The Monte Carlo method of random simulation samples

Autores/as

DOI:

https://doi.org/10.32870/myn.vi50.7710

Palabras clave:

Monte Carlo method, random simulation samples, finance, economy, index

Resumen

The Monte Carlo method is one of the most powerful mathematical techniques that, through calculation, analyzes risk and allows solving physical and mathematical problems through computer programs. Using historical data creates and predicts models of possible future results by substituting a range of values, calculating results repeatedly, and using a different group of random values of the probability functions to predict the potential effects of some uncertain event related to problems of all kinds.

Citas

BANXICO. (2023). Sistema de Información Económica. México, Banco de México. Link: http://www.inegi.org.mx/sistemas/bie/

Eppen, G. D. (2000). Operations Research in Administrative Science. Prentice-Hall, Inc.

Gentle, J. E. (2013). Random Number Generation and Monte Carlo Methods. Springer Science & Business Media.

INEGI. (2023). Banco de Información Económica. Mexico: Instituto Nacional de Geografía y Estadística. Link: http://www.inegi.org.mx/sistemas/bie/

Metropolis, N. & Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association. 44(247)

Ulam, S. M. (1983). Adventures of a Mathematician. Charles Scripner's Sons.

Vargas, J. C. & Cruz-Carpio, C. A. (2020). Study of the Monte Carlo method in simulations for the estimation of the π value. Bolivian Journal of Physics. 36.

Publicado

2023-09-01

Cómo citar

Gaytán Cortés, J. . (2023). The Monte Carlo method of random simulation samples. Mercados Y Negocios, (50), 95–108. https://doi.org/10.32870/myn.vi50.7710

Número

Sección

Indicadores Financieros y Económicos

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