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Fuzzy Investment Analysis Using Capital Budgeting and Dynamic Programming Techniques

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Computational Intelligence in Economics and Finance

Part of the book series: Advanced Information Processing ((AIP))

Abstract

In an uncertain economic decision environment, an expert’s knowledge about discounting cash flows consists of a lot of vagueness instead of randomness. Cash amounts and interest rates are usually estimated by using educated guesses based on expected values or other statistical techniques to obtain them. Fuzzy numbers can capture the difficulties in estimating these parameters. Ill this chapter, the formulas for the analysis of fuzzy present value, fuzzy equivalent uniform annual value, fuzzy future value, fuzzy benefit-cost ratio, and fuzzy payback period are developed and given sonic numeric examples. Then the examined cash flows are expanded to geometric and trigonometric cash flows and using these cash flows fuzzy present value, fuzzy future value, and fuzzy annual value formulas are developed for both discrete compounding and continuous compounding. The fuzzy dynamic programming is applied to the situation where each investment in the set has the following characteristics: the amount to be invested has several possible values, and the rate of return varies with the amount invested. Each sum that may be invested represents a distinct level of investment, and the investment therefore has multiple levels. A fuzzy present worth based dynamic programming approach is used. A numeric example for a multilevel investment with fuzzy geometric cash flows is given. A computer software named FUZDYN is developed for various problems such as alternatives having different lives, different uniform cash flows, and different ranking methods.

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Author information

Authors and Affiliations

  1. Industrial Engineering Department, Istanbul Technical University, 80680, Maçka, Istanbul, Turkey

    Cengiz Kahraman & Cafer Erhan Bozdağ

Authors
  1. Cengiz Kahraman
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  2. Cafer Erhan Bozdağ
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Editor information

Editors and Affiliations

  1. AI-ECON Research Center Department of Economics, National Chengchi University, 11623, Taipei, Taiwan

    Shu-Heng Chen

  2. Department of Electrical and Computer Science, Duke University, P.O. 90291, 27708-0291, Durham, NC, USA

    Paul P. Wang

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© 2004 Springer-Verlag Berlin Heidelberg

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Kahraman, C., Bozdağ, C.E. (2004). Fuzzy Investment Analysis Using Capital Budgeting and Dynamic Programming Techniques. In: Chen, SH., Wang, P.P. (eds) Computational Intelligence in Economics and Finance. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06373-6_3

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  • DOI: https://doi.org/10.1007/978-3-662-06373-6_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-07902-3

  • Online ISBN: 978-3-662-06373-6

  • eBook Packages: Springer Book Archive

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