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Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming

G. Srinaganya1

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 156-160, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.156160

Online published on Jul 31, 2018

Copyright © G. Srinaganya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: G. Srinaganya, “Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.156-160, 2018.

MLA Style Citation: G. Srinaganya "Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming." International Journal of Computer Sciences and Engineering 6.7 (2018): 156-160.

APA Style Citation: G. Srinaganya, (2018). Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming. International Journal of Computer Sciences and Engineering, 6(7), 156-160.

BibTex Style Citation:
@article{Srinaganya_2018,
author = {G. Srinaganya},
title = {Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {156-160},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2410},
doi = {https://doi.org/10.26438/ijcse/v6i7.156160}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.156160}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2410
TI - Simulation of Stochastic Geometric Brownian Motion of Stock Market – Using R Programming
T2 - International Journal of Computer Sciences and Engineering
AU - G. Srinaganya
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 156-160
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

In the Prediction of total stock index, many are faced with some parameters as they are uncertain in future and they can undergo changes, and this uncertainty has a few risks, and for a true analysis, the calculations should be performed under risk conditions. The empirical tests suggest that the stochastic differential equation of GBM model can be used to predict the direction of stock price movement. In terms of predicting the stock price values, the empirical findings suggest that the GBM model performs well in stock market.

Key-Words / Index Term

Prediction, Stock index, Geometric Brownian Motion (GBM), Stochastic differential equation, Stock Market

References

[1] Elias M. Stein, Jeremy C. Stein “Stock Price Distributions with Stochastic Volatility: An Analytic Approach”, The Review of Financial Studies, Vol.4, Issue.4, pp.727-752, 1991.
[2] Sottinen T. “Fractional Brownian motion, random walks and binary market models”, Finance and Stochastics, Vol.5, Issue.3, pp.343-355, 2001.
[3] Merton RC. “Optimum consumption and portfolio rules in a continuous-time model”, Elsevier Publisher, pp. 621-661, 1975.
[4] Marathe RR, Ryan SM. “On the validity of the geometric Brownian motion assumption”, The Engineering Economist, Vol.50, Issue.2, pp.159-192, 2005.
[5] Hu Y, Øksendal B. “Optimal time to invest when the price processes are geometric Brownian motions”, Finance and Stochastics, Vol.2, Issue.3, pp.295-310, 1998.
[6] Rascanu A. “Differential equations driven by fractional Brownian motion”, Collectanea Mathematica. Vol.53, Issue.1, pp.55-81, 2002.
[7] Kramers HA. “Brownian motion in a field of force and the diffusion model of chemical reactions”, Physica, Vol.7, Issue.4, pp.284-304, 1940.
[8] stali FA, Picchetti P. “Geometric Brownian motion and structural breaks in oil prices: a quantitative analysis”, Energy Economics, Vol.24, Issue.4, pp.506-522, 2006.
[9] Coutin L, Qian Z. “Stochastic analysis, rough path analysis and fractional Brownian motions”, Probability theory and related fields, Vol.122, Issue.1, pp.108-140, 2002.
[10] He Z. “Optimal executive compensation when firm size follows geometric brownian motion”. The Review of Financial Studies, Vol.22, Issue.2, pp.859-892, 2008.