El peso mexicano: la gestión de cobertura del riesgo cambiario mediante la teoría de los efectos olvidados

Authors

  • Ricardo Salazar Garza Universidad de Monterrey, México

DOI:

https://doi.org/10.46631/jefas.2012.v17n32.05

Keywords:

Exchange rate, Fuzzy Logic, Future Markets Experts, Forgotten Effects, Expertones

Abstract

This paper is about developing a nonlinear model to predict the behavior of future exchange rate based on the opinion of the economic agents participating in the dollar/peso market. Such views are treated with Fuzzy Logic and a variant of it, known as the Theory of Forgotten Effects. The aim is to find a mechanism for making coverage decisions that allow us an optimal exchange rate risk management at a lower cost than that which involves operations with traditional hedging instruments. For the period of investigation and applying this model, the results support that the collective opinions of economic experts involved in the decision making risk management of exchange rate provide better results than those using traditional methods in the future markets

Downloads

Download data is not yet available.

References

Backus, D. (1984). Empirical Models of the Exchange Rate: Separating the Wheat form de Shaff. The Canadian Journal of Economics, 17(4), 824-846.

Bazdresch, S., & Werner, A. (2002). El comportamiento del tipo de cambio en México y el régimen de libre flotación 1996-2001. Banco de México. Documento de Investigación 9,1-18.

Bojadziev, G. M., & Bojadziev, M. (1997). Fuzzy Logic for Business. Finance and Management. World Scientific. Recabado de <http://books.google. com.mx/books?id=a3dn0qP6q1sC&pg=PA93&lpg=PA93&dq=Bojadziev,+G.+M.,+%26+Bojadziev,+M&source=bl&ots=2iL0DThd6o&sig=F

o--2L3SmvGYvy8G9Oi6PddLOwI&hl=es#v=onepage&q&f=false>.

Cortez, K. (2004). Dinámica no lineal del tipo de cambio: aplicación al mercado mexicano. Tesis Doctoral. Universitat de Barcelona. España.

De Grauwe, P., Dewchter, H., & Embrechts, M. (1993). Exchange Rate Theory: Chaotic Models of Foreign Exchange Markets. London: Blackwell.

Elizondo, E., & Sepúlveda, E. (2004). Fundamentos de política cambiaria. Ejecutivos de Finanzas, 20, 36-39.

Fung, I. (2005). A Neuron-Fuzzy Computing Technique for Modeling the Time Series of Short-term Exchange Rates. Journal of American Academy of Business, September, 176.

Gil, D. F., & Carstens, A. (1996). Some Hypothesis Related to the Mexican 1994-95 Crisis, (Documento de Investigación 9601). Consultado el 17/02/06 en . referencias

Goldberg, L., & Tenorio, R.(1997). Strategic Trading in a Two-sided Foreign Exchange Auction. Journal of International Economics, 42, 299-326.

Gradojevic, N. (2002). Non-linear Exchange Rate Forecasting: The Role of Market Microestructure Variables. Doctoral Thesis. University of British Columbia, Vancouver, Canada.

Hull, J. (2002). Introducción a los mercados de futuros y opciones. Madrid, España: Prentice Hall.

Kaufmann A., & Gil-Aluja, J. (1986). Introducción a la teoría de los subconjuntos borrosos para la gestión de las empresas. Santiago de Compostela, España: Milladoiro.

Kosko, B. (1995). Fuzzy Thinking, the New Science of Fuzzy Logic. New York: Hyperion Books.

Lyons, R. K., & Evans, M. D. D. (2002). Order Flow and Exchange Rate Dynamics. Journal of Policy Economics, 110(1), 170-180.

Messe, R. A., & Rogoff, K. (1983). Empirical Exchange Rate Models of the Seventies: Do they Fit Out of Sample? Journal of International Economics.14(1), 3-24.

Murray, R. (2005). Keeping up with World Currencies. CMA Management, 78(8), 17, ABI/INFORM Global.

Nance, D. A. (2002). Reliability and the Admissibility of Experts. Seton Hall Law Review, 34, 191-249.

Ortiz, G. (2004). The Mexican Experience under a Floating Exchange Rate Regime. Consultado 31/01/06

Rupeika-Apoga, R. (2005). Nowadays Approach to Foreign Exchange Risk Management. ABI/INFORM Global.151: OrganizacijǿVadyba: SisteminiaiTyrimai.

Tichy, G. (2002). Over-optimism among Experts in Assessment and Foresight. Institute of TechnologyAssessment. Consultado el 19/03/08 en <http://www.oeaw.ac.at/ita/pdef/ita_02_05.pdf>.

Varela, J. A. (2001). Lógica borrosa y sus aplicaciones. (ICAI, 8. Documento de la UCLM). España: Universidad de Castilla-La Mancha y la Universidad

Pontificia Comillas. pp. 56-74.

Wu, I. F., & Goo,Y. J. (2005). A Neuron Fuzzy Computing Technique for Modeling the Time Series of Short Term NT$/US$ Exchange Rate. Journal of AmericanAcademy of Business, 7(2), 176.

Yao, J. (1997). Spread Components and Dealer Profits in the Interbank Foreign Exchange Market. (Working paper S/98/04). New York: University SalomonCenter, 1-54.

Zadeh, L. (1972). A Fuzzy-Set-Theoretic Interpretation ofLinguistic Hedges. Journal of Cybernetics, 2, 4-34.

Downloads

Published

2012-06-30

How to Cite

Salazar Garza, R. . (2012). El peso mexicano: la gestión de cobertura del riesgo cambiario mediante la teoría de los efectos olvidados . Journal of Economics, Finance and Administrative Science, 17(32), 53–73. https://doi.org/10.46631/jefas.2012.v17n32.05