Aplicación de los conjuntos borrosos a las decisiones de inversión

Based on the genesis of a generalized theory of uncertainty, this article deals with the importance of using a fuzzy logic approach in economics and finance, with the purpose of defining the non stochastic character of uncertainty of one of the main financial decision-making criteria: current net va...

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Autores:
Juan Carlos Gutiérrez Betancur
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
spa
OAI Identifier:
oai:repository.eafit.edu.co:10784/14063
Acceso en línea:
http://hdl.handle.net/10784/14063
Palabra clave:
Uncertainty modeling
fuzzy triangular numbers
fuzzy interest rates
fuzzy net present value.
Incertidumbre
números triangulares borrosos
tasas de interés borrosas
valor presente neto borroso
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License
Copyright © 2006 Juan Carlos Gutiérrez Betancur
Description
Summary:Based on the genesis of a generalized theory of uncertainty, this article deals with the importance of using a fuzzy logic approach in economics and finance, with the purpose of defining the non stochastic character of uncertainty of one of the main financial decision-making criteria: current net value. To achieve this objective we have designed fuzzy triangular numbers, in order to get the fuzzy current net value; incorporating the gradual nature of financial decision making and the granularity of the human thinking process. We describe an example related to investment project finance valuation using fuzzy interest rates. In this article, we propose that there are some aspects of the state or nature that limits the complete application of well defined probability distributions for the purpose of parameter estimation of investment valuation which are unknown, due to questions like the “private” risk profile of a firm or project, the illiquidity of some of its assets, the absence of precise portfolio replication strategies, and other factors. In these cases, we can use fuzzy triangular numbers or fuzzy random numbers.