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Abstract

Financial mangers have to make decisions under many restrictions and often have to deal with vague and imprecise information. In multicriteria problems, the best solution is sought in a set X of alternatives under certain constraints with rates of contentment μ t : X → [0,1]. Considering these rates as membership functions, the tools that fuzzy logic provides is adequate to solving a multicriteria investment problem. In this paper, a fuzzy approach for assessing the quality of an asset and making an investment decision based on this assessment is proposed.

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Reference

  1. Wilder W., New concepts in Technical Trading Systems, Greenboro, NC:Trend Research, 1978

    Google Scholar 

  2. Risk measurement and systemic risk, Proceedings of the Third Joint Central Bank Research Conference, October 2002

    Google Scholar 

  3. Lo, Andrew W.; Mamaysky, Harry; Wang, Jiang. Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. NBER, Cambridge, March 2000

    Google Scholar 

  4. Ramík J., Soft Computing: Overview and Recent Developments in Fuzzy Optimization, Listopad 2001

    Google Scholar 

  5. Altrock C., Fuzzy Logic & NeuroFuzzy Applications in Business and Finance, Prentice hall PTR 1995

    Google Scholar 

  6. Dong, Ming; Zhou, Xu-Shien. Exploring the Fuzzy Nature of U.S. Stock Market. INCONIP’02-FSKD’02, Singapore, 2002

    Google Scholar 

  7. Judge, G. G., R. C. Hill, W. E. Griffiths, H. Lutkepohl, and T.-C. Lee. Introduction to the Theory and Practice of Econometrics, New York, Wiley, 1988

    MATH  Google Scholar 

  8. Sharp W., Investments, Prentice-Hall, 1978

    Google Scholar 

  9. J.F. Baldwin, “Fuzzy logic and fuzzy reasoning,” in Fuzzy Reasoning and Its Applications, E.H. Mamdani and B.R. Gaines (eds.), London: Academic Press, 1981

    Google Scholar 

  10. Todorov D., Mihovski I., An Interactive System for Providing and Updating Financial Information , Bourgas Free University, 2006, ISSN: 1311-221-X

    Google Scholar 

  11. www.mathworks.com

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© 2008 Springer Science+Business Media B.V.

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Popchev, I., Georgieva, P. (2008). A Fuzzy Approach to Solving Multicriteria Investment Problems. In: Iskander, M. (eds) Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8739-4_75

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  • DOI: https://doi.org/10.1007/978-1-4020-8739-4_75

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-8738-7

  • Online ISBN: 978-1-4020-8739-4

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