1986;76:321-329.
15. Judge G, Griffiths WE, Hill RC, Lütkepohl H, Lee T. The Theory and Practice of Econometrics. New York, NY: Wiley, 1985.
16. Liang TP. A composite approach to inducing knowledge for expert system design. Management Science (Jan. 1992):1-17.
17. Lintner J. The valuation of risky assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics 1965;47:13-37.
18. Menger K. Topology Without Points. The Carl Menger Lectures, American Mathematical Society, 1953.
19. Messier Jr. WF, Hansen JV. Inducing rules for expert system development: An example using default and bankruptcy data. Management Science 1988:1403-1415.
20. Michalski R, Chilauski R. Learning by being told and learning by examples. Journal of Policy Analysis and Information Systems 1980:4.
21. Morck R, Schleiffcr A, Vishny R. Characteristics of targets of hostile and friendly takeovers. In: Auerbach AJ, ed. Corporate Takeovers: Causes and Consequences, Chicago, IL: National Bureau of Economic Research, 1988:101-129.
22. Nelson C, Balachandra R. Choosing the right expert system building approach. Decision Sciences 1991;22:354-368.
23. Nikolopoulos C. Expert Systems, New York: Marcel Dekker, 1997.
24. O'Leary DE. Validation of expert systems - With applications to auditing and accounting expert systems. Decision Sciences 1987:18:468-486.
25. O'Leary DE. Using neural networks to predict corporate failure. International Journal of Intelligent Systems in Accounting, Finance and Management 1998;7(3):187-197.
26. Palepu KG. Predicting takeover targets: A methodological and empirical analysis. Journal of Accounting and Economics 1986;8:3-35.
27. Parsaye K, Haussen O. Discovering knowledge from large databases. IntelligenceWare Technical Report, Nov. 9, 1987.
28. Parsaye K, Chignell M, Khoshafian S, Wong H. Intelligent Databases. New York: John Wiley, 1989.
29. Pearl J. Probabilistic Reasoning in Intelligent Systems. San Mateo, CA: Morgan Kaufman, 1989.
30. Postin T, Fuzzy Topology. Technical Report, Battelle Research Institute, Geneva, 1974.
31. Quinlan R. Induction of decision trees. Machine Learning 1986;1:81-106.
32. Ragothaman S, Naik B. Using rule induction for expert system development: The case of asset writedowns. International Journal of Intelligent Systems in Accounting, Finance and Management 1994;3(3):187-203.
33. Ragothaman S, Carpenter J, Naik B. Knowledge acquisition through rule induction: The case of going concern audit reports. Heuristics: The Journal of Intelligent Technologies 1995;8(4):33-46.
34. Sharpe WF. Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance 1964;19:425-442.
35. Shaw MJ. Applying inductive learning to enhance knowledge based expert systems. Decision Support Systems 1987;3:319-332.
36. Shenoy PP. Valuation-based systems: A framework for managing uncertainty in expert systems. In: Zadeh LA, Kacprzyk J, eds. Fuzzy Logic for the Management of Uncertainty, New York: John Wiley&Sons, 1992:83-104.
37. Shivdasani A. Board composition, ownership structure, and hostile takeovers. Journal of Financial Economics 1993;16:167-198.
38. Srinivasan V, Kim Y. Designing expert financial systems: A case study of corporate credit management. Financial Management 1988(Autumn):32-44.
39. Srivastava RP, Datta D. Belief-function approach to evidential reasoning for acquisition and merger decisions. In: Srivastava RP, Mock T, eds. Belief Functions in Business Decisions, Physica-Verlag, Heidelberg, Springer-Verlag Company, 2002;222-251.
40. Theidossiou P, Kahya E, Saidi R, Philippatos G. Financial distress and corporate acquisitions: Further empirical evidence. Journal of Business Finance and Accounting 1996;23(5/6):699-719.
41. Weiss SM, Kulikowski CA. Computer Systems That Learn. San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1991.
42. Zairko W, The discovery, analysis, and representation of data dependencies in databases. In: Piatetsky-Shapiro G, Frawley WJ, eds. Knowledge Discovery in Databases, Menlo Park, CA, Cambridge, MA: AAAI Press/The MIT Press, 1991:195-209.
43. Zadeh LA. The role of fuzzy logic in the management of uncertainty in expert systems. Fuzzy Sets and Systems 1983;11:199-227.