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A fuzzy expert system for solving real-option decision processes

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Author Info
Carlo Alberto Magni ()

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Abstract

This paper presents a new approach to real options. The current options-based models have provided new insights into capital-budgeting decisions. Unfortunately they are not widely used by corporate managers and practitioners as they are formally complex, rather difficult to understand and rest on strong implicit assumptions that considerably limit their scope of application. We propose a possible alternative by using a fuzzy expert system, on the basis of Mastroleo, Facchinetti and Magni (2001). We draw up a decision tree with multiple uncertain variables affecting the value of an investment opportunity, consisting of a defer option, a growth option, an abandonment option. Some simulations are conducted to test the economic soundness of the model as well as its consistency with the current models in the literature. A rather refined study can be accomplished by showing how inputs and outputs of the model interrelate one another.

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Publisher Info
Paper provided by UNIVERSIDAD TECNOLÓGICA DE BOLÍVAR in its series Documentos de Trabajo with number 005677.

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Length: 24
Date of creation: 19 Jun 2009
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Handle: RePEc:col:000162:005677

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  1. Magni, Carlo Alberto, 2004. "An alternative approach to firms’ evaluation: expert systems and fuzzy logic," MPRA Paper 7879, University Library of Munich, Germany. [Downloadable!]
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  2. Magni, Carlo Alberto, 2007. "Investment decisions, net present value and bounded rationality," MPRA Paper 6073, University Library of Munich, Germany. [Downloadable!]
  3. Magni, Carlo Alberto, 2007. "Rating and ranking firms with fuzzy expert systems: the case of Camuzzi," MPRA Paper 5646, University Library of Munich, Germany. [Downloadable!]
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  4. Malagoli, Stefano & Mastroleo, Giovanni & Magni, Carlo Alberto, 2005. "The use of fuzzy logic and expert systems for rating and pricing firms: a new perspective on valuation," MPRA Paper 11958, University Library of Munich, Germany. [Downloadable!]
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This page was last updated on 2009-11-18.


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