We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Monte Carlo Method and Brownian Movement Applied to Future Stock Market Analysis

by Fabio Lopes Licht
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 34
Year of Publication: 2020
Authors: Fabio Lopes Licht
10.5120/ijca2020920898

Fabio Lopes Licht . Monte Carlo Method and Brownian Movement Applied to Future Stock Market Analysis. International Journal of Computer Applications. 175, 34 ( Dec 2020), 1-6. DOI=10.5120/ijca2020920898

@article{ 10.5120/ijca2020920898,
author = { Fabio Lopes Licht },
title = { Monte Carlo Method and Brownian Movement Applied to Future Stock Market Analysis },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 34 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number34/31666-2020920898/ },
doi = { 10.5120/ijca2020920898 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:12.739019+05:30
%A Fabio Lopes Licht
%T Monte Carlo Method and Brownian Movement Applied to Future Stock Market Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 34
%P 1-6
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a method of forecasting the return on investment on the stock exchange based on the historical analysis of the stock and the generation of massive random data. The model is based on the use of the Monte Carlo method and on the Simulation of the Brownian Movement with a massive generation of data to generate forecasts of growth or decrease in the value of the stock over a given time. As a model test, stock market indices in Brazil and historical stock data were used.

References
  1. Mohammad Al-Shiab. The predictability of the amman stock exchange using the univariate autoregressive integrated moving average (arima) model. Journal of Economic and Administrative Sciences, 22, 12 2006.
  2. Francesca Biagini, Yaozhong Hu, Bernt ksendal, and Tusheng Zhang. Stochastic Calculus for Fractional Brownian Motion and Applications. Springer-Verlag London, 01 2008.
  3. Paolo Brandimarte. Front Matter, pages i–xvii. John Wiley & Sons, Ltd, 2014.
  4. A. Einstein. Investigations on the Theory of the Brownian Movement. Dover Books on Physics Series. Dover Publications, 1956.
  5. Como baixar cotas de fundos de investimento da cvm para o excel.
  6. David R. Harper. How to use monte carlo simulation with gbm, Aug 2020.
  7. Ibovespa: B3.
  8. BONA L.C.E LICHT F.L., SCHULZE B. Afinidade de Tipos de Aplicacoes em Nuvens Computacionais. New Academic Editions, 06 2019.
  9. Modelos arima.
  10. Movimento browniano.
  11. Rizwan Mushtaq. Augmented dickey fuller test. SSRN Electronic Journal, page Augmented Dickey Fuller Test, 08 2011.
  12. R.Y. Rubinstein and D.P. Kroese. Simulation and the Monte Carlo Method: Third Edition. Wiley, 11 2016.
  13. Archived: Who timeline - covid-19.
Index Terms

Computer Science
Information Sciences

Keywords

Monte Carlo Method Market Activity Brownian Motion

Powered by PhDFocusTM