Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Heuristic analysis of a near optimal approximation algorithm for the determination of investment options
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Keywords

Common sense reasoning
knowledge representation
soft decision making
greedy algorithms
financial analysis
Razonamiento de sentido común
representación de conocimiento
toma de decisiones
algoritmos voraces
análisis financiero

How to Cite

Flores, J., Ávila, J., González, F., & Flores, B. (2006). Heuristic analysis of a near optimal approximation algorithm for the determination of investment options. Revista De Matemática: Teoría Y Aplicaciones, 13(2), 125–138. https://doi.org/10.15517/rmta.v13i2.273

Abstract

When cash becomes available in a company, there are several strategies that allow us to benefit from it. The problem is how much to invest, for how long, and using which of the investment options in order to get the maximum profit out of it. A common problem in business administration is that we do not want to keep the money idle in the checking account, neither to over-invest. When the cash function becomes negative an analogous scheme is used as we want to pay as little interests as possible. In this paper we are reporting the experiments and implementation of several heuristics that can be used with the greedy algorithm and how well they behave. Finally we develop a hybrid algorithm that takes the best of the greedy algorithm and performs a very limited search. We find in this work that with the greedy algorithm we use, in general is not possible to optimize the profit for a given function; nevertheless the algorithm we use can find profits that are very close to the optimum and in some cases it gets the optimum. The proposed algorithm use a heuristic search based on the greedy scheme and greedy selection criteria to find profits close to the optimum. A software application was developed in order to show that the proposed strategy really works. Although this algorithm is suboptimal, it is very efficient in terms of time.

https://doi.org/10.15517/rmta.v13i2.273
PDF (Español (España))

References

Brassard G.; Bratley, P. (1997) Fundamentos de Algoritmia. Prentice-Hall, Madrid.

Cormen, T. H.; Leiserson, C. E.; Rivest, R. L.; Stein, C. (2001) Introduction to Algorithms. The MIT Press, Cambridge, Mass.

Flores, J.; González, F.; Flores, B. (2003) “Greedy determination of investment options”, preprint, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, México.

Martello, S.; Toth, P. (1990) Knapsack Problems Algoritms and Computer Implementations. John Wiley & Sons, Chichester, England.

Russell, S. J.; Norvig, P. (1995) Artificial Intelligence: A Modern Approach. Prentice-Hall, New Jersey.

Terceño, A.; de Andrés, J.; Barberà, M.G. (2001) “The use of fuzzy programming for the management of immunised fixed income portfolios, in: Fuzzy Set Systems in Management and Economy. World Scientific, Singapur.

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